Artificial intelligence is often presented to Europe as a race to catch up. An IMF paper discussed by European Union finance ministers offers a more concrete measure: effective AI adoption could raise productivity by about one percentage point over the next five years. That is not an instant revolution, but it is a significant gain for mature economies.
The average conceals differences. Around sixty per cent of workers in advanced European economies perform tasks exposed to AI: some will be improved, others reduced or automated. Countries with more digitalised firms, available capital and stronger skills may benefit first. Without common policies, technology could widen regional divisions rather than reduce them.
Productivity does not arise from simply buying access to a model. It requires organised data, redesigned processes, training and the ability to measure whether work actually improves. Adding an assistant to an inefficient procedure may create more documents without creating more value. Useful adoption begins by deciding which choices to accelerate, which to verify and which not to delegate.
Distribution matters too. If AI lets a company produce more with fewer people, the gain may flow into investment, wages, shorter hours or profits alone. Technology does not choose among these destinations. Contracts, taxation, training and worker representation determine whether efficiency becomes shared prosperity or greater insecurity.
Energy is the second constraint. Data centres already consume a significant share of electricity in hubs such as Frankfurt, London, Amsterdam, Paris and Dublin. Disorderly expansion may strain grids and prices, making citizens pay part of the infrastructure cost. AI produces digital value through physical plants; industrial and energy policy must therefore be coordinated.
Christine Lagarde has added the question of dependence. Many of the models, chips and cloud services used in Europe belong to American or Asian groups. Being cut off from such a transversal technology would be an economic and public risk. Sovereignty does not mean building everything alone; it means possessing alternatives, expertise, bargaining power and enough infrastructure not to accept every external decision.
The single market is part of the answer. Innovative European companies still face fragmented rules, capital and national systems. A firm able to grow across the continent is better placed to finance research, retain talent and compete globally. Regulation can create trust, but it must be accompanied by access to compute and public demand that supports European solutions.
Benefits must be visible to citizens. Faster health services, clearer public administration, productive firms and less repetitive work are recognisable outcomes. An abstract rise in GDP is insufficient if people encounter only job losses, higher bills or opaque automated decisions. AI’s legitimacy will depend on the quality of everyday experience it creates.
Europe can gain productivity without losing balance, but not by introducing technology first and leaving balance to the market afterwards. Distribution, energy, training and autonomy must be designed alongside adoption. The aim is not to slow every innovation; it is to prevent speed from becoming a way to socialise costs and concentrate private benefits.