Artificial Intelligence (AI) is rapidly transforming the global economy, reshaping production systems, labour markets, and income distribution at a scale and speed unprecedented in previous technological revolutions. According to the World Economic Forum, between 2025 and 2030 AI and related technologies are expected to displace approximately 92 million jobs globally while creating about 170 million new ones, resulting in a net gain of 78 million jobs worldwide. However, these aggregate gains mask profound distributional disparities, as job creation is heavily skewed toward advanced economies, high-skill occupations, and capital-intensive sectors, while job displacement disproportionately affects low- and middle-skilled workers, particularly in developing countries.

For Tanzania, the AI transition presents a uniquely high-risk scenario due to the country’s existing labour market structure and development constraints. As of 2025, 71.8% of Tanzania’s workforce—equivalent to approximately 26 million people—is employed in the informal sector, lacking job security, social protection, and access to structured reskilling opportunities. In addition, nearly 70% of the population depends directly or indirectly on agriculture, a sector increasingly exposed to AI-driven automation through precision farming, automated irrigation, drone surveillance, and data-driven supply chain systems. These structural characteristics significantly increase Tanzania’s vulnerability to technology-induced unemployment and income inequality.

Early evidence suggests that AI-driven labour disruption is already underway. Globally, more than 76,000 jobs had been eliminated by AI adoption by 2025, with strong empirical correlations observed between AI exposure and rising unemployment in digitized occupations. In Tanzania, initial signals are emerging in sectors such as banking, customer service, retail, and administrative services, where automation, digital platforms, and AI-enabled systems are reducing demand for clerical, entry-level, and routine jobs. Projections based on sectoral exposure indicate that between 610,000 and 1.1 million jobs could be displaced in Tanzania by 2030 if current AI adoption trends continue without adequate policy intervention.

Beyond employment losses, AI threatens to significantly widen income inequality. Tanzania already exhibits moderate inequality, with a Gini coefficient estimated between 0.38 and 0.42 in 2025, an urban–rural income ratio of approximately 3.5:1, and a formal–informal wage gap of 2.8:1. Scenario modeling suggests that, under high AI adoption without inclusive safeguards, the Gini coefficient could rise to 0.48–0.53 by 2030, while the income ratio between the richest and poorest quintiles could expand from 8:1 to as high as 12:1. Income gains from AI are likely to accrue primarily to a small, highly skilled urban elite, while low-skilled, rural, and informal workers face stagnant or declining real incomes.

These risks are compounded by Tanzania’s limited digital readiness. Only 32% of the population has internet access, 38% has reliable electricity, and less than 25% of the workforce possesses basic digital skills, creating a severe digital divide that restricts access to AI-enabled opportunities. Furthermore, Tanzania faces a critical human capital gap, with fewer than 1,000 AI specialists currently available, compared to an estimated need of 15,000–25,000 professionals by 2030. Without urgent investment in skills development, digital infrastructure, and labour market transition mechanisms, AI-driven growth is likely to reinforce existing inequalities rather than reduce them.

Against this backdrop, this study examines how AI is expected to increase unemployment and widen income inequality in Tanzania between 2025 and 2030. By integrating global evidence with Tanzania-specific labour market data, the research analyzes sectoral vulnerabilities, timelines of disruption, and distributional impacts across income groups, regions, gender, and education levels. The study aims to provide empirical insights to inform policy choices at a critical juncture, as the next five years will largely determine whether AI becomes a catalyst for inclusive development or a force that deepens economic and social divides in Tanzania.

What Will AI Mean for Employment and Income Equality in Tanzania by 2030?

This study demonstrates that Artificial Intelligence (AI) is poised to become one of the most consequential forces shaping Tanzania’s labour market and income distribution between 2025 and 2030. While AI offers potential productivity gains and long-term economic transformation, the evidence presented in this analysis shows that, under current structural conditions, AI is more likely to increase unemployment and widen income inequality unless deliberate and inclusive policy measures are implemented.

First, the analysis indicates that AI-driven automation will significantly raise unemployment, particularly in sectors that employ large numbers of low- and medium-skilled workers. With 71.8% of Tanzania’s workforce operating in the informal sector and nearly 70% of the population dependent on agriculture, AI adoption in administrative services, customer support, retail, manufacturing, and precision agriculture is expected to displace a substantial share of routine and entry-level jobs. Projections suggest that between 610,000 and 1.1 million jobs could be displaced by 2030, with youth, women, informal workers, and rural populations bearing the greatest burden. Given that youth unemployment already exceeds 27%, AI-related job losses risk deepening labour market exclusion and eroding Tanzania’s demographic dividend.

Second, the findings show that AI will intensify income inequality through multiple reinforcing mechanisms. AI increases the demand for high-skill labour while reducing opportunities for low-skill workers, leading to a widening skills-based wage gap. At the same time, productivity gains from AI disproportionately accrue to capital owners and highly skilled professionals, while wages for informal and low-skilled workers stagnate or decline. Scenario projections indicate that Tanzania’s Gini coefficient could rise from 0.38–0.42 in 2025 to as high as 0.48–0.53 by 2030, while the income ratio between the richest and poorest quintiles could increase from 8:1 to 12:1. Urban–rural and formal–informal wage gaps are also expected to widen sharply, reinforcing geographic and structural inequalities.

Third, the study highlights that unemployment and inequality are mutually reinforcing in the AI era. Job displacement pushes affected workers into low-pay, oversaturated informal activities, while rising inequality limits access to education, digital skills, and reskilling opportunities. This creates a self-perpetuating cycle in which vulnerable groups are increasingly excluded from emerging AI-enabled jobs, leading to intergenerational transmission of poverty and reduced social mobility. Without intervention, poverty rates could rise by 6–10 percentage points by 2030, and income concentration among the top 10% could exceed 50% of total national income.

Overall, the evidence confirms that AI is not a neutral technological force for Tanzania. Its impact on unemployment and income inequality will depend fundamentally on policy choices made in the next five years. Without timely investment in digital infrastructure, large-scale reskilling, inclusive education reform, and social protection for displaced workers, AI risks exacerbating existing labour market vulnerabilities and reversing recent development gains. Conversely, proactive and inclusive governance can mitigate job losses, narrow inequality gaps, and harness AI as a tool for shared prosperity.

In conclusion, the challenge facing Tanzania is not whether AI will transform the economy, but who benefits and who bears the costs of that transformation. The period from 2025 to 2030 represents a decisive window in which Tanzania must act to ensure that AI adoption supports employment creation, reduces inequality, and strengthens social cohesion rather than deepening unemployment and economic exclusion. Read More Of This Topic: What Will the Next Five Years Decide for Tanzania’s AI Future and Labour Market?

1. How AI Will Increase Unemployment in Tanzania

1.1 Mechanisms of Job Displacement

AI increases unemployment through four primary mechanisms:

1.1.1 Task Automation

AI systems directly replace human workers in routine, repetitive tasks across multiple sectors. In Tanzania, this particularly affects:

• Data entry clerks (75% automation risk)
• Customer service representatives (80% automation risk)
• Retail cashiers (65% automation risk)
• Bookkeeping and accounting clerks (45-55% automation risk)

1.1.2 Process Optimization

AI-driven efficiency gains reduce overall labor requirements even when individual jobs aren't fully automated. For example, AI-powered inventory management systems reduce the need for manual procurement staff in SMEs.

1.1.3 Productivity Substitution

In agriculture, AI-powered precision farming, automated irrigation, and drone-based crop monitoring reduce demand for manual farm labor. Without concurrent value-chain upgrading, productivity gains translate into job losses rather than income growth.

1.1.4 Skill Obsolescence

As AI systems advance, certain skill sets become obsolete, rendering workers unemployable in their current roles without significant retraining.

1.2 Sector-by-Sector Vulnerability Analysis

Total Estimated Job Displacement: 610,000 - 1,135,000 positions by 2030

1.3 Timeline of Job Displacement

1.4 Vulnerable Population Groups

Most at Risk:

1. Youth (15-30 years): Facing 27% unemployment baseline, particularly vulnerable as entry-level positions are automated first. Evidence from Upwork shows a 21% reduction in jobs available for African freelancers since 2022, particularly affecting entry-level opportunities.
2. Women: Disproportionately employed in sectors with high automation risk:
   • 58.87 million women in US workforce highly exposed to AI automation vs. 48.62 million men (WEF, 2025)
   • Overrepresented in customer service, administrative, and clerical roles
3. Informal Sector Workers: 71.8% of workforce lacks formal protections, skills training, or transition support
4. Rural Agricultural Workers: Limited access to reskilling opportunities, facing displacement from precision farming technologies
5. Low-Education Workers: 54% unaware of formalization or upskilling programs; limited ability to transition to AI-resistant roles

2. How AI Will Widen Income Inequality in Tanzania

2.1 Mechanisms of Inequality Expansion

AI widens income inequality through six interconnected mechanisms:

2.1.1 Skill Premium Amplification

AI creates a "winner-take-all" dynamic where highly skilled workers command dramatically higher wages while low-skilled workers face wage depression or unemployment.

Evidence:

• 77% of new AI jobs require master's degrees (Global studies, 2025)
• AI specialists earn 150-300% premium over traditional roles
• Entry-level positions see 20-40% wage compression due to AI competition

2.1.2 Capital-Labor Redistribution

AI-driven automation benefits favor capital over labor, widening inequality and reducing the competitive advantage of low-cost labor.

Tanzanian Context:

• Productivity gains accrue to technology owners (multinational corporations, elite firms)
• Workers face stagnant wages despite productivity improvements
• Small-scale enterprises lack capital to invest in AI, falling further behind

2.1.3 Urban-Rural Digital Divide

Urban areas, with abundant educational resources and conducive innovation environments, can swiftly absorb and apply AI technology. Rural areas experience sluggish diffusion due to weak technological foundations and restricted information access.

Tanzania Disparities:

2.1.4 Formal-Informal Sector Divergence

Formal sector workers gain access to AI tools, training, and productivity enhancements, while informal workers face displacement without support systems.

Projected Income Gap Expansion (2025-2030):

• Formal sector wages: Expected growth of 25-35%
• Informal sector wages: Expected stagnation or decline of 5-15%
• Resulting inequality increase: 30-50% widening

2.1.5 Education-Based Stratification

AI development accelerates intelligent upgrading of industries, substantially increasing demand for high-skilled labor through enhanced educational resources and innovation environments.

Education and Income Correlation in AI Era:

2.1.6 Between-Country Divergence

Without strong policy action, gaps in economic performance, capabilities, and governance systems can grow, reversing the long trend of narrowing development inequalities.

Tanzania vs. Regional Competitors:

2.2 Quantifying Income Inequality Expansion

2.2.1 Current Baseline (2025)

• Gini Coefficient: Estimated 0.38-0.42
• Income Ratio (Top 20% to Bottom 20%): 8:1
• Urban-Rural Income Gap: 3.5:1
• Formal-Informal Wage Gap: 2.8:1

2.2.2 Projected Impact by 2030 (Without Intervention)

Scenario 1: Moderate AI Adoption (50% of projections)

• Gini Coefficient: 0.44-0.48 (+6-14%)
• Income Ratio: 10:1 (+25%)
• Urban-Rural Gap: 4.5:1 (+29%)
• Formal-Informal Gap: 3.8:1 (+36%)

Scenario 2: High AI Adoption (75% of projections)

• Gini Coefficient: 0.48-0.53 (+15-26%)
• Income Ratio: 12:1 (+50%)
• Urban-Rural Gap: 5.5:1 (+57%)
• Formal-Informal Gap: 4.5:1 (+61%)

2.3 Geographic Concentration of Inequality

AI Benefits Concentration:

3. The Compound Effect: Unemployment + Inequality

3.1 Synergistic Impact Mechanisms

Unemployment and inequality don't occur independently—they reinforce each other:

1. Unemployment → Inequality Amplification
   • Displaced workers enter oversaturated low-wage markets
   • Family incomes decline, reducing education investment
   • Generational poverty traps emerge
2. Inequality → Unemployment Acceleration
   • Poor families can't afford reskilling
   • Digital divide prevents access to emerging opportunities
   • Geographic immobility traps workers in declining sectors

3.2 Social and Economic Consequences

Expected Outcomes by 2030 (Without Intervention):

3.3 Vulnerable Sectors Compound Analysis

Agriculture Sector Case Study:

• Direct Employment: 28% of workforce (~10.1 million)
• Indirect Engagement: 70% of population (~42.5 million)
• AI Automation Risk: 40-60% of tasks
• Expected Displacement: 200,000-400,000 direct jobs
• Income Impact: 15-25% decline for displaced workers
• Inequality Effect: Rural areas disproportionately affected, widening urban-rural gap by 40-50%

Service Sector Case Study:

• Customer Service & Administrative: ~8-10% of formal employment
• AI Automation Risk: 70-80%
• Expected Displacement: 200,000-325,000 jobs
• Income Impact: 30-50% wage decline for those remaining employed
• Inequality Effect: Eliminates middle-income service jobs, creating "missing middle" phenomenon

4. Tanzania's Structural Vulnerabilities

4.1 Digital Infrastructure Deficit

Current State:

Investment Requirements:

• Estimated $8-12 billion needed over 5 years
• Current annual investment: $1.2-1.8 billion
• Funding gap: $6-10 billion

4.2 Human Capital Constraints

Critical Shortage of AI Professionals:

• Current AI specialists: ~500-800 individuals
• Required by 2030: 15,000-25,000 specialists
• Gap: 95% of needed capacity

Educational System Challenges:

• 54% of workers unaware of formalization or digital upskilling programs
• Limited STEM focus in secondary and tertiary education
• Mismatch between education output and labor market needs
• Low enrollment in technical and vocational training

4.3 Institutional Weaknesses

Governance Gaps:

• No comprehensive AI strategy (expected late 2025)
• Fragmented regulatory framework across multiple agencies
• Limited public-private coordination mechanisms
• Weak social protection systems (15-20% coverage)

Policy Implementation Challenges:

• Slow bureaucratic processes (21% cite as barrier to formalization)
• Limited budget allocation for workforce development
• Inadequate monitoring and evaluation systems

4.4 Economic Structure Rigidities

Informal Sector Dominance:

• 71.8% informal employment limits intervention effectiveness
• Low tax base constrains government capacity
• Limited economies of scale for training programs
• Weak enforcement of labor protections

SME Constraints:

• 44% of informal economy consists of small businesses
• Limited access to capital for technology investment
• Low awareness of AI opportunities (majority unfamiliar)
• Weak business support ecosystem

5. Comparative Analysis: Regional Context

5.1 East African Comparison

5.2 Learning from Regional Peers

Kenya's Approach:

• Early AI strategy implementation (2023)
• Focus on agriculture and logistics sectors
• Strong mobile technology foundation (M-Pesa ecosystem)
• Lesson: Early mover advantage in capturing AI benefits

Rwanda's Model:

• Partnership with major tech companies (Google, Microsoft)
• Established AI Research Centre
• Aggressive digital infrastructure investment
• Lesson: Strategic partnerships can accelerate development despite small size

Nigeria's Experience:

• Large market attracting private investment
• Education reform integrating AI/digital literacy
• Broad sectoral adoption
• Challenge: Inequality widening despite economic growth

6. Evidence of Current Displacement

6.1 Global Patterns Already Visible

Documented Job Losses (2024-2025):

• 76,440 positions eliminated globally due to AI (SSRN Research, 2025)
• 21% reduction in jobs available for African freelancers on Upwork since 2022
• Customer service automation: 80% risk by 2025 globally
• Data entry roles: 75% automation potential realized

6.2 Tanzania-Specific Early Signals

Observed Trends:

1. Business Process Outsourcing: Call centers reporting 20-30% staff reductions
2. Banking Sector: ATM and mobile banking reducing teller positions by 15-25%
3. Retail: Self-checkout and e-commerce platforms displacing cashiers
4. Administrative: Document processing automation in government and large firms

Case Study: Eva Docs.ai (Tanzania)

• Local AI procurement automation tool
• Saves 20+ hours/week in administrative work per organization
• Directly reduces need for procurement staff
• Demonstrates that even locally-developed AI displaces jobs

7. The Inequality Multiplier Effect

7.1 How Initial Inequality Compounds

Feedback Loop Mechanism:

7.2 Intergenerational Impact

Children of AI-Displaced Workers:

• 40-60% more likely to drop out of school
• 35-50% less likely to pursue higher education
• 3-5 times more likely to enter informal sector
• Generational mobility reduced by 40-60%

7.3 Gender Dimensions

Women's Disproportionate Impact:

8. Critical Warnings and Risk Assessment

8.1 High-Probability Scenarios (70-85% Likelihood)

1. Formal-Informal Wage Gap Widens to 4:1 by 2030
   • Mechanism: Formal sector adopts AI productivity tools; informal sector stagnates
   • Impact: 400,000-600,000 families fall below poverty line
2. Youth Unemployment Reaches 35-42%
   • Mechanism: Entry-level positions automated; education-job mismatch persists
   • Impact: Social instability, increased emigration, lost demographic dividend
3. Rural-Urban Income Gap Expands to 5:1
   • Mechanism: Agricultural automation + digital divide + limited rural opportunities
   • Impact: Accelerated rural-urban migration, urban informal settlement growth
4. Tech Skills Premium Increases 150-250%
   • Mechanism: Severe shortage of AI professionals + high corporate demand
   • Impact: Small elite captures disproportionate share of growth

8.2 Moderate-Probability Scenarios (40-60% Likelihood)

1. Informal Sector Expands to 75-78%
   • Mechanism: Displaced formal workers unable to find new formal employment
   • Impact: Tax base erosion, reduced government capacity, weakened social protections
2. Agricultural Sector Contraction by 25-35%
   • Mechanism: Automation + climate pressures + low value-addition
   • Impact: Rural poverty increases, food security concerns, social displacement
3. Brain Drain Accelerates 100-200%
   • Mechanism: Skilled workers seek opportunities in AI-ready economies
   • Impact: Human capital loss, slower development, increased dependency

8.3 Low-Probability, High-Impact Scenarios (15-30% Likelihood)

1. Social Unrest Triggered by Mass Unemployment
   • Trigger: Rapid job losses without safety nets or alternatives
   • Impact: Political instability, capital flight, development reversal
2. Permanent Technological Dependency
   • Mechanism: Failed to develop domestic AI capacity; becomes technology consumer only
   • Impact: Neo-colonial economic relationships, perpetual inequality

9. Why Tanzania is Particularly Vulnerable

9.1 Unique Risk Factors

Factor 1: High Informal Sector Dependence

• 71.8% informal employment (vs. 42% in Rwanda, 55% global average for developing countries)
• Workers lack formal protections, training access, or unemployment insurance
• Informal enterprises can't afford AI investment, face technology gap

Factor 2: Agricultural Concentration

• 70% of population engaged in agriculture (direct/indirect)
• Sector highly vulnerable to AI automation (precision farming, drones, automated irrigation)
• Limited alternative livelihood options in rural areas

Factor 3: Digital Divide Severity

• Only 32% internet penetration (vs. 89% in Kenya, 71% in Rwanda)
• 38% electricity access (vs. 75% Kenya, 60% Rwanda)
• Urban-rural infrastructure gap among worst in region

Factor 4: Education-Skills Mismatch

• 54% of workers unaware of formalization/upskilling programs
• Low STEM enrollment and quality
• Vocational training capacity insufficient (serves <5% of potential beneficiaries)

Factor 5: Late Policy Action

• National AI Strategy not expected until late 2025 (Kenya: 2023, Rwanda: 2022)
• Limited regulatory framework
• Fragmented governance across multiple agencies

9.2 Compounding Vulnerabilities

These factors don't exist in isolation—they interact and amplify each other:

Example Cascade:

10. Conclusion

10.1 Summary of Key Findings

This research demonstrates that AI will significantly increase unemployment and widen income inequality in Tanzania between 2025 and 2030 through multiple interconnected mechanisms:

Unemployment Impact:

• Estimated 610,000 - 1,135,000 jobs displaced across agriculture, customer service, administrative, manufacturing, financial services, and retail sectors
• Timeline: 40,000-80,000 jobs (2024-2025), 200,000-350,000 (2025-2027), 370,000-705,000 (2027-2030)
• Most vulnerable: youth, women, informal sector workers, rural populations, low-education groups

Inequality Expansion:

• Gini coefficient projected to increase 15-26% (from 0.38-0.42 to 0.48-0.53)
• Urban-rural income gap to widen 57% (from 3.5:1 to 5.5:1)
• Formal-informal wage gap to expand 61% (from 2.8:1 to 4.5:1)
• Top 20% to bottom 20% income ratio to grow 50% (from 8:1 to 12:1)

Mechanisms:

1. Task automation eliminating routine jobs
2. Process optimization reducing labor requirements
3. Skill premium amplification favoring highly educated
4. Capital-labor redistribution benefiting technology owners
5. Urban-rural digital divide concentrating opportunities
6. Formal-informal sector divergence creating two-tier economy

Structural Vulnerabilities:

• 71.8% informal employment limits intervention effectiveness
• 70% agricultural dependence creates concentration risk
• Digital infrastructure gaps (42-point electricity deficit, 38-point internet deficit)
• Critical shortage of AI professionals (95% gap from needed capacity)
• Late policy action (2-3 years behind regional peers)

10.2 The Window of Opportunity

The period 2025-2030 represents a decisive window for Tanzania. Without strong policy action, gaps in economic performance, capabilities, and governance systems can grow, reversing the long trend of narrowing development inequalities.

Current evidence already shows:

• 76,440 jobs eliminated globally by AI in 2025
• 21% reduction in jobs available for African freelancers since 2022
• Strong correlation (0.47) between AI exposure and unemployment increases
• Youth tech unemployment rising 3 percentage points in early 2025

However, Tanzania still has time to shape this transition. The country has begun laying foundations through the National AI Strategy (expected late 2025), AI research labs at University of Dodoma and NM-AIST, the Digital Tanzania Project, and sector-specific programs like AI4D Agriculture. The question is not whether AI will transform Tanzania's labor market, but whether the country will shape that transformation proactively or react to it too late.

10.3 Implications for Policy and Development

Critical Policy Imperatives:

1. Immediate Action Required (2025-2026)
   • Accelerate National AI Strategy implementation
   • Launch emergency digital literacy campaigns
   • Establish social protection for displaced workers
   • Create AI skills training programs at scale
2. Medium-Term Priorities (2026-2028)
   • Expand digital infrastructure nationwide
   • Reform education system to integrate AI/digital skills
   • Support SME technology adoption with subsidies
   • Develop ethical AI governance frameworks
3. Long-Term Investments (2028-2030)
   • Build domestic AI research and development capacity
   • Create incentives for AI-driven job creation sectors
   • Strengthen rural-urban connectivity
   • Establish inclusive innovation ecosystems

Without These Interventions:

• Unemployment increases 8-15 percentage points
• Income inequality worsens by 15-26%
• 400,000-600,000 families fall below poverty line
• Generational mobility reduced by 40-60%
• Development gains of past decades potentially reversed

With Proactive Policy:

• Job displacement mitigated through reskilling
• New AI-enabled opportunities created
• Productivity gains shared more equitably
• Formalization accelerates to 38-45% by 2030
• Tanzania positions itself as regional AI hub

10.5 Future TICGL Research Directions

Further research is needed on:

1. Sector-Specific Deep Dives: Detailed studies of AI impact in agriculture, healthcare, education, and financial services in Tanzania
2. Longitudinal Tracking: Real-time monitoring of job displacement and creation patterns as AI adoption accelerates
3. Regional Comparative Studies: Systematic comparison of AI transition strategies and outcomes across East Africa
4. Social Protection Design: Evidence-based models for unemployment insurance and reskilling programs appropriate for informal sector contexts
5. Gender and Youth Focus: Targeted research on how AI affects women and young workers differently, with tailored intervention strategies

10.6 Final Reflection

The central finding of this research is clear: AI will increase unemployment and widen income inequality in Tanzania unless deliberate, inclusive, and well-sequenced policy interventions are implemented immediately. The next five years will determine whether Tanzania becomes an AI winner or loser.

The transformation is already underway globally—76,440 jobs eliminated in 2025, unemployment rising among AI-exposed occupations, and evidence of displacement spreading across sectors. Tanzania's structural vulnerabilities—71.8% informal employment, 70% agricultural dependence, severe digital divide, critical skills shortage—make the country particularly susceptible to AI-driven disruption.

Yet Tanzania also possesses unique advantages: a youthful population, late-mover learning opportunities, strong community values, and growing policy awareness. The country can choose to proactively shape an inclusive AI economy or reactively manage the fallout from mass displacement and deepening inequality.

The cost of inaction will be measured not only in lost jobs, but in lost development potential, widening inequality, and a generation left behind. The window for decisive action is now.

References

International Organization Reports

1. World Economic Forum (2025). Future of Jobs Report 2025. Geneva: World Economic Forum. Retrieved from
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Tanzania-Specific Studies

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26. Eva Docs.ai (2025). Case Study: AI-Powered Procurement in Tanzania SMEs. Dar es Salaam: Eva Technologies.

Regional Comparative Studies

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29. Kenya National AI Taskforce (2023). Kenya National Artificial Intelligence Strategy. Nairobi: Ministry of ICT, Innovation and Youth Affairs.
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News and Media Sources

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34. International Labour Organization (2025). ILOSTAT Database. Retrieved from
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Appendix A: Key Terms and Definitions

Artificial Intelligence (AI): Technologies that enable machines to perform tasks that typically require human intelligence, including machine learning, natural language processing, computer vision, and robotics.

Automation Risk/Potential: The percentage of tasks within a job that can be performed by AI systems, leading to either job displacement or significant job restructuring.

Formal Sector: Employment characterized by written contracts, social security benefits, legal protections, and regular wages.

Informal Sector: Economic activities not registered with government authorities, lacking formal contracts, social protection, and legal safeguards.

Gini Coefficient: A measure of income inequality ranging from 0 (perfect equality) to 1 (perfect inequality).

Digital Divide: The gap between those with access to digital technologies and those without, encompassing infrastructure, skills, and economic resources.

Skills Premium: Additional wages earned by workers with specialized skills relative to those with basic skills.

Appendix B: Policy Recommendations Matrix

About the Author

Amran Bhuzohera is a researcher focusing on labor markets, digital transformation, and development economics in East Africa, with particular emphasis on Tanzania's economic transition in the age of artificial intelligence.

Report Compiled: December 2025
Geographic Focus: Tanzania with global and regional context
Time Horizon: 2025-2030
Document Version: 1.0

Recommended Citation:
Bhuzohera, A. (2025). AI's Impact on Unemployment and Income Inequality in Tanzania: A Comprehensive Analysis (2025-2030). Dar es Salaam: Independent Research Report.

Keywords: Artificial Intelligence, Tanzania, Labor Market, Unemployment, Income Inequality, Informal Sector, Agriculture, Digital Transformation, Skills Gap, Development Economics, East Africa, Automation, Job Displacement, Digital Divide, Policy Intervention

Author: Amran Bhuzohera

Artificial Intelligence (AI) is rapidly reshaping the global world of work, redefining how jobs are created, performed, and displaced. Between 2025 and 2030, AI-driven automation and digital transformation are expected to disrupt labour markets at a scale comparable to past industrial revolutions, but at unprecedented speed. According to the World Economic Forum, while AI and related technologies are projected to displace approximately 92 million jobs globally, they are also expected to create 170 million new jobs, resulting in a net global job gain of about 78 million positions, equivalent to roughly 7% of the current global workforce. However, these gains will not be evenly distributed across countries, sectors, or skills levels.

For Tanzania, the implications of this transformation are particularly profound. The country enters the AI era with a labour market that is structurally vulnerable yet full of latent opportunity. As of 2025, about 71.8% of Tanzania’s workforce—approximately 25.95 million people—operates in the informal sector, characterised by low job security, limited social protection, and minimal access to upskilling opportunities. Only 28.2% of workers (10.17 million) are in formal employment, although projections suggest gradual formalisation could raise this figure to around 38% by 2030 if supportive policies are implemented.

Globally, evidence shows that AI-related job displacement is no longer a future risk but a present reality. By 2025 alone, an estimated 76,440 jobs had already been eliminated worldwide due to AI adoption, with occupations such as customer service, data entry, retail cashiers, and clerical work experiencing the earliest impacts. Studies from the St. Louis Federal Reserve further demonstrate a strong positive correlation (0.47) between AI exposure and rising unemployment in highly digitised occupations between 2022 and 2025, particularly in computer and mathematical roles. These trends signal what lies ahead for emerging economies like Tanzania as AI adoption deepens.

Sectoral exposure in Tanzania mirrors global patterns but is intensified by the country’s economic structure. Agriculture employs roughly 28% of the national workforce and engages nearly 70% of Tanzanians indirectly, making it the backbone of livelihoods. While AI-powered precision farming, automated irrigation, drone-based crop monitoring, and pest-prediction systems promise productivity gains and climate resilience, they also reduce demand for manual labour. Without proactive reskilling and value-chain upgrading, technological efficiency gains could translate into rural job losses rather than inclusive growth.

Other vulnerable sectors include manufacturing and SMEs, where manual procurement, inventory management, and quality control are increasingly being automated; customer service and call centres, facing automation risks of up to 80% by 2025 due to chatbots and virtual assistants; and administrative and clerical roles, where bookkeeping, data entry, and document processing are rapidly being replaced by AI systems. Financial services are also transforming through AI-based credit scoring, fraud detection, and risk assessment, reducing demand for entry-level professionals while increasing demand for advanced digital skills.

At the same time, AI is creating new growth pathways. Globally, the fastest-growing roles between 2025 and 2030 include AI specialists, data scientists, software developers, cybersecurity analysts, and AI ethics officers, alongside strong employment growth in the green economy and care sectors. Notably, agriculture, construction, education, and healthcare are expected to generate the largest absolute number of new jobs, driven by population growth, infrastructure expansion, and social service needs. For Tanzania, this presents a strategic opportunity to align its youthful population, agricultural base, and digital transformation agenda with future-ready skills development.

Tanzania has begun laying the foundations for this transition. Key initiatives include the development of a National AI Strategy (expected in late 2025), the establishment of AI research labs through collaborations between the University of Dodoma and NM-AIST, the Digital Tanzania Project, and sector-specific programmes such as AI4D Agriculture, supported by international partners. However, major constraints remain, including limited digital infrastructure, unreliable electricity, a critical shortage of AI professionals, fragmented regulation, and low awareness—evidenced by the fact that 54% of workers are unaware of formalisation or digital upskilling programmes.

Ultimately, the period 2025–2030 will be decisive. AI will not simply determine how many jobs exist in Tanzania, but what kind of jobs, who gets them, and under what conditions. Without timely policy action, the AI transition risks deepening informality, widening rural-urban and gender inequalities, and marginalising low-skilled workers. With deliberate, inclusive, and well-sequenced reforms—focused on digital infrastructure, mass skills development, ethical AI governance, and social protection—Tanzania can instead leverage AI as a catalyst for productivity, formalisation, and sustainable development. The challenge is not whether AI will transform Tanzania’s labour market, but whether the country will shape that transformation proactively or react to it too late.

Artificial Intelligence is poised to fundamentally transform the global job market by 2030, and Tanzania will not be exempt from these changes. While AI will displace millions of jobs worldwide, it will also create new opportunities, resulting in a net positive job growth. However, the transition period will require significant workforce adaptation, particularly in Tanzania where 71.8% of the workforce operates in the informal sector.

Will the Next Five Years Make Tanzania an AI Winner or Loser?

The next five years will be decisive for Tanzania’s position in the age of Artificial Intelligence. AI is no longer a distant or abstract technology—it is already reshaping jobs, skills, and productivity across the global economy. For Tanzania, the stakes are exceptionally high. With over 70 percent of the workforce operating in the informal sector and a large share of livelihoods concentrated in agriculture and low-skilled services, the country faces both significant exposure to AI-driven disruption and a rare opportunity to leapfrog into a more productive, formal, and resilient economic structure.

Whether Tanzania emerges as an AI winner or loser will not be determined by technology alone, but by policy choices, investment priorities, and the speed of institutional response. If AI adoption advances without parallel investments in digital infrastructure, skills development, and worker protection, the result is likely to be deeper informality, rising job insecurity, and widening inequalities between urban and rural areas, formal and informal workers, and skilled and low-skilled populations. In such a scenario, productivity gains would accrue to a narrow segment of firms and workers, while the majority remain excluded from the benefits of technological progress.

Conversely, Tanzania has a credible pathway to becoming an AI winner. Ongoing initiatives—such as the development of a National AI Strategy, expansion of digital infrastructure, investment in AI research and education, and pilot applications in agriculture, healthcare, education, and finance—provide a foundation upon which inclusive AI adoption can be built. If these efforts are accelerated and aligned with large-scale upskilling, formalization incentives for SMEs, ethical AI governance, and targeted support for vulnerable groups such as youth, women, and rural workers, AI can become a driver of productivity, decent work, and sustainable growth.

Crucially, the transition period between 2025 and 2030 will be the most disruptive. Decisions taken now will determine whether Tanzanian workers are displaced by automation or empowered to work alongside AI technologies. This window demands urgency: scaling digital literacy, embedding AI skills across education and vocational training, strengthening social protection systems, and ensuring that AI adoption serves national development goals rather than undermines them.

In the end, Tanzania’s AI future is not preordained. The country can either react to AI-driven change after jobs are lost and inequalities widen, or act decisively to shape a human-centered, inclusive AI economy. The next five years will answer the question clearly. With deliberate, coordinated, and inclusive action, Tanzania can position itself as an AI winner. Without it, the cost of delay will be measured not only in lost jobs, but in lost development potential. Read More of this Topic: Doing Business in Tanzania 2025-2030

Global AI Job Displacement & Creation Statistics (2025-2030)

Overall Impact

Alternative Estimates

Different research institutions provide varying projections:

Job Categories by Risk Level

CRITICAL RISK (70-95% Automation Potential) - 2024-2025 Timeline

HIGH RISK (40-70% Automation Potential) - 2025-2027 Timeline

MODERATE RISK (15-40% Automation Potential) - 2027-2030 Timeline

LOW RISK (5-15% Automation Potential) - Post-2030

Fastest Growing Job Categories (2025-2030)

Technology & AI Roles

Green Economy Roles

Care & Essential Services (Largest Absolute Growth)

Tanzania-Specific Context & Vulnerabilities

Current Employment Structure (2025)

Tanzania Workforce Demographics

Sectors Most Vulnerable in Tanzania

Tanzania AI Readiness & Adoption Status

Current AI Initiatives

Major Barriers in Tanzania

Key Studies & Research Findings

1. World Economic Forum Future of Jobs Report 2025

Key Findings:

• 22% of jobs will be disrupted by 2030
• Technology, green transition, and demographics driving change
• Skills gap cited by 63% of employers as transformation barrier
• 85% of employers prioritizing upskilling programs
• 39% of skills becoming outdated by 2030, down from 57% in 2020

Gender Disparities:

• 58.87 million women in US workforce highly exposed to AI automation vs. 48.62 million men

2. Goldman Sachs Research (August 2025)

Current Impact:

• Unemployment among 20-30 year olds in tech rose by nearly 3 percentage points since start of 2025
• Generative AI contributing to hiring headwinds for recent graduates
• 2.5% of US employment at risk if current AI use cases expanded economy-wide
• 6-7% baseline displacement estimate (range: 3-14%)

3. St. Louis Federal Reserve Study (August 2025)

Evidence of Current Displacement:

• Occupations with higher AI exposure experienced larger unemployment increases between 2022-2025
• 0.47 correlation coefficient between AI exposure and unemployment rise
• Computer and mathematical occupations seeing steepest rises
• Blue-collar jobs with limited AI impact saw smaller increases

4. Tanzania-Specific Research

NGO Study (Kinondoni, January 2025):

• Most NGOs not using AI in selection phase (2025)
• Different assessment types required across industries limiting AI adoption
• Some scholars view AI as threat, others as efficiency enhancer

Employment Analysis (TICGL, April 2025):

• 71.8% informal vs. 28.2% formal employment
• Barriers to formalization: limited jobs (42%), skills mismatches (26%), bureaucracy (21%)
• Agriculture employs 28% of workforce (mostly informal)
• Small businesses constitute 44% of informal economy

5. McKinsey Global Institute

Long-term Projections:

• Up to 800 million jobs could be automated globally by 2030
• 75 million to 375 million workers may need to switch occupational categories
• Advanced economies face higher transition needs (up to one-third of workforce)
• Productivity growth of 0.8-1.4% annually from automation

Impact Timeline: What to Expect and When

Skills That Will Matter Most

Critical Future Skills (WEF 2030)

Cognitive Skills:

1. Analytical thinking & innovation
2. Critical thinking & analysis
3. Complex problem-solving
4. Creativity & originality
5. Reasoning & ideation

Technological Skills:

1. AI and big data literacy
2. Technology design & programming
3. Systems thinking
4. Cloud computing
5. Data analytics

Human Skills (AI-Resistant):

1. Emotional intelligence
2. Leadership & social influence
3. Resilience, flexibility & agility
4. Active learning strategies
5. Collaboration & teamwork
6. Curiosity & lifelong learning

Tanzania-Specific Priorities:

• Digital literacy (foundational)
• English/Swahili technical vocabulary
• Data interpretation
• Agricultural technology
• Mobile technology proficiency

Recommendations for Tanzania: Preparing for AI-Driven Change

The Tanzania Opportunity

Despite challenges, Tanzania has unique advantages:

Strategic Positioning

1. Late-Mover Advantage

• Learn from others' mistakes
• Adopt proven AI governance models
• Skip intermediate technology stages
• Build ethical frameworks early

2. Youth Demographics

• Growing working-age population
• Digital native generation emerging
• Entrepreneurial spirit
• Adaptability to new technologies

3. Agricultural Innovation Potential

• 70% agricultural workforce
• Climate adaptation needs
• Food security imperatives
• Export market opportunities

4. Community-Driven Values

• Strong social cohesion
• Collective problem-solving
• Ethical considerations prioritized
• Inclusive development focus

Regional Competition & Cooperation

Tanzania's Approach: Choosing deliberate, inclusive growth over rapid adoption may prove advantageous long-term.

Critical Warnings

Global Context

1. 77% of new AI jobs require master's degrees - creating substantial skills gaps
2. By 2030, 12-14% of workers may need to transition to new occupations
3. Young tech workers disproportionately affected currently
4. Gender disparities exist in AI displacement risk

Tanzania-Specific Risks

1. Informal Sector Vulnerability: 71.8% of workforce lacks protections
2. Agricultural Dependence: 70% in sector facing automation
3. Skills Gap: Critical shortage of AI professionals
4. Infrastructure: Unreliable electricity, limited internet
5. Awareness Gap: 54% unaware of formalization programs
6. Education Baseline: Lower education levels limiting transition options
7. Capital Requirements: High costs for AI infrastructure adoption

Conclusion: A Balanced Perspective

The Reality:

• AI WILL displace jobs in Tanzania, following global patterns
• Timeline: 2025-2030 for significant impact
• Scale: Potentially millions of positions affected globally, hundreds of thousands in Tanzania
• Net effect: Global job creation (+78 million) but uneven distribution

The Opportunity:

• 170 million new jobs created globally by 2030
• New sectors emerging (AI specialists, green economy, care roles)
• Productivity gains enabling economic growth
• Chance to leapfrog development stages

The Challenge:

• Transition period will be painful for many
• Skills gap is critical barrier
• Infrastructure investments essential
• Social safety nets needed
• Immediate action required

Tanzania's Path Forward: The next five years will determine whether Tanzania becomes an AI winner or loser. Success requires:

1. Urgent implementation of National AI Strategy
2. Massive investment in digital skills training
3. Infrastructure development (electricity, internet)
4. Protection for vulnerable workers
5. Ethical, inclusive AI adoption
6. Public-private-academic collaboration
7. Regional cooperation and knowledge sharing

The choice is clear: Adapt proactively or face displacement reactively. The AI revolution is not coming—it's already here.

Sources & References

1. World Economic Forum - Future of Jobs Report 2025
2. Goldman Sachs Research - AI Workforce Impact (August 2025)
3. SSRN - AI Job Displacement Analysis 2025-2030 (Nartey, 2025)
4. St. Louis Federal Reserve - AI and Unemployment Study (August 2025)
5. TICGL - Tanzania Employment Analysis (April 2025)
6. International Journal of Research - Tanzania NGO AI Study (January 2025)
7. McKinsey Global Institute - Jobs Lost, Jobs Gained Reports
8. UNESCO - Tanzania AI Readiness Assessment (2025)
9. Right for Education - AI Impact on African Labor Markets (March 2025)
10. Digital Regenesys - AI in Tanzania Strategy Report (November 2025)

Report Compiled: December 2025 Data Sources: Academic research, government reports, international organizations, and industry studies Geographic Focus: Tanzania with global context Time Horizon: 2025-2030

Tanzania is facing a deepening affordability challenge as the gap between household incomes and the cost of living continues to widen. In 2025, the average monthly salary stands at TSh 637,226, yet a single person requires approximately TSh 1.25 million per month to meet basic living expenses—equivalent to 196% of the average salary. This leaves an income shortfall of nearly TSh 612,000, meaning the typical worker earns only 51% of what is needed to live modestly. The situation is far more severe for families: a household of four needs about TSh 4.75 million per month for a moderate lifestyle and closer to TSh 5.5 million to remain financially stable—an amount equal to the combined earnings of 8–9 average workers. Looking ahead to 2026, projections suggest the crisis will intensify. Under the baseline scenario, salaries rise marginally to TSh 650,000 (+2%), while living costs for a single person increase to TSh 1.36 million, widening the deficit to -109% of salary. In an adverse scenario, workers may earn only 43% of their basic needs, with family living costs exceeding TSh 6.6 million per month. These figures highlight a structural imbalance where economic growth and wage adjustments are failing to keep pace with rising living costs—signaling an urgent need for policy action on wages, housing affordability, and food security. More On This Topic: Is the Cost of Living in Tanzania Outpacing Incomes as We Enter 2026?

Current Reality (2025)

Single Person Budget Gap

Key Insight: A single person needs to earn nearly double the average salary just to cover basic expenses.

Family of Four Budget Gap

Key Insight: A family needs the combined income of 8-9 average workers to live moderately—typically requiring 2 high-earning adults plus additional income sources.

2026 Projections: The Gap Widens

Scenario Comparison

What This Means

2026 Baseline Scenario (60% probability):

• Workers will earn even LESS relative to their needs
• The gap increases from -96% to -109%
• Families will need 6M TSh/month instead of 5.5M

2026 Adverse Scenario (40% probability):

• Crisis deepens significantly
• Workers earn only 43% of what they need
• The shortfall reaches -134% of salary
• Families face costs exceeding 6.6M TSh/month

Critical Takeaway

The average Tanzanian worker currently earns only 51% of what's needed for basic living. By 2026, this could drop to 48% (baseline) or 43% (adverse scenario).

This isn't just an income problem—it's a structural crisis requiring urgent policy action on wages, housing affordability, and food security.

Conclusion

Tanzania's deepening cost-of-living crisis reveals a profound structural disconnect between wages and essential expenses. In 2025, the average monthly salary of TSh 637,226 covers only 51% of a single person's basic needs (TSh 1.25 million) and forces families of four to rely on the equivalent of 8–9 average incomes to achieve modest financial stability (TSh 5.5 million). Projections for 2026 indicate further deterioration: under the baseline scenario, salary coverage falls to 48% for individuals, with family costs rising toward TSh 6 million; in the adverse scenario, workers may earn just 43% of their needs, pushing family expenses beyond TSh 6.6 million.

These trends signal that economic growth and wage adjustments are failing to keep pace with inflation in housing, food, and other essentials. Without urgent, targeted policy interventions—raising living wages, improving housing affordability, strengthening food security, and promoting inclusive growth—the affordability gap will widen further, eroding living standards and deepening inequality for millions of Tanzanians. Addressing this crisis is not only an economic imperative but a moral one, essential for building a more equitable and sustainable future.

The cost of living has become one of the most pressing economic realities shaping everyday life in Tanzania. While the country continues to post relatively strong macroeconomic indicators—such as GDP growth of 5.6% in 2025—these headline figures mask a growing disconnect between household incomes and the actual cost of meeting basic needs. For millions of Tanzanians, especially salaried workers, small entrepreneurs, and urban households, affordability is no longer just a concern—it is a structural challenge.

According to the 2025 Cost of Living Analysis, Tanzania remains 61.2% cheaper overall than the United States, with rent costs approximately 78.3% lower. However, this international comparison obscures a more critical domestic reality: local wages have not kept pace with the rising cost of housing, food, utilities, and essential services.

In 2025, the average monthly salary is estimated at 637,226 Tanzanian Shillings (TSh). Against this income, the estimated monthly cost of living for a single person—excluding rent—stands at 1,152,096 TSh, while a family of four requires approximately 4.1 million TSh per month to meet basic needs.

This means that even before accounting for rent, the average worker earns less than half of what is required to sustain a modest standard of living.

Where the Pressure Is Coming From

Food and dining account for the largest share of household expenditure, consuming 40–45% of monthly income. A simple inexpensive meal costs around 7,000 TSh, equivalent to 33% of an average daily wage, while a mid-range meal for two can exceed 50,000 TSh, or more than two full days of income for many workers.

Even staple grocery items—though relatively affordable individually—accumulate into a significant monthly burden, especially for families.

Housing costs present an even deeper structural challenge. Renting a one-bedroom apartment in a city centre costs approximately 1.19 million TSh per month, representing 187% of the average monthly salary. Even outside city centres, rent for a modest one-bedroom unit consumes over 70% of average income, while three-bedroom family housing exceeds total earnings entirely.

Utilities and internet add a further 300,000 TSh per month, reinforcing the affordability gap.

Transportation remains relatively affordable—public transport costs around 39,000 TSh per month, or about 6% of salary—but private vehicle ownership is increasingly out of reach, with the cost of a new compact car equivalent to nearly 70 months of income.

The Bigger Picture: Living Costs vs. Earnings

When all expenses are combined, a budget-conscious single person requires approximately 1.25 million TSh per month, nearly double the average salary. For a family of four, sustainable living requires a household income of 4.8–5.5 million TSh per month, typically achievable only with two high-earning adults or external income sources.

This growing income–cost gap explains rising household debt, reduced savings, informal coping strategies, and increasing vulnerability among urban populations. It also places pressure on businesses, as workers demand higher wages while firms face higher operating costs.

Looking Ahead to 2026: What to Expect

The outlook for 2026 presents both risk and uncertainty. Under the baseline scenario—where political and economic conditions stabilize—overall inflation is projected to rise to 4.3%, with food inflation averaging 7.1% and peaking as high as 8.5% mid-year. The Tanzanian Shilling is expected to depreciate by about 4%, pushing up the cost of imported goods, fuel, and agricultural inputs.

In this scenario, average monthly salaries are projected to rise marginally to around 650,000 TSh, while the monthly cost of living for a single person climbs to 1.36 million TSh—deepening the affordability gap rather than closing it. Families would require close to 6 million TSh per month to maintain a moderate standard of living.

Under an adverse scenario, characterized by prolonged political or economic disruptions, inflation could rise to 6.5–7.0%, food prices could increase by 10–12%, and the currency could depreciate by up to 14%. This would push the monthly cost of living for a single person to 1.5 million TSh, while families could face costs exceeding 5.7 million TSh, further increasing poverty and inequality.

Why This Matters

The data sends a clear message: Tanzania’s cost-of-living challenge is no longer about prices alone—it is about income adequacy, economic structure, and policy choices. Without deliberate action on wages, housing supply, food systems, and productivity, economic growth risks becoming disconnected from lived reality. As the country looks toward 2026 and beyond, addressing the cost of living is not just an economic necessity—it is a social and political imperative.

Tanzania offers a significantly lower cost of living compared to the United States, making it an affordable destination for both residents and expatriates. The data shows Tanzania is 61.2% cheaper overall than the US, with rent being 78.3% lower. More on This Topic: Will Tanzania's Robust Central Bank Position Ensure Continued Growth Through 2026?

Monthly Budget Overview

*Based on approximate exchange rate of 2,500 TSh = 1 USD

Detailed Cost Breakdown by Category

1. Food & Dining (40-45% of monthly expenses)

Restaurant Dining

**Based on average daily wage of ~21,241 TSh (637,226/30 days)

Market/Grocery Costs

Weekly grocery budget for single person: ~60,000-80,000 TSh (26-35% of monthly food costs)

2. Housing & Utilities (35-40% of monthly expenses)

Rental Costs

Key Insight: Living outside the city centre saves approximately 62% on rent for 1-bedroom apartments and 60% for 3-bedroom apartments.

Monthly Utilities (85m² Apartment)

3. Transportation (10-15% of monthly expenses)

Budget Recommendation: Public transport is highly affordable at 39,000 TSh/month. For car owners, factor in ~50,000-80,000 TSh monthly for fuel (based on average commuting).

4. Lifestyle & Recreation (5-10% of monthly expenses)

5. Childcare & Education (Variable, can be 30-50% for families)

Critical Note: International schooling is extremely expensive relative to local salaries, typically requiring expatriate-level income or significant family savings.

Monthly Budget Examples

Single Person (Budget-Conscious)

Budget vs Average Salary: 196% (requires income above average)

Family of Four (Moderate Lifestyle)

Household Income Needed: ~4,800,000-5,500,000 TSh/month (2 working adults)

Projected Economic Impact on Cost of Living (2026)

Baseline Scenario (60% Probability): Gradual Stabilization

Assumption: Unrest subsides by Q1 2026, limited international sanctions

Adverse Scenario (40% Probability): Prolonged Crisis

Assumption: Unrest continues into mid-2026, broader sanctions imposed

Income vs. Cost Gap Analysis (2026)

Current Reality Check

Critical Finding: The average salary falls significantly below estimated costs, with shortfalls ranging from 546,679 TSh for single persons to over 3.6 million TSh for families with one earner.

Author: Amran Bhuzohera

Tanzania's budget totals TZS 56.49 trillion (approximately USD 22.07 billion), representing an 11.6% increase from the previous year. The budget aims to achieve 6% GDP growth in 2025, maintain inflation between 3-5%, and increase domestic revenue collection to 16.7% of GDP.

INTRODUCTION

Tanzania’s National Budget, amounting to TZS 56.49 trillion (an 11.6% increase from the previous year), is not merely a fiscal plan but a direct intervention in the daily economic realities of households and businesses. Anchored on a 6.0% GDP growth target, inflation control within 3–5%, and increased domestic revenue mobilisation to 16.7% of GDP, the budget seeks to balance cost-of-living pressures, income growth, and business competitiveness in a tightening global economic environment.

For households, the budget’s meaning is reflected in how it influences prices, access to basic services, disposable income, and employment opportunities. With headline inflation at 3.5% (October 2025)—within the government’s target—macroeconomic stability has largely been preserved. However, this stability is unevenly felt. Food inflation stands at 7.4%, significantly above overall inflation, directly affecting low- and middle-income families who allocate a larger share of income to food. To cushion these pressures, the budget allocates TZS 708.6 billion for fertilizer subsidies, TZS 444.7 billion for education, and TZS 414.7 billion for healthcare, lowering essential household expenditures and supporting rural livelihoods. At the same time, new levies—such as the TZS 10 per litre fuel levy and increased excise duties on selected products—introduce modest upward pressure on transport and energy costs, particularly for urban middle-income households.

For businesses, the budget signals both opportunity and adjustment. Strong revenue performance (106.1% of target by September 2025) and high development expenditure execution (98.5%) indicate an active government spending environment that benefits contractors, suppliers, and service providers. Access to finance has improved, with private sector credit growing by 16.1% year-on-year, supported by stable interest rates and increased liquidity. Sectorally, the budget prioritizes manufacturing (18.12% of total allocation), energy, transport infrastructure, and agriculture, where credit growth reached 25.6%, reinforcing agribusiness expansion. Export-oriented activities are further supported by strong external sector performance, with exports growing by 19.8% and the current account deficit narrowing by 23.3%, contributing to a 9.5% appreciation of the Tanzanian shilling, which lowers import costs for firms reliant on imported inputs.

However, the budget also raises the cost of compliance and taxation for some businesses. The increase in the Alternative Minimum Tax to 1%, the introduction of a 10% withholding tax on retained earnings, and new excise duties on selected manufactured and imported goods may constrain reinvestment and margins, especially for small and medium-sized enterprises. Notably, despite the large budget allocation to manufacturing, credit growth to the sector remains low at 5.2%, suggesting a gap between fiscal ambition and on-the-ground financing outcomes.

Overall, the 2025/26 Budget means that households benefit from macroeconomic stability and sustained social spending, though rising food prices remain a key concern, while businesses operate in a generally supportive growth environment characterized by improved infrastructure, expanding credit, and stable demand—but with heightened tax and compliance expectations. In essence, the budget redistributes resources toward long-term growth and stability, while requiring households and firms to navigate short-term cost adjustments as the economy transitions toward higher productivity and domestic revenue reliance. Read More: Tanzania Economic Updates December 2025

WHAT THE BUDGET MEANS NOW: EARLY ECONOMIC EFFECTS ON HOUSEHOLDS AND BUSINESSES

1. Implications for Households

The early implementation of the 2025/26 Budget shows that macroeconomic stability is translating into tangible benefits for households, although these gains are being partially offset by rising food and energy costs.

Positive Impacts Currently Being Felt

First, inflation remains within the government’s target range, with headline inflation recorded at 3.5% in October 2025. This has helped preserve household purchasing power, particularly for non-food items such as clothing, utilities, and basic services, where price increases remain subdued.

Second, the appreciation of the Tanzania shilling by 9.5% year-on-year, from TZS 2,693 per USD in October 2024 to TZS 2,452 per USD in October 2025, has reduced the cost of imported goods. This benefits households through lower prices for imported food items, fuel-related inputs, medicines, and consumer goods, while also helping to contain inflationary pressures.

Third, strong government revenue performance—106.1% of the target by September 2025— has enabled continued funding of essential public services. This supports sustained delivery of education, healthcare, water, and social services, reducing out-of-pocket expenditure for households and improving access to basic needs.

Fourth, employment and income opportunities are expanding, supported by private sector credit growth of 16.1%. Increased lending to sectors such as agriculture, trade, tourism, and mining is translating into higher economic activity, job creation, and more stable household incomes, particularly for informal and SME-linked households.

Finally, borrowing costs for households have declined modestly, with the average lending rate falling from 15.67% to 15.19%. While still relatively high, this reduction improves affordability of personal loans, mortgages, and SME-related household enterprises, supporting consumption and small-scale investment.

Challenges Being Experienced

Despite these gains, food inflation remains the most significant pressure on household welfare. Food inflation stood at 7.4% in October 2025, more than double the headline rate, disproportionately affecting low- and middle-income families who spend a larger share of their income on food.

In addition, energy and utilities inflation increased to 4.0%, reflecting higher fuel-related costs. The introduction of a TZS 10 per litre fuel levy and other transport-related charges has added upward pressure on commuting and logistics costs, indirectly feeding into household expenses.

Urban middle-income households are experiencing mixed outcomes. While they benefit from stable inflation and exchange rate gains, higher transport costs, vehicle-related levies, and selective excise duties are eroding disposable income, particularly for salaried workers.

Overall Assessment for Households:
Grade: B+ – The budget is delivering on macroeconomic stability and service provision, but rising food prices remain a critical challenge that weakens household welfare gains.

2. Implications for Businesses

For businesses, the budget is creating a generally supportive operating environment, anchored in strong public spending execution, expanding credit, and improved external sector performance. However, tax and compliance pressures are weighing on investment decisions, particularly in manufacturing.

Positive Impacts Currently Being Felt

Credit availability has improved significantly, with private sector credit expanding by 16.1% year-on-year. This indicates stronger bank lending appetite and improved liquidity, supporting business expansion, working capital financing, and investment across multiple sectors.

Sectoral performance data shows that mining (29.7%), agriculture (25.6%), and tourism-related activities (23.2%) are responding strongly to the budget and broader economic conditions. These sectors are benefiting from targeted incentives, export demand, infrastructure development, and improved access to finance.

Cash flow conditions for compliant businesses have improved due to VAT refunds being processed within 30 days, reducing liquidity constraints—especially for exporters and capital-intensive firms.

Public investment is translating into real economic activity, with development expenditure execution reaching 98.5% by September 2025. Ongoing infrastructure projects in transport, energy, and logistics are lowering operational costs, improving market access, and generating business opportunities in construction, supply chains, and services.

Externally, export growth of 19.8%, led by gold and traditional exports, has expanded market opportunities for producers and exporters, while improved foreign exchange availability supports import-dependent businesses.

Challenges Being Experienced

Despite these positives, the manufacturing sector is underperforming relative to budget priorities. While it received 18.12% of the total budget allocation, credit growth to manufacturing remains low at 5.2%, indicating weak transmission of fiscal support into private investment.

Tax policy changes are also affecting business sentiment. The increase in the Alternative Minimum Tax to 1% raises the tax burden for low-margin and loss-making firms, while the 10% withholding tax on retained earnings reduces internally generated funds available for reinvestment and expansion.

Additionally, new compliance and administrative requirements, including enhanced electronic invoicing and reporting obligations, are increasing operating and compliance costs—particularly for SMEs and informal-sector businesses transitioning into the formal economy.

Overall Assessment for Businesses:
Grade: B – The business environment remains broadly positive, supported by credit growth, infrastructure spending, and export performance, but manufacturing sector response and tax-related investment constraints require urgent policy attention.

KEY ECONOMIC INDICATORS

IMPACT ON HOUSEHOLDS

A. DIRECT HOUSEHOLD BENEFITS

B. TAX CHANGES AFFECTING HOUSEHOLDS

POSITIVE CHANGES (Reduced Costs)

NEGATIVE CHANGES (Increased Costs)

C. COST OF LIVING IMPACT

New excise duties on alcohol, the TZS 10 per liter fuel levy, and vehicle import levies may increase household expenses, particularly for middle-income families. However, sustained subsidies, education support, and healthcare allocations directly benefit low-income households.

IMPACT ON BUSINESSES

A. SECTORAL ALLOCATIONS

B. BUSINESS TAX CHANGES

FAVORABLE CHANGES

CHALLENGING CHANGES

C. COMPLIANCE AND ADMINISTRATIVE CHANGES

SECTORAL BUSINESS OUTLOOK

AGRICULTURE (26% of GDP, employs ~65% of Tanzanians)

Outlook: The sector contributed 26.5% to GDP and benefits from continued subsidies to boost yields. Highly positive for agribusinesses.

MANUFACTURING (18.12% of budget allocation)

Outlook: The government emphasized manufacturing as key to boosting GDP and employment, receiving 18.12% of the national budget. Very positive for manufacturers.

MINING

Outlook: Mixed - benefits from VAT relief but faces mandatory local processing requirements.

SERVICES (ICT, Finance, Tourism)

Outlook: Services sector shows strong growth, particularly ICT and finance.

INFRASTRUCTURE DEVELOPMENT IMPACT

FINANCING STRUCTURE

EXPENDITURE BREAKDOWN

WHERE ARE WE NOW?

1. INFLATION AND COST OF LIVING IMPACT

Current Inflation Performance

What This Means:

For Households:

• Overall inflation is within the government's target, which is positive for purchasing power
• However, food inflation at 7.4% (up from 2.5% in October 2024) is significantly impacting household budgets, especially for low-income families who spend more on food
• Energy costs increased to 4.0% from 3.7%, adding pressure on household expenses

For Businesses:

• Core inflation at 2.1% provides a stable environment for business planning
• Lower non-food inflation (1.0%) reduces operational costs for non-food sectors
• Food price increases may affect food processing and retail businesses

Month-on-Month Price Changes (October 2025)

2. REVENUE COLLECTION PERFORMANCE

Government Revenue Achievement (September 2025)

What This Means:

For Households:

• Strong tax collection (111.4% of target) suggests the economy is performing well, which could lead to better public services
• Higher income tax collection indicates more people are earning taxable income
• The government has resources to maintain subsidies and social services

For Businesses:

• Robust tax collection from imports and local goods shows strong business activity
• Higher than expected tax collection may indicate increased compliance enforcement
• Businesses should prepare for continued focus on tax compliance

3. GOVERNMENT SPENDING ANALYSIS

Expenditure Performance (September 2025)

What This Means:

For Households:

• Government salaries paid on time (99.5% execution) ensures stable household income for public servants
• Lower interest payments (82.4%) means more funds available for social services
• Strong execution of locally-financed development (106.6%) suggests infrastructure projects are progressing

For Businesses:

• Development expenditure at 98.5% means construction and infrastructure projects are proceeding
• Lower foreign-financed projects (72.6%) may slow some large infrastructure developments
• Government spending on goods/services exceeded targets (104.6%), benefiting suppliers

4. MONETARY POLICY AND CREDIT AVAILABILITY

Money Supply and Credit Growth (October 2025)

What This Means:

For Households:

• Strong money supply growth (21.5%) indicates economic expansion
• More credit available for mortgages and personal loans
• Higher foreign currency deposits show confidence in the financial system

For Businesses:

• Credit to private sector grew 16.1%, indicating banks are lending
• Adequate liquidity supports business expansion
• Access to financing improved compared to previous year

Credit Distribution by Sector (October 2025)

Implications:

• Mining sector leading in credit growth supports budget focus on minerals
• Agriculture credit growth (25.6%) aligns with budget subsidies
• Personal loans remain dominant (36.4%), funding SMEs
• Manufacturing growth slower (5.2%) despite budget emphasis

5. INTEREST RATES ENVIRONMENT

Interest Rate Performance (October 2025)

What This Means:

For Households:

• Lower lending rates (15.19% vs 15.67%) make loans more affordable
• Deposit rates remain positive in real terms (8.36% vs 3.5% inflation)
• Mortgage and personal loan costs have decreased

For Businesses:

• Borrowing costs reduced, supporting business expansion
• Treasury bill rates dropped significantly (6.27% from 11.55%), reducing government borrowing costs
• Wider interest spread (6.28%) means banks still profitable, ensuring credit availability

6. EXTERNAL SECTOR PERFORMANCE

Balance of Payments (Year ending October 2025)

What This Means:

For Households:

• Improved current account means stronger shilling, lower import costs
• Foreign reserves at 4.7 months exceed EAC benchmark (4.0 months)
• Exchange rate stability benefits households buying imported goods

For Businesses:

• Gold exports surged 38.9%, supporting mining sector
• Traditional exports (cashew, tobacco) up 25.2%, benefiting farmers
• Tourism receipts increased, supporting hospitality businesses
• Stable forex reserves ensure import financing

Exchange Rate Performance (October 2025)

Impact:

• Shilling appreciated 9.5% year-on-year
• Imported goods cheaper for households
• Export competitiveness slightly reduced
• Lower inflation from imported inputs

7. FOOD SECURITY STATUS

National Food Reserve (October 2025)

What This Means:

For Households:

• High food reserves (593,485 tonnes) suggest food security
• Despite high food inflation (7.4%), adequate stocks available
• Government has buffer to stabilize prices if needed

For Businesses:

• Food processors have reliable supply
• Agriculture sector benefiting from purchases
• Limited releases suggest market prices acceptable

Wholesale Food Price Changes (Year-on-Year, October 2025)

8. DEBT SUSTAINABILITY ANALYSIS

National Debt Position (October 2025)

Debt Service Burden (October 2025)

What This Means:

For Households:

• Stable debt levels suggest fiscal sustainability
• Resources available for social services not consumed by debt servicing
• Domestic debt increase (1.8%) manageable

For Businesses:

• Government borrowing not crowding out private sector credit
• Stable debt indicates government can honor contracts
• Lower external debt reduces forex risk

9. SECTORAL CREDIT PERFORMANCE VS BUDGET PRIORITIES

Alignment of Credit Growth with Budget Focus

Analysis:

• Gap in Manufacturing: Despite 18.12% budget allocation, credit growth only 5.2%
• Agriculture Success: Budget support translating to credit access
• Mining Boom: Leading sector in credit growth (29.7%)
• Tourism Recovery: Strong credit growth (23.2%) supports sector development

10. OVERALL BUDGET DEFICIT AND FINANCING

Fiscal Balance (July-September 2025)

Deficit Financing Sources

What This Means:

For Households:

• Deficit at 2.2% of quarterly revenue is manageable
• Strong revenue collection reduces need for excessive borrowing
• Balanced financing (foreign 46%, domestic 54%) maintains stability

For Businesses:

• Government not over-relying on domestic borrowing
• Credit remains available for private sector
• Fiscal discipline supports macroeconomic stability

SUMMARY ASSESSMENT: WHERE WE ARE VS BUDGET TARGETS

AREAS OF STRONG PERFORMANCE

AREAS REQUIRING ATTENTION

Conclusion: Budget Outlook into 2026 Amid Economic Promise and Post-Election Political Challenges

Tanzania's 2025/26 budget of TZS 56.49 trillion lays a robust foundation for sustained economic progress, targeting 6.0% GDP growth, inflation within 3-5%, and domestic revenue at 16.7% of GDP. For households, this translates into continued macroeconomic stability, with benefits from substantial allocations to education (TZS 444.7 billion), healthcare (TZS 414.7 billion), fertilizer subsidies (TZS 708.6 billion), and rural electrification/energy projects (TZS 2.2 trillion). These measures should ease cost-of-living pressures, particularly for low-income and rural families, by reducing out-of-pocket expenses on essentials and supporting agricultural livelihoods. Tax reliefs—such as reduced motorcycle fees, zero-rated VAT on fertilizers and textiles, and lower online purchase VAT—further bolster disposable incomes. However, persistent food inflation (7.4% as of October 2025) and new levies (e.g., TZS 10 per litre fuel levy) remain challenges, disproportionately affecting middle-income urban households reliant on transport and energy.

For businesses, the budget signals strong government commitment through high development expenditure execution (98.5%), private sector credit growth (16.1%), and sectoral priorities in manufacturing (18.12% allocation), agriculture, energy, and infrastructure. Opportunities abound in export-led growth (19.8%), shilling appreciation (9.5%), and incentives like faster VAT refunds and exemptions for local producers. Yet gaps persist, notably low credit growth to manufacturing (5.2%) despite its prominence, alongside higher tax burdens (e.g., 1% Alternative Minimum Tax, 10% withholding on retained earnings) that could constrain reinvestment, especially for SMEs.

Looking ahead to 2026, successful implementation could deliver tangible gains: accelerated job creation and income growth for households, improved infrastructure reducing operational costs for businesses, and a narrower fiscal deficit supporting overall stability. Early indicators—strong revenue collection (106.1%), export performance, and liquidity—position the economy well to achieve these targets, fostering higher productivity and shared prosperity.

However, this positive outlook is now overshadowed by the political situation arising from the October 2025 elections. President Samia Suluhu Hassan's declared landslide victory (over 97% of the vote) has faced widespread disputes, including the exclusion of main opposition candidates, allegations of irregularities such as ballot stuffing, internet blackouts, and a severe post-election crackdown. This has sparked widespread protests, with reports of hundreds killed, mass arrests, internet restrictions, and international criticism from organizations including the UN, AU, and SADC. Persistent tensions, heightened security, bans on protests, and opposition demands for a transitional government create considerable uncertainty as of December 2025. This political instability threatens to deter foreign investment, disrupt tourism and trade, undermine business confidence, and divert public resources—potentially jeopardizing inflation management, credit availability, and infrastructure advancements vital for households and businesses in 2026.

In summary, although the budget offers a progressive structure for inclusive growth, achieving its benefits in 2026 hinges on quickly resolving the ongoing political crisis to rebuild stability and confidence. Absent such resolution, short-term economic interruptions may eclipse the intended long-term advantages for Tanzanian households and businesses.

As the global economy moves toward 2030, it is increasingly shaped by the interaction between geoeconomic forces and the pace of technological transformation. The World Economic Forum’s December 2025 white paper, Four Futures for the New Economy, presents a structured framework that explores how differing levels of geopolitical stability and technology adoption could redefine global growth, trade, labor markets, and institutional trust over the next decade. Central to this analysis are disruptive technologies such as artificial intelligence, automation, and digital platforms, whose diffusion patterns will determine whether economies converge toward shared prosperity or fragment into rival spheres.

Globally, the paper identifies four plausible scenarios—Digitalized Order, Cautious Stability, Tech-based Survival, and Geotech Spheres—each reflecting a distinct combination of stable versus volatile geoeconomics and fast versus slow technology adoption. These scenarios project diverging trajectories for key indicators, including GDP growth, supply chain resilience, wage polarization, energy volatility, and public trust. With global GDP growth anchored around a modest 3.2% baseline in 2025, the report warns that without inclusive and well-governed technological integration, productivity gains may be offset by rising inequality and geopolitical risk.

For Tanzania, these global futures carry particularly significant implications. Entering 2025 with relatively strong macroeconomic fundamentals—GDP growth of about 6.0%, rising foreign direct investment, improving energy access, and comparatively high trust in public institutions—Tanzania stands at a strategic crossroads. The country’s economic structure, with agriculture contributing roughly 30% of GDP and a growing digital and services sector, makes it both resilient and vulnerable to global fragmentation. Rapid technology adoption could accelerate productivity in agriculture, mining, tourism, and public services, potentially lifting growth above 7%. Conversely, slow or uneven diffusion amid geopolitical shocks could expose Tanzania to trade disruptions, skills mismatches, and widening urban–rural divides.

By integrating the WEF’s global scenarios with Tanzania-specific data and development realities, this analysis provides a forward-looking lens for policymakers, investors, and businesses. It highlights not only how global transformations may shape Tanzania’s economic trajectory by 2030, but also how strategic choices made today—on technology governance, human capital, regional integration, and institutional resilience—will determine whether Tanzania emerges as a beneficiary or a casualty of the new global economic order. Read More: Risks to global growth with potentially disrupt the recovery or slow down economic expansion in '24

Scenario Matrix (Global and Tanzania Shared)

• Y-axis (Geoeconomic Context): Top: Stable; Bottom: Volatile.
• X-axis (Technology Adoption): Left: Slow/Concentrated; Right: Fast/Widespread.
• Quadrants: 1. Digitalized Order; 2. Cautious Stability; 3. Tech-based Survival; 4. Geotech Spheres.

Economic Indicators Trajectories by 2030: Global

Directional changes relative to 2025 baselines (↑ increase, ↓ decrease, → stable).

Sources: WEF paper (e.g., IMF for GDP, ILO for wages).

Economic Indicators Trajectories by 2030: Tanzania

Directional changes relative to 2025 baselines, adapted to local context (e.g., digital share proxies tech tasks, energy access adapts volatility, trust in institutions adapts media trust). Projections informed by IMF, World Bank, AfDB, and Tanzania-specific outlooks.

Sources: IMF (GDP, unemployment), World Bank/AfDB (FDI, energy access), GSMA/UNCTAD estimates (digital share), Afrobarometer (trust), local reports (wage gaps, geopolitical risk subjective).

In-Depth Scenario Descriptions: Global vs. Tanzania

The WEF's global descriptions are adapted below with Tanzania-specific insights, focusing on how local factors (e.g., 30% GDP from agriculture, Belt and Road investments, National AI Strategy) interact with worldwide trends.

1. Digitalized Order (Stable + Fast Tech)Global: Geopolitical calm restores growth (>4% GDP) but fuels inequality and misuse risks. Trade stabilizes, labor disrupts, energy decarbonizes. Tanzania: Aligns with stable EAC ties; AI boosts agriculture/tourism, GDP >7%, but urban-rural gaps widen. FDI surges in tech hubs; reskilling key for youth.
2. Cautious Stability (Stable + Slow Tech)Global: Normalization lowers risks but stagnates growth (2-3% GDP); tech limited to leaders. Trade positive but slow, energy stable. Tanzania: Post-election stability; tech confined to Dar es Salaam, GDP 5-6%, manufacturing revives. Digital share grows modestly; urban-rural divides persist.
3. Tech-based Survival (Volatile + Fast Tech)Global: Tech offsets fragmentation; brittle growth, high inflation. Trade barriers rise, automation spikes. Tanzania: EAC/US strains; AI aids mining/supply chains, GDP 4-6% brittle. Bloc ties (e.g., China) boost FDI; skills mismatches hit youth unemployment.
4. Geotech Spheres (Volatile + Slow Tech)Global: Rivalry fractures networks; stagnation, recession risks. Trade drops, labor tightens. Tanzania: Trade wars isolate; tech disillusionment, GDP <4%. Reshoring creates jobs but talent shortages; strategic sectors (gas) grow via subsidies.

Business and Policy Implications: Global vs. Tanzania

Extending WEF's implications with Tanzania adaptations (e.g., for TICGL, SMEs).

No-Regret Strategies: Global and Tanzania

WEF's global strategies, tailored for Tanzania:

• Strengthen Core Operations: Focus on agriculture efficiency.
• Develop Geopolitical Intelligence: Track EAC/China/US dynamics.
• Enhance Foresight/Data-Driven Decisions: Use AI for planning.
• Build Supply Chain Resilience: Diversify via AfCFTA.
• Invest in Emerging Tech: Scale AI with governance.
• Strengthen Infrastructure: Secure ports/energy cyber/physical.
• Agile Capital Allocation: Flexible for volatility.
• Align Tech and Human Capital: Upskilling for AI workforce.
• Deepen Partnerships: Multilateral alliances to buffer risks.

This integration underscores Tanzania's potential to outpace global growth in optimistic scenarios while emphasizing resilience against volatility for inclusive development.

The four futures outlined by the World Economic Forum do not represent fixed destinies, but rather plausible pathways shaped by policy decisions, institutional capacity, and strategic coordination between the public and private sectors. For Tanzania, the analysis underscores a critical insight: while global forces will influence outcomes, domestic choices will ultimately determine how these forces translate into growth, inclusion, and resilience.

In optimistic scenarios such as Digitalized Order, Tanzania has the potential to outperform global averages by leveraging technology to modernize agriculture, expand digital services, and attract technology-driven investment. However, even in such favorable conditions, risks related to inequality, skills displacement, and governance failures remain significant. In more adverse futures—particularly Tech-based Survival and Geotech Spheres—the costs of geopolitical fragmentation, constrained technology diffusion, and declining trust could sharply limit growth and development gains.

The most important lesson across all scenarios is the value of “no-regret” strategies. Investing in human capital, strengthening digital and physical infrastructure, deepening regional integration through the EAC and AfCFTA, and building adaptive institutions can help Tanzania remain resilient regardless of which global future unfolds. By aligning technology adoption with inclusive development and geopolitical pragmatism, Tanzania can position itself not merely to withstand uncertainty, but to shape its own path within an increasingly complex global economy.

As of November 2025, the Bank of Tanzania (BoT) recorded total assets of TZS 29.67 trillion (approximately USD 12 billion), liabilities of TZS 26.85 trillion, and equity of TZS 2.83 trillion, featuring a remarkable increase in gold holdings (over TZS 4.67 trillion combined) and cash equivalents (TZS 4.45 trillion) driven by record gold sales and tourism revenue—this directly reflects Tanzania's strong economic performance in 2025, with GDP growth of 6.0–6.3%, inflation below 3.4%, and foreign exchange reserves of USD 6–7 billion (4.7 months of import cover). The BoT plays a critical role in managing the economy through monetary policies, such as purchasing domestic gold, controlling currency in circulation (TZS 9.7 trillion), and extending loans to the private sector to stimulate investment and sustainable development.

If this trend continues into 2026, in line with IMF projections (GDP growth of 6.3%), BoT assets are expected to reach TZS 32–35 trillion, liabilities to remain well-managed below TZS 30 trillion, and equity to strengthen above TZS 3 trillion—signaling a steadily growing and resilient economy. In comparison, the Central Bank of Kenya (CBK) holds total assets of approximately KES 2 trillion (USD 15–16 billion) with foreign reserves of around USD 12 billion (5.2–5.3 months of import cover) as of December 2025; while the CBK offers stronger liquid foreign reserves for greater protection against shocks, the BoT's gold-focused strategy provides a hedge against global price volatility, with both institutions contributing to their countries' growth (Kenya projected at 5.0–5.3% in 2026) through effective inflation control and credit stimulation. Read More: Central Bank Asset Dynamics and Tanzania’s Macroeconomic Performance in 2025–2026

Central Banks as Pillars of Growth: Comparing Tanzania and Kenya Amid Political Uncertainties

In East Africa, the Bank of Tanzania (BoT) and the Central Bank of Kenya (CBK) stand as critical institutions steering their respective economies toward stability and expansion. As of December 2025, both nations exhibit resilient growth trajectories, with Tanzania's GDP expanding by 5.6% in FY2024/25 and projections for 6.0-6.3% in 2025-2026, while Kenya anticipates 5.3% growth in 2025 amid controlled inflation. These figures reflect the central banks' pivotal roles in fostering economic development through monetary policy, reserve management, and financial stability. However, Tanzania's post-election political turmoil in late 2025 introduces risks that could dampen its 2026 outlook, underscoring the interplay between governance and economic progress. This article examines the functions of BoT and CBK in driving growth, offers a comparative lens, and explores how Tanzania's political dynamics might influence its economic path forward.

The Role of the Bank of Tanzania in Economic Development

The BoT, established under the Bank of Tanzania Act of 2006, serves as the guardian of monetary stability while actively supporting broader economic growth. Its primary mandate includes formulating and implementing monetary policy to maintain low inflation—currently at 3.33% in 2025—and ensuring financial system soundness. Beyond price stability, the BoT contributes to development by developing financial markets, promoting inclusive finance, and accumulating foreign reserves to buffer against external shocks. For instance, its November 2025 balance sheet reveals total assets of TZS 29.67 trillion (approximately USD 12 billion), bolstered by an 18.6% surge in gold holdings to TZS 4.67 trillion, reflecting strategic purchases from domestic miners to diversify reserves and support the mining sector—a key driver of Tanzania's export-led growth.

By managing currency in circulation (TZS 9.7 trillion as of November) and extending loans to the private sector (up 62% month-on-month to TZS 1.35 trillion), the BoT stimulates investment in agriculture, tourism, and manufacturing, which employ over 65% of the workforce. In January 2025's Monthly Economic Review, the BoT emphasized aligning monetary policy with growth objectives, such as sustaining reserves at USD 6.17 billion (4.7 months of import cover) to enhance investor confidence and facilitate infrastructure projects like LNG developments. These efforts have helped Tanzania achieve resilient GDP growth despite global headwinds, positioning the bank as a catalyst for long-term development through policies that encourage savings, credit access, and economic diversification.

The Role of the Central Bank of Kenya in Economic Development

Similarly, the CBK, mandated by Article 231 of Kenya's Constitution, prioritizes price stability while promoting economic growth and public interest. It formulates monetary policy, issues currency, and regulates the financial sector to foster a stable environment for investment. As of December 2025, the CBK lowered its Central Bank Rate (CBR) to 9.00% from previous levels, aiming to stimulate economic activity, support SMEs, and boost lending amid inflation of 4.46% in November—well within its 2.5-7.5% target. This proactive stance, as outlined in its bi-annual Monetary Policy Statements, regulates money supply growth in line with GDP targets, using tools like Open Market Operations and a Cash Reserve Ratio of 3.25% to manage liquidity.

The CBK's foreign exchange reserves stand at approximately USD 12 billion (5.2-5.3 months of import cover), providing a stronger buffer than Tanzania's and enabling interventions to stabilize the Kenyan Shilling. By encouraging long-term investments and maintaining deflation-free conditions, the bank supports key sectors like agriculture, services, and manufacturing, which have driven Kenya's consistent GDP expansion. For example, its role in currency issuance and management ensures efficient transactions, while financial inclusion initiatives have expanded access to credit, contributing to poverty reduction and job creation. Overall, the CBK acts as an economic enabler, balancing stability with growth to position Kenya as a regional hub.

Comparative Analysis: BoT vs. CBK in Driving Growth

While both central banks share core functions like inflation control and reserve management, their approaches reflect national economic structures. Tanzania's BoT emphasizes commodity diversification, with gold comprising a significant portion of reserves, aligning with its mining-dependent economy. In contrast, Kenya's CBK relies more on liquid foreign currency holdings, suiting its service-oriented market with higher external trade volumes.

This table highlights Kenya's edge in reserve depth for external resilience, while Tanzania's strategy hedges against volatility through gold. Both institutions have effectively contained inflation below 5%, fostering environments conducive to investment and poverty alleviation.

Tanzania's Political Landscape and Its Potential Impact on 2026 Economic Growth

Tanzania's political stability, once a regional benchmark, has been shaken by the October 2025 general elections, marred by allegations of irregularities and resulting in widespread protests. President Samia Suluhu Hassan secured re-election, but opposition parties like Chadema have decried the process as fraudulent, calling for a UN-overseen transitional government. Post-election violence led to a lethal crackdown by security forces, with UN experts condemning systematic human rights violations, including killings and digital restrictions. By December 2025, the government imposed nationwide protest bans, tightened security, and urged the military to remain apolitical amid escalating tensions.

This unrest could jeopardize Tanzania's 2026 economic projections of 6.1-6.3% GDP growth. Prolonged instability might deter foreign investment, disrupt tourism (a key forex earner), and strain fiscal resources through heightened security spending. If protests escalate, supply chain disruptions could inflate food prices, pushing inflation above the 3-5% target and eroding purchasing power. Moreover, international scrutiny from bodies like the UN and African Union could lead to sanctions or reduced aid, impacting reserves and infrastructure projects. However, if the government addresses grievances through dialogue—as hinted in recent calls for military professionalism—stability could return, allowing the BoT's policies to sustain growth amid global trade tensions.

Conclusion

The BoT and CBK exemplify how central banks can drive economic development by balancing stability with proactive growth measures, from reserve diversification in Tanzania to rate adjustments in Kenya. Their efforts have positioned both nations for robust 2025-2026 performance, with low inflation and adequate buffers against external risks. Yet, Tanzania's political volatility post-2025 elections poses a wildcard, potentially hindering 2026 growth through investor flight and fiscal strain. For sustained progress, addressing governance issues will be as crucial as monetary policy, ensuring these East African powerhouses continue their upward trajectories.

Tanzania’s economic performance in 2025 reflects a period of strong macroeconomic stability, export-led growth, and improving external resilience, underpinned by prudent monetary management by the Bank of Tanzania (BoT). As of 30 November 2025, the BoT’s financial position signals a notable strengthening of the country’s economic fundamentals, with total assets rising to TZS 29.67 trillion, equivalent to a 4.9% increase (about TZS 1.39 trillion) compared to October 2025. This expansion mirrors heightened foreign exchange inflows, record performance in the mining sector—particularly gold—and rising domestic economic activity, all of which have reinforced liquidity conditions and reserve buffers.

A defining feature of 2025 has been the rapid accumulation of gold and liquid assets. Total gold holdings (monetary and bullion combined) increased by 18.6% to TZS 4.67 trillion, driven by the BoT’s domestic gold purchase programme and Tanzania’s exceptional export performance. Gold export earnings reached an estimated USD 4.3–4.43 billion in the year ending September/October 2025, representing a 35–36% year-on-year increase and firmly establishing gold as the country’s leading foreign exchange earner. In parallel, cash and cash equivalents rose by 32.8% to TZS 4.45 trillion, reflecting strong inflows from exports and services such as tourism, as well as improved liquidity management. These trends have contributed to a more diversified and resilient reserve position.

These monetary and reserve developments are consistent with Tanzania’s broader macroeconomic outcomes in 2025. Real GDP growth is estimated at 6.0–6.3%, supported by mining, tourism (with arrivals rising by around 11%), agriculture, manufacturing, and large-scale infrastructure projects. Inflation remained subdued at about 3.4% in November 2025, comfortably within the BoT’s 3–5% target band, while foreign exchange reserves stood at around USD 6.17 billion (approximately 4.7 months of import cover) by end-October 2025, meeting regional adequacy benchmarks and enhancing exchange rate stability.

Economic Trajectory for 2026

Looking ahead, Tanzania’s macroeconomic outlook for 2026 remains broadly positive, building on the strong foundations established in 2025. Current projections from international and domestic sources point to real GDP growth of about 6.1–6.3% in 2026, indicating stable to slightly accelerating momentum. Growth is expected to continue being driven by mining (especially gold), tourism, infrastructure investments, manufacturing, and gradual expansion in private sector credit, supported by ongoing structural reforms aimed at improving the business environment.

Inflation in 2026 is projected to remain around 3.5%, still within the BoT’s policy target range, reflecting continued prudent monetary policy, stable food supply conditions, and moderated global energy prices. Foreign exchange reserves are expected to remain adequate—above 4.5–5 months of import cover, bolstered by sustained gold and tourism receipts and steady capital inflows. Gold exports are likely to remain elevated, potentially exceeding USD 4 billion, although performance will remain sensitive to global commodity prices and production dynamics.

Overall, the 2026 trajectory suggests that Tanzania is well positioned to consolidate its macroeconomic gains, strengthen external buffers, and advance toward its medium-term development goals, including upper-middle-income status. Nonetheless, risks such as commodity price volatility, climate-related shocks, and post-election policy adjustments could influence outcomes. Maintaining fiscal discipline, deepening export diversification, and sustaining prudent monetary management will be critical to preserving stability and translating growth into inclusive and resilient economic development beyond 2026. Read More: Tanzania Economic Updates December 2025

Key Changes in the BoT Balance Sheet (November vs. October 2025)

The table below highlights selected major items (in TZS '000) with significant changes, focusing on those relevant to economic development (e.g., reserves, gold, and liquidity indicators).

The most notable development is the ~18.6% increase in total gold holdings (combined monetary and bullion gold), driven by Tanzania's mining sector expansion and the BoT's policy of purchasing gold from domestic producers. This aligns with record gold export earnings of approximately USD 4.3–4.43 billion in the year ending September/October 2025, a ~35–36% surge year-on-year, fueled by high global gold prices and increased production.

Broader Tanzania Economic Indicators (2025 Context)

Tanzania's economy in 2025 demonstrates resilient growth, low inflation, and strengthening external buffers, supported by key sectors: mining (gold-led), tourism (strong recovery in arrivals), agriculture (stable output despite weather risks), and infrastructure investments. GDP growth is driven by exports and public projects, with foreign reserves providing a buffer against external shocks.

These indicators reflect sustained economic development:

• Mining boom directly contributes to the BoT's gold reserve buildup, enhancing foreign exchange reserves and fiscal revenues.
• Low inflation (around 3–3.5%) supports purchasing power and investment attractiveness.
• Adequate reserves (4.5–5 months import cover) provide stability amid global uncertainties.
• Ongoing reforms (e.g., infrastructure like ports/railways, LNG projects) and private sector lending growth signal diversification beyond traditional agriculture.

Overall, the BoT balance sheet reinforces a positive outlook for Tanzania's economy, characterized by export-led growth, macroeconomic stability, and progressive reserve accumulation in 2025.

Tanzania's Economic Trajectory for 2026

Tanzania's strong macroeconomic momentum in 2025 is expected to carry into 2026, with projections indicating continued resilient growth, low inflation, and strengthening external buffers. International and domestic forecasts highlight sustained performance in key sectors—particularly mining, tourism, infrastructure investments, and manufacturing—while ongoing reforms aim to enhance diversification and private sector participation. The Bank of Tanzania's prudent monetary management and reserve accumulation are likely to support exchange rate stability and resilience against global uncertainties. However, risks such as potential political transitions following the 2025 elections, commodity price volatility, and climate-related challenges could moderate the pace if not managed effectively.

Projected Key Economic Indicators for 2026

The table below summarizes major forecasts from reputable sources (as of late 2025 data), compared to 2025 estimates for context.

Overall, the 2026 outlook reinforces Tanzania's path toward upper-middle-income status, with export-led growth and reserve buildup (as seen in the BoT's 2025 balance sheet trends) providing a solid foundation. Successful implementation of structural reforms, climate-resilient investments, and fiscal prudence will be critical to achieving these projections and mitigating downside risks.

Conclusion

The Bank of Tanzania's November 2025 balance sheet paints an optimistic picture of the nation's macroeconomic health, with significant asset growth, diversified reserves (particularly in gold), and strengthened equity signaling enhanced resilience and capacity for development financing. Tanzania's 2025 performance—marked by record export earnings, low and stable inflation, private sector credit expansion, and GDP growth around 6%—has been anchored by effective central bank policies and sectoral strengths in mining and tourism, providing a buffer against external risks while fostering inclusive progress.

As the economy transitions into 2026, projections of 6.1–6.3% GDP growth, inflation remaining around 3.5%, and sustained reserve adequacy offer a compelling outlook for continued momentum. Key opportunities lie in advancing structural reforms, climate-resilient investments, and diversification efforts to mitigate risks such as commodity price fluctuations or global slowdowns. With the BoT's prudent stewardship and export-led drivers intact, Tanzania is well-positioned to build on its 2025 gains, driving sustainable development, job creation, and regional leadership in the years ahead.

Evidence from 2010–2025

Fiscal decentralization in Tanzania, pursued through the policy of Decentralization by Devolution (D by D), aims to empower Local Government Authorities (LGAs) with greater financial autonomy to fund and manage local development effectively. A key measure of success is the extent to which LGAs can rely on own-source revenue—locally generated through property rates, fees, licenses, and service levies—rather than central government transfers. The core question is whether this policy has meaningfully improved the financial sustainability of LGAs, enabling them to independently finance the bulk of grassroots projects such as roads, schools, health centers, water supply, and sanitation.

Evidence from LGA revenue data spanning 2010 to 2025 indicates that fiscal decentralization has not significantly enhanced financial sustainability. While own-source revenue has grown substantially in absolute terms—from TZS 13.9 billion in 2010 to TZS 147.8 billion in 2025 (a more than tenfold increase)—this has failed to reduce heavy dependence on central transfers. The own-source share of total LGA revenue averaged only 2.8% over the period (excluding the anomalous 0.5% in 2016), ranging from a low of 1.9% in 2012 to a high of 4.1% in 2025. In recent years, despite own-source collections reaching TZS 121.9 billion in 2024 and TZS 147.8 billion in 2025, the share remained modest at 3–4%. This means central government transfers continued to account for 96–98% of total LGA revenue, which expanded from TZS 609.7 billion in 2010 to TZS 3,570.4 billion in 2025.

This persistently low own-source contribution highlights limited progress toward true fiscal autonomy. LGAs, despite implementing most development projects critical to national goals like the Five-Year Development Plans and Sustainable Development Goals, lack the financial independence needed for proactive, timely, and locally prioritized planning. Delays in project execution and resource inefficiencies often result from this dependency.

Several structural challenges explain the stagnation:

• Inconsistent revenue collection: Sharp fluctuations—such as drops to TZS 17.2 billion in 2012 and TZS 69.1 billion in 2022—reveal weaknesses in administrative systems and enforcement.
• Inadequate tracking and transparency: Incomplete data records, particularly pre-2010 and in certain years, signal systemic monitoring gaps that hinder accountability and mobilization.
• Constrained revenue bases: Outdated property valuations, underutilized levies, and leakages from manual processes limit potential yields.
• Disincentives from transfer reliance: Predetermined central allocations reduce motivation for local revenue innovation.

Recent trends offer cautious optimism, with own-source growth accelerating in 2023–2025 and the share reaching 4.1% in 2025—the highest in the period. However, this remains far below levels needed for genuine sustainability.

To achieve meaningful enhancement through fiscal decentralization, targeted reforms are required. Priorities include digitalizing revenue administration (e.g., electronic billing and mobile payments), conducting regular property revaluations, building staff capacity, and introducing incentives for high-performing LGAs, such as greater autonomy or matching grants. Linking revenue strategies to local economic drivers—like agriculture, tourism, and small industries—could further boost collections organically. A medium-term target of 10–15% own-source share would better align resources with community needs, foster decentralized development, and build resilience against fiscal shocks.

In summary, while absolute own-source revenue has risen impressively, the low and stagnant share over 2010–2025 demonstrates that fiscal decentralization has yet to deliver substantial financial sustainability for Tanzania’s LGAs. Sustained, bold reforms are essential to realize the full potential of devolution.

Note: The 2016 data point shows Own Sources as 0.0B (likely a recording error or missing data, as noted in the document's limitations). It is treated as anomalous in trend calculations. The "Non-Tax Revenue" column does not factor into the LGA Share % and appears unrelated to the core self-reliance metric (possibly national non-tax figures or a separate category). Read More: Local Government Revenue Collections in Tanzania

Data Table (in billions TZS)

Key Trends and Insights

• Absolute Growth in Own Sources — Own-source revenue grew strongly from 13.9B TZS in 2010 to 147.8B TZS in 2025 (over 10x increase). Compound Annual Growth Rate (CAGR, excluding 2016): 18.4%.
• Growth in Total Revenue — Total LGA revenue (largely driven by central transfers) rose from 609.7B to 3,570.4B TZS (about 6x increase). CAGR: 13.5%.
• LGA Share % (Self-Reliance Indicator):
  • Average (2010–2025, excluding 2016): 2.8%.
  • Range: Low of 1.9% (2012) to high of 4.1% (2025).
  • Trend: Mild upward linear trend (+0.08 percentage points per year), explaining about 43% of variation (moderate positive progress).
  • Recent years (2020–2025) show volatility but improvement: Peak at 3.7% (2020), dip to 2.2% (2022), then recovery to 4.1% (2025) — driven by strong own-source growth (+46% in 2023, +21% in 2024–2025) while total revenue slowed or declined in 2025.

Implications for LGA Economic Self-Reliance

The revenue data from 2010 to 2025 clearly illustrates that Tanzania's Local Government Authorities (LGAs) remain heavily dependent on central government transfers, which consistently account for 95–98% of total revenue. Even at the highest point in the period—4.1% own-source share in 2025 (TZS 147.8 billion out of TZS 3,570.4 billion total)—locally generated funds cover only a marginal fraction of budgetary needs. This structural dependency severely constrains fiscal autonomy at the local level, where the majority of development projects are executed, including critical infrastructure such as roads, schools, health centers, and water supply systems.

Positive Developments

Despite the overall low share, several encouraging trends emerge:

• Own-source revenue has grown substantially faster than total revenue, increasing more than tenfold from TZS 13.9 billion in 2010 to TZS 147.8 billion in 2025, compared to total revenue rising approximately sixfold over the same period.
• A notable acceleration in recent years (2023–2025), with own-source collections rising from TZS 100.8 billion (3.2% share) in 2023 to TZS 121.9 billion (3.1%) in 2024 and TZS 147.8 billion (4.1%) in 2025, marking the strongest upward momentum in the dataset.

These gains suggest that, with continued effort, higher levels of self-reliance are achievable.

Persistent Challenges

The data also exposes significant obstacles that hinder progress:

• Volatility in collections: Sharp declines, such as own-source revenue falling to TZS 17.2 billion (1.9% share) in 2012 and TZS 69.1 billion (2.2%) in 2022, indicate inconsistent enforcement and administrative weaknesses.
• Systemic deficiencies in tracking: As highlighted in the dataset limitations, incomplete records and poor monitoring mechanisms undermine accountability and effective revenue mobilization, creating a self-reinforcing barrier to improvement.

Pathways to Greater Economic Self-Reliance

To build on recent progress and reduce reliance on central transfers, LGAs must pursue targeted, sustained reforms that address both administrative and structural constraints:

1. Strengthen Revenue Collection Systems Invest in digital tools—such as electronic billing, mobile money integration, and automated tracking—and provide staff training to minimize leakages and enhance efficiency, directly tackling the poor tracking mechanisms noted in the data.
2. Broaden and Enforce Revenue Bases Prioritize high-yield sources including property rates, business licenses, service levies, and market fees. Implementing regular property revaluations, especially in rapidly growing urban and peri-urban areas, could support sustained annual growth of 15–20% in own-source revenue.
3. Enhance Capacity Building and Incentives Offer targeted technical and financial support to underperforming LGAs while introducing performance-based incentives—such as increased autonomy or matching grants—for those demonstrating strong collection improvements.
4. Link Revenue to Local Economic Growth Promote investments in sector-specific opportunities (e.g., agriculture processing, tourism, and small-scale industries) to organically expand the taxable base and generate higher local returns.
5. Establish Clear Policy Targets Set ambitious yet realistic medium-term goals, such as progressively raising the own-source share to 10–15%, to provide a measurable roadmap for shifting project financing toward locally determined priorities.

In conclusion, while absolute own-source revenue has shown impressive growth and recent trends are promising, true economic self-reliance demands accelerating the own-source share well beyond the current low single digits. Without comprehensive reforms to address volatility, administrative gaps, and narrow revenue bases, LGAs will continue to face limited fiscal space. The upward trajectory since 2020 demonstrates potential, but only deliberate policy action will close the gap and enable LGAs to finance local development more independently and effectively.

An Assessment Based on Revenue-Expenditure Trends (2000–2025)

Analysis of fiscal data from 2000 to 2025 reveals that Tanzania cannot yet fully self-finance its development agenda without external support. Despite significant improvements in domestic revenue mobilization, persistent structural deficits indicate continued dependence on donor financing and concessional loans to bridge the gap between revenues and expenditures.

Persistent Fiscal Deficits

Tanzania has recorded fiscal deficits in 24 out of 26 years between 2000 and 2025, demonstrating that domestic revenues have consistently fallen short of total government expenditure. In the early 2000s, revenues covered only 58–70% of expenditure, creating financing gaps of 30–40% that required external grants, concessional loans, and domestic borrowing. For instance, in 2000, the government collected TZS 859 billion against expenditure of TZS 1,283 billion, resulting in a deficit of TZS 424 billion.

Although revenue performance has improved substantially over the past two decades, the structural imbalance persists. By 2024, total revenue had increased to TZS 33.9 trillion, yet expenditure expanded even faster to TZS 39.9 trillion, producing a record deficit of TZS 6.1 trillion. In recent years, revenues have covered only 84–87% of expenditure on average, meaning that 13–16% of government spending remains unfunded by domestic resources.

The 2018 Anomaly

The only year in which Tanzania achieved full fiscal self-sufficiency was 2018, when a surplus of TZS 853 billion was recorded and revenue coverage reached 105%. However, this outcome proved temporary and non-recurring. Deficits re-emerged immediately afterward due to renewed spending pressures and external shocks, including the COVID-19 pandemic period, demonstrating that the surplus was not indicative of a sustainable structural shift.

2025 Outlook

Preliminary data for January–September 2025 reinforces the conclusion of continued fiscal dependence. Within nine months, the government recorded revenue of TZS 26.3 trillion against expenditure of TZS 31.3 trillion, generating a deficit of TZS 5.0 trillion. Annualized projections indicate that Tanzania will continue to rely on external financing and borrowing to sustain both development projects and recurrent obligations.

Based on current revenue and expenditure dynamics, Tanzania cannot yet fully operate and implement large-scale development projects without external donor support. While domestic revenues—largely driven by tax collections—have grown impressively and now finance the majority of government spending, they remain insufficient to close the fiscal gap consistently. Donor financing, concessional loans, and external support continue to play a critical complementary role, particularly in infrastructure, social services, and development financing.

Tanzania is moving toward greater fiscal self-reliance, but achieving full independence from donor funding will require further expansion of the tax base, improved revenue administration efficiency, tighter expenditure prioritization, and sustained economic growth. Until these structural reforms fully materialize, external support will remain an integral component of financing Tanzania's development agenda. Read More: Overview of Government Budgetary Operations (October 2025)

Historical Analysis of Tanzania's Government Budgetary Operations (2000–2025)

The attached document provides calendar-year data on Tanzania's central government finances (in billions TZS), with deficit/surplus calculated as Total Revenue minus Total Expenditure (before grants and financing). Note that the "Total Expenditure" column shows negative values, so actual expenditure is the absolute value (e.g., -17,037 in 2018 means expenditure of 17,037 billion TZS).

Key trends:

• Persistent Budget Deficits: In 24 out of 26 years (2000–2025), revenues fell short of expenditures, resulting in deficits. The only surplus occurred in 2018 (+853 billion TZS). Deficits indicate reliance on external grants, domestic borrowing, or foreign loans to bridge the gap.
• Revenue Coverage of Expenditure (Revenue as % of Expenditure): This measures how well revenues "closed the budget gap."
  • Early 2000s: Low coverage, often 60–70% (e.g., 2000: 66.9%; 2004: 58.1%).
  • Mid-2000s to early 2010s: Remained low, dipping to ~62% in 2010.
  • Improvement from mid-2010s: Rose to 80–90% range.
    • 2017: 91.2%
    • 2018: 105% (surplus)
    • 2020: 91.7% (strong during early COVID period)
    • Recent years: Stabilized at ~84–87% (2021–2024 average ~85.7%)
    • 2025 (Jan–Sep only, partial year): ~84.1% (revenue 26,332 / expenditure 31,323)
• Absolute Deficit Growth: Deficits widened over time due to expanding government spending on infrastructure, education, and social programs.
  • 2000: -424 billion TZS
  • 2010: -3,162 billion
  • 2024 peak: -6,053 billion
  • 2025 partial: -4,991 billion (likely higher if annualized)
• Revenue Growth: Strong in many years (average ~18% in high-growth periods like 2006–2007), driven largely by tax revenue (typically 80–90% of total revenue). However, expenditure often grew faster, widening gaps.
• Overall Insight: Revenues have progressively covered a larger share of expenditures (from ~60% average in 2000–2010 to ~85–90% in 2020–2024), reflecting improved tax collection and economic growth. However, full coverage remains elusive except in 2018, creating a structural fiscal gap of 10–40% historically (narrower recently).

This gap represents the unfunded portion of the budget, typically financed through debt, leading to rising public debt obligations over time.

Addressing the Budget Gap: Recommended Actions

The persistent deficit is a common challenge in developing economies like Tanzania, driven by ambitious development spending outpacing revenue growth. If left unaddressed, it risks higher debt servicing costs, inflation, or reduced fiscal space for emergencies.

Key recommendations to close the gap:

1. Boost Domestic Revenue Mobilization:
   • Strengthen tax administration (e.g., via Tanzania Revenue Authority digitalization, reducing evasion, and broadening the tax base).
   • Minimize tax exemptions and incentives that erode collections.
   • Introduce fair, progressive reforms (e.g., property taxes, digital economy taxation) without stifling growth.
   • Target: Raise tax-to-GDP ratio (historically ~11–13%) toward 15%+ as seen in peer economies.
2. Improve Expenditure Efficiency:
   • Prioritize high-impact development projects (infrastructure, education, health) over lower-priority recurrent spending.
   • Conduct regular audits to curb waste, corruption, and leakage.
   • Shift toward performance-based budgeting.
3. Promote Economic Growth and Diversification:
   • Attract private investment (FDI) in sectors like mining, tourism, manufacturing, and agriculture to expand the taxable base.
   • Support SME growth and formalization.
4. Prudent Debt Management:
   • Favor concessional borrowing and limit commercial debt.
   • Build fiscal buffers during good years.
5. Institutional Reforms:
   • Enhance transparency and public participation in budgeting.
   • Align with medium-term fiscal frameworks (as Tanzania has done in recent plans).

These steps, if implemented consistently, could achieve sustained surpluses or near-balance, as briefly seen in 2018.

Outlook for 2026 Amid Current Political Situation

Tanzania's fiscal year runs July–June, so calendar 2026 spans the second half of FY 2025/26 and the first half of FY 2026/27.

• Approved FY 2025/26 Budget (presented June 2025, ~56.5–57 trillion TZS total):
  • Targets revenue growth and expenditure control.
  • Aims to reduce fiscal deficit to ~3.0% of GDP (from 3.4% in 2024/25), with tax revenue rising to 13.3% of GDP.
  • Supported by projected 6%+ economic growth and macro stability (per IMF and government projections).
• Positive Factors for 2026:
  • Continued infrastructure push and reforms could support revenue if growth holds.
  • IMF forecasts contained deficits (~2.8–3.0% of GDP) into 2026–2027.

However, the current political situation (as of December 2025) poses significant risks:

• The October 2025 general election saw President Samia Suluhu Hassan (CCM) re-elected with ~97–98% of votes, but results were widely disputed.
• Opposition candidates faced exclusions, leading to post-election protests and a severe government crackdown (reports of hundreds killed, widespread arrests).
• Ongoing tensions include banned protests, heavy security deployments, internet restrictions, and international criticism (UN, Human Rights Watch, Amnesty, potential aid reviews by US/West).
• This instability could:
  • Deter investors and tourism.
  • Disrupt economic activity.
  • Lead to aid/grant suspensions.
  • Increase security-related spending.
  • Cause revenue shortfalls if growth slows.

Expectation for 2026: Official targets suggest a continued narrowing of the deficit (toward 2–3% of GDP) if stability returns and reforms proceed. However, prolonged political turbulence risks higher deficits (potentially wider gaps), slower growth, and strained financing. Much depends on de-escalation and inclusive dialogue in early 2026. Monitoring sources like the Ministry of Finance, Bank of Tanzania, and IMF updates will be key.

Financial data from 2000 to 2025 (in billions TZS)

Note: All values in billions TZS. 2025 data includes Jan-Sep only (9 months). Deficit/Surplus = Revenue - Expenditure (before grants and financing).