ContextSpeech by the BIS General Manager at a large fintech event in India, at the invitation of the Reserve Bank of India.
Why it mattersA reference speech on what AI means for central banks: measurement of the economy, the risk of an investment bust and the gap between rich and poor countries.
- Many poorer economies lack the digital infrastructure to benefit from AI.
- AI makes output and the natural interest rate harder to measure.
- An AI investment arms race could turn into a bust.
- Build on digital public infrastructure, as India has done.
- Focus AI efforts on areas of comparative advantage instead of duplication.
- Invest in measurement, judgement and international cooperation.
Read the speech summary
1. Demand, investment and trade
Speaking at the Global Fintech Fest in Mumbai, BIS General Manager Pablo Hernández de Cos organised his remarks around three questions. AI is already reshaping the global economy. On demand, it has triggered an investment boom in data centres, chips, cloud and hardware, and its optimism keeps financial conditions loose, supporting consumption through wealth effects. The five biggest tech firms alone plan over a trillion dollars of AI spending across 2025-26, and industry expects global AI investment to rise from about 500 billion dollars to 3-4 trillion by 2030, increasingly financed by debt and private credit. Trade is affected too: prices of AI-related goods have risen while other export prices stayed flat, so economies high in the supply chain, such as Taiwan, Korea, Malaysia and Singapore, gain, though narrowly (five Korean firms made 43% of export earnings), while heavy buyers of equipment lose terms of trade.
2. Productivity and jobs
On supply, task-level studies show productivity gains of 10 to 65% from generative AI, strongest for less experienced workers, and published estimates centre on roughly half a point a year added to productivity growth, with early evidence that better-prepared economies grew productivity faster. For work, AI both complements and substitutes. Informal workers in developing economies, with least protection and training, are most exposed; displacement so far is limited but emerging in customer support, programming and administration, and nearly 80% of firms discuss automation plans. His lesson is to prepare people through reskilling, not to resist the technology.
3. Divergence between economies
Advanced economies are likely to gain more in the short run because finance and professional services weigh more there and AI preparedness is higher. But emerging economies differ widely: China and parts of the Middle East are very well prepared, many low-income countries lag, and India, with its digital public infrastructure, has a real chance to close the gap. AI production is a five-layer chain (chips, cloud, data, foundation models, applications) with high fixed costs and scale economies, favouring a few giants in the US, China, Taiwan, Korea and the Netherlands. Smaller economies face a trade-off between building national capacity for resilience and wasteful duplication; many can focus on local applications, models for local languages and domain data.
4. Central banks and financial stability
The mandate is unchanged, but AI makes the economy harder to read, making it harder to pin down how much the economy can produce and where neutral interest rates sit. The BIS sets out three long-run scenarios: a bounded productivity boost, explosive self-improving growth, and a demand bottleneck in which displaced workers, as lost consumers, eventually starve the spending that supports innovation; in the last, the natural rate first rises, then falls below pre-AI levels, with inflation following. Financial-stability worries include cyber risk, which tilts towards attackers, and the investment boom itself: valuations are concentrated, spending exceeds cash flow, and circular financing among chipmakers, cloud firms and AI developers is opaque. An arms race risks over-investment, as in the canal, railway, electrification and dot-com episodes, and households now hold more equity, so a correction could hit consumption harder and spread globally. He does not say a bust is inevitable but urges caution. Benefits will depend on infrastructure, skills, competition, data governance and institutions; for central banks, the premium rises on measurement, judgment and cooperation.