AI Adoption in S&P 500 Firms

Yang Yu, Martin Fleming, Lucy Hampton, Christophe Combemale, Neil Thompson · arXiv · 9 Jul 2026

Where this sits in the debate

Will AI actually boost productivity and growth? · its finding goes against the claim (why studies differ)
Will AI destroy more jobs than it creates?
How fast will the impact arrive? · its finding goes against the claim (why studies differ)

Direction of the finding as read from the abstract by an AI model (AI-written).

Key takeaway AI-written

Using SEC 10-K filings — where misleading statements are legally prohibited — as a hype-resistant measure, the authors find 11% of S&P 500 firms had AI deeply integrated into business processes in 2025 (plus 10% using it in production/delivery), up more than fourfold from 5% in 2022, with tech firms accounting for two-thirds of deep adoption. Profitability follows a J-curve across adoption stages, but capex and productivity show no differences, feeding directly into the Solow-paradox debate: even among bellwether firms, deep AI integration has yet to show up in measured productivity.

The paper in three steps AI-written

Written by an AI agent from the paper's abstract, which is the primary source and is quoted below.

The question

How far have S&P 500 firms deeply integrated AI into their business processes between 2016 and 2025, and how does adoption relate to profitability, investment and productivity?

The approach

The authors measure enterprise-level AI adoption from SEC 10-K filings, where misleading statements are legally prohibited, distinguishing deep integration of AI in business processes from mere mentions, and relate adoption to firm outcomes.

The findings

In 2025, 11% of S&P 500 firms had AI deeply integrated into business processes and a further 10% used AI in producing goods or services, up from 5% in 2022. Technology firms account for two-thirds of deep adoption. Profitability follows a J-curve with adoption, but the authors see no differences in capex or productivity.

How to read it: observational. Analysis of real-world firm, worker, or market data — realistic settings; causal claims depend on the identification strategy.

Limitations and counterpoints AI-written

Adoption is inferred from what firms disclose in annual filings, and the sample covers only the largest US listed firms, so results may not carry over to smaller firms or other countries.

Abstract

The adoption of artificial intelligence (AI) by large enterprises is an important potential source of aggregate productivity improvement and labor market impact. We study AI adoption of S&P 500 firms over the period 2016 to 2025, estimating adoption at the enterprise level. While generative AI tools are useful for personal and professional applications, our focus is on the deep integration of AI in the business processes of large enterprises which are bellwethers for firm adoption more broadly. We develop a novel measure to assess deep AI adoption (and distinguish it from AI hype) that is based on SEC 10-K filings, where laws and regulations ``prohibit companies from making materially false or misleading statements." In 2025, 11% of S&P 500 enterprises had AI deeply integrated into their business processes, and a further 10% were using AI in the production of goods and delivery of services. AI adoption has more than quadrupled from 5% in 2022 with slowly accelerating adoption among non-technology firms but very aggressive adoption in the technology sector which accounts for two-thirds of deeply integrated enterprise adoption. Firm profitability shows a "J-curve" as firms move from no adoption to deep adoption, but we observe no differences in capex or productivity. Among technology firms, but not others, AI adoption is higher for firms with more employees and higher values of Tobin's q.

About this publication

Preprint. A preprint — posted publicly before or without journal peer review; findings may still be revised.

Published: 2026 (3 months ago)
Citations: Not recorded for this source

Citation counts come from OpenAlex; none are recorded for this source — absence of a count is not absence of citations.