Companies have invested heavily in artificial intelligence, but Apollo economist Torsten Slok says the financial results have not appeared across most large corporations outside the technology sector. His analysis finds no evidence that AI has improved profit margins or revenue per worker among the S&P 493.
What the S&P 493 measure shows
Slok uses the term S&P 493 for the S&P 500 after excluding Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla. In that group, profit margins and revenue per worker appear flat, according to a note he recently published as chief economist at Apollo Global Management.
The measures offer a way to look for broad business effects beyond the technology companies most closely associated with AI. Slok’s conclusion is that, so far, the financial indicators he examined do not show a payoff for this set of large non-tech corporations.
That is a specific finding about these companies and measures. It does not establish that no company has benefited in other ways, or that future gains are impossible. It does, however, challenge the expectation that large AI investments should already be producing visible improvements in corporate financial performance.
Why adoption may not translate into stronger results
One possible explanation is that companies outside tech are simply behind the technology giants in adopting AI. Slok is skeptical that catching up will be enough. He argues it may be difficult for corporate America to turn increasingly cheap intelligence into faster revenue growth and higher profit margins.
The distinction is between having access to a tool and changing business outcomes. AI may help with calculations, but a company’s earnings and growth also depend on decisions about customers, workers, risks and priorities. Those decisions require more than producing an answer quickly.
Slok puts judgment at the center of the issue. In his view, business depends on responsibilities and relationships that are difficult to reduce to a calculation. If AI use does not help companies make better decisions or serve customers more effectively, the technology may not show up in the measures investors care about.
Judgment, trust and accountability remain central
Slok says AI does not understand accountability, trust, culture, unwritten rules, ethical trade-offs or fairness. Those factors, he argues, shape reputational risk and ultimately influence revenue growth and profit margins.
That observation points to a challenge for companies weighing AI investments: productivity tools operate inside organizations with existing norms and obligations. A system can provide information or perform a task, but people and institutions still have to decide how to use its output and take responsibility for the consequences.
As a result, deploying AI does not automatically mean that a company has improved the way it works. The financial payoff may depend on whether the technology supports sound judgment within a business, rather than simply making intelligence cheaper or more available.
The payoff question remains open
Slok’s assessment adds to recent studies that have also found AI has yet to deliver significant productivity gains. Together, these findings suggest that widespread interest and investment have not yet produced clear, broad improvements in the business measures discussed in the article.
For companies, the question is not only whether AI is being used, but whether that use changes revenue, productivity or margins. Slok’s analysis says the evidence in the S&P 493 does not yet show such a change. Whether firms can convert AI capabilities into stronger financial performance remains unsettled.