Artificial intelligence has attracted significant corporate investment, but evidence of measurable financial returns outside the technology sector remains limited, according to Torsten Slok, chief economist at Apollo Global Management.

In a recent research note, Slok examined what he calls the S&P 493: the S&P 500 excluding Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. His analysis found that profit margins and revenue per worker appeared broadly flat, with no clear indication that AI adoption was improving productivity.

Slok concluded that, despite substantial investment and widespread enthusiasm surrounding the technology, companies outside the major technology firms had not demonstrated a measurable financial payoff.

The findings challenge the assumption that the rapid development of AI will automatically translate into stronger corporate earnings. While companies are investing in automation and AI-powered tools, the financial impact may be harder to establish than technological progress alone suggests.

The Gap Between AI Adoption and Business Results

One question raised by the analysis is whether companies outside the technology sector are simply lagging behind the firms developing and commercializing AI systems.

Slok expressed skepticism that broader corporate America will easily convert increasingly affordable AI capabilities into faster revenue growth and higher profit margins.

The distinction is important for investors evaluating whether current spending can support future earnings. AI tools may improve individual tasks or accelerate certain workflows, but those changes do not necessarily produce measurable improvements at the company level.

For financial performance to improve, productivity gains must ultimately influence costs, revenue generation or operating efficiency. The Apollo analysis suggests that such improvements have not yet become apparent in the aggregate financial indicators it examined for companies outside the largest technology firms.

However, the reported findings concern broad financial measures and do not establish that every non-technology company has failed to benefit from AI.

Why Business Judgment Still Matters

Slok argues that intelligence and information processing alone are insufficient to generate better business outcomes. He describes AI as a capable computational tool but emphasizes that commercial decisions also depend on judgment.

Factors such as accountability, trust, corporate culture, unwritten organizational rules, ethical trade-offs and fairness can influence reputational risk and ultimately affect revenue and profitability.

These considerations may help explain why improvements in AI capabilities do not necessarily produce immediate or uniform financial returns. Businesses must incorporate the technology into decisions and processes that involve human relationships, organizational responsibilities and competing priorities.

The argument shifts attention from the capabilities of AI systems themselves to the conditions required for those capabilities to improve business performance.

Implications for Corporate Investment

The findings raise questions about how companies should evaluate AI-related spending. Rather than treating adoption as an objective in itself, businesses and investors may need to focus more closely on measurable outcomes, including productivity, operating margins and revenue per employee.

For companies investing heavily in AI, the challenge is to demonstrate that new systems can improve financial performance after accounting for implementation costs and organizational changes.

The analysis does not establish whether broader financial benefits will emerge over time. It instead highlights the current gap between widespread investment in AI and the measurable improvements identified in the financial indicators examined.

What Investors Should Watch Next

Investors will be looking for clearer evidence that AI adoption is translating into stronger productivity and financial results beyond the technology sector. Changes in profit margins, revenue per employee and operating costs could help indicate whether companies are converting AI investment into sustainable economic benefits.

Until those improvements become more visible, the financial case for AI adoption across the wider corporate sector remains an important question for businesses allocating capital and investors assessing future earnings growth.