The rapid expansion of artificial intelligence is creating new risks to financial stability, Bank for International Settlements head Pablo Hernandez de Cos said Thursday, with AI infrastructure spending now large enough to influence global economic conditions.
Speaking at a conference hosted by India's central bank, Hernandez de Cos said the BIS estimates the world's five largest technology firms will invest more than $1 trillion in AI between 2025 and 2026. Industry forecasts suggest global AI investment could grow from about $500 billion currently to as much as $4 trillion by 2030.
"The promise of AI is real," he said, while cautioning that its long-term impact would depend on policy choices, investment in skills and infrastructure, and how widely benefits are shared.
Opaque financing and market concentration
The AI boom is increasingly being financed through debt and private credit rather than corporate earnings, Hernandez de Cos said. Much of that funding remains "opaque and interconnected," which he said merits close scrutiny from regulators and central banks.
He also flagged lofty valuations and market concentration as potential vulnerabilities if corporate profits fall short of expectations. "I do not say that this is where the AI boom must lead," he said. "But the scale and speed of the current investment boom, and the weight of expected commercial returns, do warrant some caution." He drew parallels with past investment cycles, including the railway expansion era and the dotcom surge.
For finance professionals tracking these developments, understanding how AI investment flows through debt markets and private credit is becoming as important as monitoring equity valuations. The AI for Finance landscape now extends well beyond technology companies themselves.
Productivity gains and labor market shifts
Hernandez de Cos pointed to evidence that generative AI can significantly boost productivity. Studies have found gains of between 10% and 65% in specific tasks, particularly in coding, consulting and professional writing. Current estimates suggest AI could raise total factor productivity growth by about half a percentage point per year, depending on adoption pace and how effectively labor and capital are reallocated.
Advanced economies are expected to benefit first because of their larger service sectors and greater readiness to deploy AI. Emerging economies face more varied prospects, though Hernandez de Cos said India had a "genuine opportunity" to narrow the gap, helped by its digital public infrastructure.
Job losses so far remain limited, but signs are emerging in customer service, programming and administrative roles. Hernandez de Cos said retraining and reskilling are becoming increasingly important as AI replaces routine cognitive tasks.
Trade flows and supply chain effects
AI is also reshaping global trade. Economies closely tied to the technology supply chain - including South Korea, Singapore, Malaysia and Taiwan - have benefited from stronger export prices for AI chips and equipment. For central banks, this complicates economic interpretation because AI affects demand, supply and financial markets simultaneously.
Hernandez de Cos said AI does not change monetary policy mandates, but it makes economies harder to read. The scale of capital expenditure concentrated in a handful of firms means corporate earnings disappointments could transmit quickly through credit markets.
Why this matters for finance professionals
The BIS warning signals that AI-related credit exposure is becoming a legitimate risk-management concern, not just a technology story. Finance teams should track how much of their counterparties' AI spending relies on debt and private credit rather than operating cash flow. For CFOs and senior finance leaders, the productivity data - task-level gains of 10% to 65% - offers a concrete benchmark for evaluating AI investments in their own organizations. The AI Learning Path for CFOs addresses how finance leaders can assess these trade-offs between productivity gains and concentration risk.
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