The adoption of AI is “reshaping the euro area economy“, by supporting investment, trade and credit growth, European Central Bank executive board member Philip Lane has told an event in the US.
Speaking at the Federal Reserve Bank of San Francisco Economic Research Symposium on AI and the Economy, which took place on 30 October, Lane said expenditure on AI adoption was providing a “significant stimulus” to the euro area economy.
‘European productivity growth’
“Although the development of frontier AI models is primarily taking place in the United States and China, the adoption of AI will be a key determinant of European productivity growth in the coming years,” Lane commented.
“In addition, European firms are part of the global AI supply chain, while European investors are contributing to the funding of the global buildout of AI infrastructure through equity and debt markets and the banking system.”
According to data cited by Lane, digital investment in the euro area has increased by 73% in real terms since 2014, rising from 2.3% to an estimated 3.3% of GDP by the end of the first half of 2026. To date, much of this investment has been in intangible assets, including software and databases, rather than data centres.
A recent survey by the ECB found that AI had added around 10% to companies’ capital expenditure plans for 2026. Demand linked to AI has also supported activity in technology equipment and information and communication services.
AI usage
Elsewhere, ECB’s Survey on the Access to Finance of Enterprises (SAFE) for the fourth quarter of 2025 found that around two thirds (64%) of companies reported using AI either experimentally or moderately, although only 7% described their use as significant. Improving business processes was the main reason for adoption, cited by 62% of firms, while 23% referred to innovation and product development.
Among workers, the proportion using AI in their jobs has doubled over two years, from 26% in 2024 to 52% in 2026. The median worker using AI reported saving three hours per week, equivalent to around 7.7% of median working time.
“However, the distribution is highly skewed: most users enjoy only moderate time savings, while a small number report very high efficiency gains,” Lane added. “Generating or debugging code yields the largest gains, at six hours per week, although only around 15 per cent of workers use AI for this purpose. A similar pattern emerges for data analysis, automation of routine tasks and creating audio or visual content.
“By contrast, research, information gathering, writing and text editing are among the most frequently cited uses. Yet time savings reported for these tasks are considerably lower than for more technical tasks such as coding.”
Increased adoption
However, adoption remains uneven. Around 41% of workers said they were not interested in using AI, while approximately half of companies planning AI investment over the next year expected to provide employee training.
“When asked what would encourage them to adopt AI, around half of all workers point to better training on using AI tools and a better understanding of the usefulness of AI,” said Lane. “Employers appear to be responding to some of these needs. About half of firms plan to invest in AI training over the next 12 months, directly addressing the barrier most frequently cited by workers.
“Conversely, this means that around half of firms are not investing in AI training – this is possibly also affected by one-third of managers not being interested enough in AI.” Read more here.
