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AI could lift long-run productivity, but its near-term effects may include job disruption, higher demand for electricity and new financial risks. In remarks focused on Europe, IMF Managing Director Kristalina Georgieva argues that whether AI becomes a broadly shared source of growth depends on how leaders handle those transitions—not on adoption alone.
Why AI offers hope—and why the benefits are not guaranteed
Georgieva’s September 21, 2026 remarks, “Europe and the Global AI Race”, describe AI as a possible engine of productivity and growth over time. The IMF estimate she cites is that AI could eventually raise global annual potential growth by 0.1–0.8 percentage points. That is a projection of potential growth, not a measured increase already delivered.
The distinction between short and long time horizons matters. Building data centers and other AI infrastructure can raise investment and demand in the near term, adding to inflation pressure. If AI later helps businesses produce more with available resources, it could expand productive capacity. The eventual outcome depends on whether investment delivers, workers and firms adapt, and infrastructure can support wider use.
Growth alone does not ensure that gains reach workers or households broadly. Georgieva warns that AI could polarize work and hollow out middle-skill roles. The transition may leave some workers with new opportunities while others need to change occupations or acquire skills. Policy, training and social support affect how disruptive that shift becomes and whether people can participate in the gains.
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What the IMF says AI could mean for jobs
The IMF remarks say AI could affect up to 60% of jobs in advanced economies. “Affect” is not the same as eliminate: exposure can mean that tasks change, work is reorganized or productivity rises, as well as the possibility that particular roles shrink. The figure applies to jobs in advanced economies and should not be read as a forecast that 60% of those jobs will disappear.
The skills shift is already relevant to hiring: the IMF says about one in ten job vacancies in advanced economies asks for at least one new skill. For leaders, that points to the importance of training systems that can respond to changing occupational needs, alongside support for workers moving between roles.
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How AI investment could create financial risks
The same investment wave that may support future productivity can create vulnerabilities if expectations outrun results. The IMF highlights leverage, circular financing and cross-border financial links as channels through which an AI investment disappointment could turn into a broader market correction. These are risks to monitor, not a prediction that a crash is inevitable.
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For policymakers, the practical challenge is to support useful investment without overlooking how it is funded or how risks connect across companies and borders. Patient private risk capital can help startups pursue uncertain ideas; Georgieva’s remarks also leave room for selective public equity where market failures justify it. That is different from treating every AI investment as sound or promising public support without conditions.
Why electricity and infrastructure matter
AI expansion depends on physical infrastructure, especially electricity and data centers. The IMF says data centers account for about 3% of European power consumption and that AI-driven data-center demand is likely to triple by 2030. The first figure describes Europe; the second is a projection, not a measured increase.
Georgieva’s Europe-focused discussion points to grid connectivity and energy costs as constraints. If power is expensive or networks cannot connect new facilities, infrastructure plans may be harder to deliver. The remarks discuss improving energy connectivity and locating data centers where energy is cheaper as parts of the response.
Europe’s readiness and its adoption gap
The speech is about Europe’s position and policy choices, not a comprehensive account of what every world leader should do. The IMF says seven of the top ten countries in its AI preparedness index are European, while also identifying barriers to wider business adoption: financing constraints, regulatory burdens, high electricity prices and narrower adoption than in the United States. The remarks do not provide the index’s full methodology, so the ranking is best treated as the IMF’s stated comparison rather than a universal measure of readiness.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesThat combination—strong preparedness indicators alongside adoption barriers—helps explain the speech’s emphasis on competitiveness. Georgieva argues for maintaining AI safeguards while ensuring Europe has enough technological capacity to govern the technology and compete. In this framing, safeguards and innovation capacity are not opposing goals: rules work best when the region has the expertise and industry needed to implement them.
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What Georgieva urges European leaders to do
The remarks organize policy around finance, energy, business flexibility, labor markets and public-sector capacity. The recommendations are directed at Europe and should not be presented as a complete policy program for all countries.
- Finance: Encourage patient private risk capital for startups and consider public equity selectively when a market failure warrants it.
- Energy: Improve connectivity and address the cost and availability of power needed for AI infrastructure.
- Business flexibility: Pursue regulatory convergence and reduce burdens on businesses operating across borders.
- Labor markets: Invest in training and social support that help people navigate occupational transitions. Review tax systems as AI changes the balance of income between labor and capital.
- Public-sector capacity: Build digital public infrastructure and integrate AI into public services in ways that can also encourage private-sector adoption.
Together, these proposals address both the conditions for AI investment and the institutions needed to manage its consequences. They do not promise that growth will be immediate or evenly distributed; they set out choices intended to improve the odds.
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