AI's varied economic impact in emerging markets hinges on preparedness

The productivity and growth effects of artificial intelligence (AI) vary widely across countries, reflecting differences in sectoral composition and adoption capacity.

Micro-level studies show substantial productivity gains from generative AI, often between 10 and 65 percent, particularly in tasks like coding and professional writing.

AI also tends to equalize workplace performance, with junior developers experiencing significant productivity increases relative to senior developers.

However, the aggregate impact on economy-wide total factor productivity remains uncertain, with estimates ranging from 0.07 percent to 0.9 percentage points annually.

Labour market implications are significant, as up to 60 percent of occupations could see substantial task reallocation by 2030. In emerging market economies (EMEs), informal workers face heightened automation risks due to weaker social protection and limited skill access, potentially leading to short-term job displacement.

Cross-country differences in AI's impact stem from sectoral composition and AI preparedness.

Many emerging market economies (EMEs) are likely to see smaller near-term benefits as their output is less concentrated in AI-intensive sectors like finance and information.

Sectors such as agriculture and construction, prevalent in EMEs, show low exposure to generative AI.

AI preparedness, encompassing digital infrastructure, a skilled workforce, innovation capacity, and sound regulatory frameworks, is crucial.

The IMF's AI Preparedness Index (AIPI) shows advanced economies generally better positioned.

While some EMEs score highly on digital infrastructure, many exhibit uneven profiles, particularly in human capital and regulatory readiness.