Dinner remarks by Philip R. Lane, Member of the Executive Board of the ECB, at The International AI Summit
Dublin, 13 October 2026
AI is a general purpose technology that can improve global living standards and the global knowledge frontier by expanding access to information and raising productivity.
That said, delivering the benefits from AI depends on a host of different actors playing their part in supporting the transformation of the economy. The list is long and includes: the developers of AI frontier models (whether proprietary or open-weight); the builders of the various layers of the AI infrastructure stack; the entrepreneurs designing the customised AI products that can best unlock productivity gains in individual sectors or in relation to specialised tasks; the research and development community that can accelerate scientific discovery and compress the time lag between invention and commercial application; the operators of the energy systems that must respond to this new source of energy demand; the financial system that is required to appropriately value AI-related assets and finance AI production and AI adoption, while also incorporating AI into its own processes; the education and training sectors that must re-design instruction, learning and evaluation methods; and, finally, the managers and workers that must implement revised business processes at the sector and firm levels to maximise the benefits of AI.
This transformation also poses many challenges for political systems, civic society, policymakers and regulators at national, European and global levels in relation to the ethical, fiscal, governance and legal issues posed by AI. How these political economy issues are resolved will have a major bearing on the AI transition path, including the appropriate speed of adjustment that balances the societal benefits, costs and risks posed by AI.
Given the scale and breadth of the AI challenge, a wide range of possible timelines and outcomes can be envisaged, depending on the rate of progress along each individual dimension. The uncertainty surrounding the impact of AI – in both the short term and the long term – is compounded by the interdependencies and complementarities across these different dimensions.
For instance, the rollout of rapid progress in AI capabilities can be held back by bottlenecks in some areas, slowing the overall pace of AI adoption. In particular, how firms and labour market institutions navigate the re-orientation of the workforce is a key issue, with some occupations facing the prospect of higher demand due to complementarities with AI and others facing lower demand due to the scope for substitution by AI.[1] The net impact on employment will also depend on the evolution of labour costs versus token prices.
The European Central Bank is closely monitoring and analysing the impact of AI on the euro area economy for several reasons.[2] First, the medium-term and longer-term positive impact of AI on the level of potential output and the trend growth rate of the economy has the potential to raise the speed limit of the economy, with direct implications for the financial system and monetary policy. For Europe, the potential for AI to offset the economic impact of the projected trend decline in the working-age population is especially valuable.
Second, more immediately, AI is already a primary factor driving current activity levels in the euro area. We see this in terms of a higher rate of business investment (firms are set to devote around 10 per cent of their total investment to AI this year), an expansion in digital services sectors and the high global demand for European components and capital goods that are part of the AI supply chain. In turn, this is supported by expansion in AI-related lending, which accounts for roughly one quarter of recent credit growth to firms.
In our surveys, we are also tracking the rate at which firms and workers are adopting AI. In our Survey on the Access to Finance of Enterprises for the fourth quarter of 2025, most firms reported that they were using AI: 64 per cent of firms said they were using it either experimentally or moderately, while only 7 per cent of firms reported that their use was “significant”.[3]
Our survey of households indicates that the proportion of workers using AI has doubled over the last two years, with 52 per cent now reporting that they use AI at work, compared with 26 per cent in 2024.[4] In the aggregate, workers are reporting significant time savings, but these are highly concentrated in specific sectors and specialised tasks such as coding.
Taken together, these surveys suggest that AI adoption in Europe is already significant and growing rapidly, even if it is too early to detect any material impact on aggregate productivity.
In relation to the labour market, we do not yet see a major change in aggregate employment trends but hiring plans are muted, which especially affects the prospects for new graduates. The potential for AI to replace some types of workers may also weaken the bargaining power of workers, moderating wage growth and reducing the labour share in total income. In our surveys, there is significant variation across industries, with workers in sectors benefiting from the AI infrastructure buildout currently more optimistic than those in knowledge-intensive sectors that face greater AI substitution risk.
At the same time, it is also important to appreciate that the quantitative scale of the European AI surge is of a different order to the AI boom in the United States or East Asia. Over the last two years, digital investment in the United States has grown twice as fast as in the euro area, while US workers spend two to three times as much of the working week using AI as workers in the largest euro area economies.[5] In terms of the AI frontier, the Stanford AI Index calculates that the United States and China have produced 59 and 35 notable AI models, respectively, while France and the United Kingdom have produced one each. In terms of AI computing capacity, the United States hosts 75 per cent of the global aggregate, whereas Europe hosts just 5 per cent. Although international trade in AI goods and services can do much to spread the benefits of AI around the world, asymmetrical AI capacity across countries may generate a host of economic and geopolitical issues.[6]
Third, it is likely that the global AI investment boom and expectations of a future global AI-driven productivity boost at longer-term horizons are plausibly contributing to the global increase in long-term interest rates.[7] Especially since the scale of the European AI boom is not of the same order as the global AI boom, the spillover to the euro area bond market means that the increase in long-term interest rates constitutes a material tightening of financial conditions for the euro area. This is a relevant factor for the ECB in determining the appropriate monetary policy stance.
Fourth, the high equity valuations of AI firms and the global surge in AI-related debt issuance carry macroeconomic and financial stability risks in the event of even a temporary reversal in the expected rate of AI advancement or a decline in investor sentiment.[8] Accordingly, the financial stability and banking supervision functions of the ECB are closely monitoring the evolution of AI-related financial risks and, in addition, the associated cyber risks.[9]
Fifth, the ECB has an extensive internal AI adoption agenda. Given that we are a knowledge-intensive organisation, AI has great potential to improve our analytical capacity and organisational efficiency. Over the last several years, I have been very impressed by the bottom-up initiatives of ECB staff to apply AI in a wide range of applications.[10]
In closing, Europe has much to gain by seizing the AI opportunity. The ECB is committed to making sure that the AI transformation in Europe is underpinned by price stability and financial stability.
In these remarks, I have highlighted that the aggregate impact of AI depends on a multi-dimensional transformation of the economy over an extended period. This is best achieved by recognising the collective interest shared by all sectors and policymakers in ensuring a sustainable AI transformation path. To this end, this AI summit provides an important opportunity to learn from each other and listen to a wide range of perspectives on AI.
