Artificial intelligence (AI) has been the dominant theme in global financial markets since late 2022, with equities in the infrastructure buildout. However, AI’s influence on markets extends beyond a narrow set of infrastructure providers and stretches further back in time. Many firms integrate AI into their businesses, either by developing AI-enhanced products or by adopting AI-enabled processes that improve productivity.[1] This box therefore introduces a new firm-level measure of AI exposure derived from AI-related discussions in earnings call transcripts. It uses this measure to examine how the AI exposure of European firms is reflected in their equity returns and corporate bond spreads.[2]

Chart A

Performance of the STOXX Europe 600 and S&P 500 and their technology subsectors

Sources: LSEG and European Central Bank (ECB) calculations.Notes: The chart shows the levels of European and US benchmark equity indices and their technology subsectors over time. The latest observations are for 15 September 2026.

Firms are classified as AI-exposed when their earnings calls link AI to infrastructure provision, product development, or improvements in business processes and productivity.[3] These criteria are applied across STOXX Europe 600 constituents, identifying not only firms that supply AI technology but also firms across all sectors that embed AI in their products and operations. The approach also captures the evolving nature of AI: as the technology matures and diffuses across sectors, firms’ disclosures shift accordingly, allowing a measure grounded in contemporaneous statements to track this evolution. This is valuable given the reliance of analysis on timely identification of AI-related news. Accordingly, AI exposure is measured quarterly from 2017 onwards and treated as time-varying, allowing the analysis to control for firm heterogeneity and sector-specific time variation.[4]

The share of AI-exposed firms has risen markedly since 2022, with AI predominantly mentioned in earnings calls as a source of product innovation and growth (Chart B). 75% of earnings calls mentioning AI refer to product innovation or growth opportunities from an AI-enhanced product offering, while 50% discuss AI-related productivity gains, with some mentioning both. There is clear heterogeneity across sectors and over time: IT firms mentioned AI-related product innovation as far back as 2017, whereas firms in other sectors mainly started to refer to productivity improvements resulting from AI after the launch of ChatGPT in late 2022. This is consistent with the findings of the ECB’s Survey on the Access to Finance of Enterprises in the euro area in June and December 2025, which show more innovation-oriented cases of AI use in the IT sector and greater emphasis on cost reduction in manufacturing, construction, trade and other services.[5]

Chart B

Share of AI-exposed STOXX Europe 600 firms and breakdown by AI exposure type

Sources: LSEG and ECB calculations.Notes: The sample includes all STOXX Europe 600 firms and spans from the first quarter of 2017 to the second quarter of 2026. Panel a): quarterly share of earnings calls in which AI is mentioned (left-hand side) and breakdown of earnings calls mentioning AI by exposure type over the sample period (right-hand-side). Panel b): annual share of firms in each Global Industry Classification Standard sector mentioning innovation exposure (left-hand side) and productivity exposure (right-hand side). The 2026 annual share is approximated using the shares for the first and second quarters. The latest observations are for the second quarter of 2026.

Whether AI exposure raises or lowers firms’ financing costs is

Sources: LSEG and ECB calculations.Notes: Panel a): distribution of annual equity returns, weighted by end-of-year market value. Panel b): distribution of annual price/earnings ratios, weighted by end-of-year market value. The latest observations are for the second quarter of 2026.

Non-financial corporate bond markets exhibit a broadly similar pattern to equity markets (Chart D). Panel regressions using quarterly option-adjusted spreads over 2019-26, with bond and issuer-specific controls, show that AI exposure corresponds to spreads that are around 5 basis points tighter – a modest but robust link between AI exposure and a lower market-implied cost of debt.[8] This again aligns with descriptive patterns in the data. AI-exposed issuers consistently exhibit lower spreads than non-exposed issuers, with both the median and interquartile range shifted downward across most years (Chart D, panel a). Exposed firms have also issued a larger share of bonds with maturities exceeding ten years (Chart D, panel b), whereas issuance by non-exposed firms is more concentrated at intermediate maturities. This combination points to more favourable financing conditions, since longer maturities would typically command higher, not lower, spreads.[9]