The World Can’t Afford to Get AI Wrong

IMF Blog, October 15, 2026

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Kristalina Georgieva wrote that AI is already having a profound impact on the global economy and that investment is flowing into AI on a scale that will likely exceed the vast sums that went into building the railroads, the electricity grid, and the internet.
The AI boom is described as a positive demand shock lifting growth in the short run, especially in the U.S. and Asian countries that supply hardware.
The real promise is a future positive supply shock that could significantly boost productivity and raise global growth; the growth boost "could be on the order of half a percentage point annually over the next decade."
Technological transformations "rarely happen overnight" and businesses, employees, and consumers must adapt to unlock productivity gains.

Much of the boom is being driven by massive investment in AI infrastructure such as data centers, with hyperscalers leading the race.
In the last two years, hyperscalers' share of investment-grade bond issuance "has increased more than tenfold—from less than 1 percent to 10 percent and growing."
The AI ecosystem is described as highly concentrated with circular dealmaking (hyperscalers investing in frontier-model labs, which buy data capacity from those same firms).
Potential risk scenarios identified:
- Big revenue or earnings disappointments by AI developers could undermine expectations and hit equity prices.
- Unsettling incidents involving frontier models or cyberattacks could dent confidence and raise financial stability risks.
- In a severe scenario, a market correction could cascade through the highly leveraged and circular AI ecosystem and, given sizable cross-border holdings of AI assets, "the losses could spread around the world."
Cybersecurity risks: AI accelerates vulnerability discovery, exploitation, and attack, compressing the attack-defense cycle to machine speed. A major attack affecting payments, trading, or access to deposits could cause immediate losses and undermine confidence; an operational disruption at a critical node could evolve into a broader confidence shock.

IMF research is cited that "roughly 40 percent of jobs globally are exposed to AI."
"In advanced economies, exposure rises to about 60 percent."
The article notes uncertainty about net employment effects: "It is still too early to predict the toll on employment—so far, there is no apparent impact on the job market, but the nature of work is changing, and this is likely to accelerate."
IMF research on Asia-Pacific found employer demand has "declined about 10 percent in highly AI-exposed occupations" even as demand grows for workers who can use AI.
New roles are emerging, such as prompt engineering and building AI agents.
Policy implications for labor markets:
- Equip people with cognitive, creative, and technical skills to use AI.
- Maintain traditional social safety nets such as unemployment insurance.
- Deploy active labor-market programs to upskill and reskill workers.
- Calibrate tax systems so they do not excessively favor or impede automation.
- Preserve labor-market flexibility so firms can recruit needed talent while supporting displaced workers.

Third: support workers and create opportunities.
- Acknowledge that AI will take over some tasks but displaced workers may move to new roles or firms, potentially benefiting from higher productivity.
- Policies should balance labor-market flexibility with support for displaced workers.
- Emphasize training young people in skills that empower them to use AI and expanding active labor-market programs.

The article recommends coordination among governments, AI companies, and other stakeholders given rapidly growing frontier-model capabilities and interconnectedness.
The IMF stated it "will continue to offer policy advice, capacity building and, when necessary, financial support within our core macroeconomic mandate."

The world is described as going through a technological transition that may force reconsideration of how to protect critical infrastructure, preserve financial stability, and how people work.
The author urges taking public concerns seriously while also recognizing AI's promise of a more productive world and calls to "embrace the challenge together, and learn as we go."