Artificial intelligence (AI) is no longer merely a technological story. It is becoming a macrofinancial one. The latest Annual Economic Report of the Bank for International Settlements (BIS) argues that AI has entered an investment phase comparable with earlier technology booms, with characteristics that deserve close policy attention. The concern is not that AI is overhyped. It is that the way the AI revolution is being financed could itself become a source of financial vulnerability. In this regard, the BIS identifies three trends. First, AI investment is becoming highly concentrated. Building frontier AI models requires enormous expenditure on semiconductors, data centres, cloud infrastructure, and electricity. Unsurprisingly, a handful of tech giants dominates almost every layer of the AI ecosystem. Such concentration raises familiar concerns about market power, with dependence on a small set of firms and infrastructure providers.
Second, the financing of AI investment is changing. According to the BIS, companies are relying less on retained earnings and increasingly on debt to fund capital expenditure. Credit can accelerate innovation, but it also amplifies risk. If projected revenues fail to materialise or valuations correct sharply, leveraged balance sheets could transmit stress to lenders and financial markets. The lesson from previous technology cycles is not that innovation inevitably ends in bubbles, but exuberant financing can leave lasting scars when expectations outrun commercial reality. Third, AI’s economic gains are likely to be unevenly distributed. Early evidence points to productivity improvement, particularly in knowledge-intensive sectors. But the biggest beneficiaries are likely to be firms with proprietary data and access to computing infrastructure.
These warnings matter even for countries that are not yet at the centre of the AI investment boom. India today accounts for only a small share of global spending on AI infrastructure. The overwhelming bulk of the AI capital expenditure is being undertaken by a few technology companies based in the United States. India has made progress in building digital public infrastructure and expanding data-centre capacity, but investment in advanced chips, hyperscale computing, and foundation models remains modest by comparison. However, this does not insulate the economy from global financial risks. India depends on global capital flows for investment. A sharp correction in richly valued AI-linked stocks and tighter global credit conditions could quickly spill over into emerging markets through reduced capital flows, weaker investment sentiment, and tighter financial conditions. The experience of the dotcom bust and the global financial crisis shows that financial contagion rarely respects national technological boundaries.
For India, the policy challenge, therefore, is at two levels. The country must continue expanding digital infrastructure, encouraging AI adoption, and creating conditions for domestic innovation so that it is not left behind as AI reshapes global production. At the same time, policymakers must recognise that AI has become a macrofinancial phenomenon. They should be prepared to respond to a sharp correction in global stock markets and potential stress in credit markets, which could result in a sharp decline or reversal in capital flows, creating risks to financial stability and currency markets.