Windfall Fellowship Program

Welfare in the AI Transition: Kenya Case Study

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This case study examines whether Kenya’s welfare system can protect households from AI-related labour market disruption in an economy where more than 80% of workers are informally employed and changes in earnings are largely invisible to government systems. We find strong payment and emergency-response capacity, but weaker systems for identifying need, keeping registries current and tracking changes in informal and platform work. We identify the measures Kenya can take now, and the more ambitious forms of income protection that depend on stronger data governance, registry integration and fiscal capacity.

Published August 18th 2026

Emma Kimani

Emma Kimani

Raphael Gregorian

Raphael Gregorian

Deric Cheng

Deric Cheng

This case study applies Windfall Trust’s Welfare Resilience Assessment Framework to assess how prepared Kenya’s welfare system is for the economic changes associated with the AI transition.

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Welfare Resilience Snapshot · Kenya

Risks

What pressures does the welfare system face?

Policy levers

What instruments can respond to these pressures?

Enablers

Can those instruments actually function effectively?

1. OVERALL RISK EXPOSURE

What pressures does the welfare system face?

Dominant exposure

Income volatility

Most workers earn in informal, self-employed or casual activities where earnings fluctuate frequently. AI adoption is likely to amplify these fluctuations.

AI AMPLIFIES THIS THROUGH

Global competition in digitally traded services
Automation of routine service tasks

Risk dynamics

SHORT TERM

Disruptive

Earnings shocks arrive quickly: food price changes, droughts, shifts in platform demand.

FRONT-LOADED

MEDIUM TERM

Transitional

Risks build gradually as tasks change in outsourcing, logistics and digital work.

LONG TERM

Structural

Tied to persistent informality and limited redistribution capacity.

Concentration of exposure

The missing middle remains the sharpest exposure

WHO CARRIES IT

Informal workers
Smallholder farmers
Young service-sector workers

WHERE IT CONCENTRATES

Urban informal economies
Drought-prone regions

2. BINDING CONSTRAINTS

The conditions that most limit welfare policy responses

Limited income visibility

Informal labour market

Earnings are difficult to observe in administrative data when most work sits outside formal payrolls.

Fragmented data systems

Enhanced single registry

The registry exists but suffers from uneven updating, limited interoperability and incomplete integration with other government systems.

Limited fiscal headroom

Narrow tax base · High informality

Expansion of social protection depends largely on general revenues, in an economy with a narrow tax base and high informality.

3. CAPACITY PROFILE

Each capacity answers one risk dimension; systemic capacity runs beneath all three

DISRUPTIVE · SHORT TERM

Coping capacity

IN PLACE

Inua Jamii and the Hunger Safety Net Programme (HSNP) operate at scale and have expanded during crises
Mobile money enables rapid transfers once beneficiaries are identified

LIMITS

Coverage and benefit levels remain limited relative to the scale of informal income volatility

TRANSITIONAL · MEDIUM TERM

Adaptive capacity

IN PLACE

Ajira Digital Programme, TVET systems and the National Employment Authority support transitions
A large innovation ecosystem of start-ups and technology hubs

LIMITS

Training systems and institutions adjust slowly to shifts in digital labour demand
Limited visibility into platform-mediated work

STRUCTURAL · LONG TERM

Transformative capacity

IN PLACE

Targeted social assistance carries the system's redistributive load

LIMITS

Payroll-based redistribution reaches only a small share of workers
Persistent informality limits contributory insurance and broader redistribution

ACCESS & DELIVERY · CROSS-CUTTING

Systemic capacity

operates across all three horizons

IN PLACE

Widespread mobile money use, expanding connectivity and a growing data-centre ecosystem
eCitizen and the Enhanced Single Registry support national coordination

LIMITS

Identity governance challenges, documentation gaps and registry updating constraints create exclusion risks as digital systems expand
Device affordability, digital literacy and connectivity gaps remain barriers, particularly for rural populations, women and older users

4. WHAT CAN BE DONE NOW VS LATER

The framework's output: which levers can move now and which depend on reform first

Achievable now

Within existing law, institutions and fiscal capacity

Rules-based scale-up triggers in existing cash transfers

Expand HSNP and Inua Jamii during shocks, using drought early-warning indicators or food price indices.

Temporary income stabilisation through public works

Programmes such as Kazi Mtaani can stabilise earnings for urban youth during labour market shocks.

Strengthen digital livelihoods programmes

Expand initiatives such as the Ajira Digital Programme while linking them to structured training and progression pathways.

AS
ENABLERS
STRENGHTEN

Feasible only if enablers are strengthened

Blocked on legal, institutional or fiscal reform

Earnings-responsive stabilisers

Automatic stabilisers based on labour market or transaction data.

Depends on: Legal frameworks for data sharing, Stronger data governance, Improved registry integration

Platform labour reporting frameworks

Linking digital labour platforms with public labour market information systems.

Broader social protection systems

Universal or quasi-universal programmes for informal households.

Depends on: Sustained fiscal expansion, Improved enrolment systems for informal households

Kenya’s welfare risk profile is shaped by widespread informality, frequent income volatility and the rapid digitisation of government systems. AI is likely to intensify existing pressures rather than create an entirely new pattern of risk. Disruption may appear through changing tasks, falling earnings and less stable contracts in outsourcing, customer support and other digitally traded services. For most workers, however, income shocks will continue to arise outside formal employment and may never appear in unemployment statistics.

Applying Windfall’s Welfare Resilience Assessment Framework, this case study finds that Kenya’s strongest capacity lies in payment delivery and emergency response. Inua Jamii, the Hunger Safety Net Programme and mobile money infrastructure allow government to move cash quickly once recipients have been identified, and these systems have expanded during droughts and other crises.

The central weakness comes earlier in the delivery chain. More than 80% of workers earn outside formal payrolls, social registries are updated unevenly, and identity and documentation gaps can exclude eligible households. Official labour statistics also provide limited visibility into platform work, contract duration and earnings volatility. Kenya has transition institutions, including TVET providers, the Ajira Digital Programme and the National Employment Authority, but their coverage and responsiveness to changing digital labour demand remain uneven.

The report therefore recommends a sequenced approach. Near-term priorities include more reliable enrolment and registry updates, stronger grievance and appeal mechanisms, better labour market data, rules-based expansion of existing cash transfers during shocks, temporary public works and clearer progression routes through digital livelihoods programmes. Earnings-responsive stabilisers and broader social protection for informal households should follow only when legal frameworks for data sharing, data governance, registry integration and fiscal capacity are strong enough to support them.

Kenya already has the infrastructure to move money quickly. Its preparedness will depend on whether it can identify emerging need accurately and include households before disruption becomes a crisis.