An analysis by Goldman Sachs highlights that increased artificial intelligence investments by S&P 500 companies have not yet translated into significant earnings growth, contrasting sharply with strong gains observed in AI infrastructure sectors.
- Only 2% of S&P 500 firms cite AI effects in Q2 earnings.
- AI infrastructure providers’ earnings surged by 54%.
- AI spending per employee more than doubled for top companies in 2026.
Market signal
Goldman Sachs’ recent analysis reveals a disconnect between corporate AI expenditure and immediate earnings impact within the S&P 500. Just 2% of companies explicitly quantified AI-driven productivity gains in their second-quarter reports, with 11% of those showing modest improvement in areas like software coding and customer support. Median earnings growth was 17% for these companies, only slightly above the 14% median among companies not reporting AI effects.
Meanwhile, firms supplying AI infrastructure—such as semiconductor manufacturers and cloud computing providers—are driving clear revenue and profit growth, with earnings soaring 54% in the sector. This highlights a current market preference for players enabling AI adoption rather than early corporate adopters who have yet to see widespread financial returns.
Operator impact
For operators in payments and fintech markets, the slow earnings translation of AI investments underscores the need for measured expectations around ROI timelines. While AI initiatives often improve specific workflows, such as coding efficiency or customer support automation, these gains have yet to substantially boost overall financial performance. The rise in AI spending per worker, from $5 to $12 median monthly and $240 to $650 among the top 10% of firms this year, signals intensified commitment but also suggests that broad-scale integration remains a work in progress.
Executives should prioritize identifying targeted AI projects with demonstrable short-term value while maintaining longer-term horizons for company-wide integration. CFO surveys indicate growing confidence in returns within one to two years, yet also anticipate that complete AI embedding across organizations will take over six years, doubling from previous projections.
What to watch next
Market watchers should monitor quarterly earnings disclosures for increased visibility of AI-driven results, as spending trends point towards growing implementation and scaling. The rising AI investment per employee and the improving CFO outlook suggest that clearer financial impacts may emerge over upcoming quarters. Additionally, the continuing strength of AI infrastructure providers implies sustained demand for enabling technologies, which could shape vendor strategies and partnerships.
Operators and technology buyers should also track evolving benchmarks for AI productivity and ROI as companies transition from pilot projects to comprehensive adoption. Understanding how AI integration timelines and returns vary by sector will be critical for planning capital allocations and technology roadmaps in the payments and fintech industry.