## AI and the Informal Economy

## Source details

**Canonical URL:** [AI and the Informal Economy](https://www.imf.org/en/publications/fandd/issues/2026/09/point-of-view-ai-and-the-informal-economy-anthony-tan)

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## Bibliographic details
- Authors: ANTHONY TAN
- Published: August 18, 2026

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### Overview
- Focus: How artificial intelligence can benefit people in developing economies by starting from the realities of informal labor markets rather than formal-economy assumptions.
- Central claim: In Southeast Asia, the informal economy is a structural foundation—flexibility and adaptability are features, not failures—and AI-enabled platforms can strengthen resilience and earnings for informal workers without requiring formalization.

### Platform interventions and outcomes
- Grab’s lending and credit assessment:
  - Last year Grab disbursed $3.2 billion in loans to driver partners and merchant-partner borrowers.
  - Sixty-eight percent of those borrowers accessed formal credit for the first time through the platform.
  - The platform uses AI to read platform-generated records of earnings and activity to judge creditworthiness, set credit limits based on platform earnings, deduct repayments in proportion to daily income, and grant hardship relief case-by-case if earnings cease.
  - Half of driver-partner borrowers say they turned to Grab to avoid unlicensed lenders.
- Earnings and matching:
  - Average driver-partner earnings per online hour rose by 5.5 percent year over year last year.
  - Platform capabilities include real-time demand assessment and job matching to boost earnings and reduce unpaid gaps between jobs; the platform predicts the best spot for the next job.
- Merchant support:
  - One in four micro, small, and medium enterprises on the platform now uses Grab’s Merchant AI Assistant.
  - Merchant AI Assistant supports marketing, menu management, and operations, and underpinned a 15 percent lift in sales.

### Skills, training, and AI literacy
- Argument: Realizing AI’s potential requires investment in skills so workers can understand and benefit from AI-enabled tools; informal workers need access to training outside formal-employer structures.
- Reach of training:
  - More than 1.5 million driver partners completed at least one GrabAcademy course last year.
- Interaction of tools and training: AI paired with practical, work-relevant training multiplies gains from platform participation.

### Policy recommendations — "My three asks"
- First: Fund AI literacy as a public good.
  - AI literacy should be funded with the same seriousness as roads or energy.
  - Public-private partnerships can scale permanent, codesigned training structured for workers with irregular hours; example: SkillsFuture Singapore has recognized Grab as an industry leader in championing skills development.
- Second: Rethink how success is measured.
  - Governance frameworks should adopt metrics reflecting informal economy dynamics—earnings volatility, participation in multiple platforms, access to credit—rather than calibration around formalization rates or financial stability alone.
  - Regulators must hold platforms and themselves accountable to those metrics to avoid missing what matters for the informal economy.
- Third: Unify regional AI governance.
  - Diversity of regulatory frameworks across Southeast Asia’s main markets constrains platforms’ decisions on data storage and scaling what works.
  - The May 2026 Association of Southeast Asian Nations’ Digital Economy Framework Agreement establishes a needed regional coordination architecture; policymakers must ensure the framework works for the informal economy and does not impose formal economic assumptions regionally.

### Designing policy around informality
- Principle: Effective measures are built around informality rather than imported from systems developed for formal economies.
- Practical approaches:
  - Use real-time behavioral data where documentation requirements fail.
  - Use platform-based distribution where institutional access does not reach.
  - Build protections that travel with the worker across jobs and platforms (portable coverage).
- Example of portable social protection:
  - Malaysia’s March 2026 Gig Workers Act extends social security coverage to gig workers through the national program without making them employees.
- Wider applicability:
  - Southeast Asia as a proof of concept for regions where informal work is large; policymakers in Africa, Asia, and Latin America can draw lessons.

### Key statistics and regional context
- Informality in Southeast Asia:
  - 78 percent of the workforce operates in the informal economy.
- Regional informal employment shares:
  - Africa: 86 percent of employment.
  - Asia: 68 percent of employment.
  - Latin America: 51 percent of employment.
- Grab program metrics (last year):
  - $3.2 billion disbursed in loans.
  - 68 percent first-time formal credit access for borrowers.
  - 5.5 percent year-over-year rise in average driver-partner earnings per online hour.
  - More than 1.5 million driver partners completed at least one GrabAcademy course.
  - One in four micro, small, and medium enterprises uses Merchant AI Assistant; 15 percent lift in sales attributed.

*Anthony Tan, "AI and the Informal Economy," F&D Magazine, September 2026.*

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_Source: https://www.imf.org/en/publications/fandd/issues/2026/09/point-of-view-ai-and-the-informal-economy-anthony-tan_