AI adopters gain margin edge in Morgan Stanley stock screen

AI adopters are drawing new investor attention as Morgan Stanley links enterprise use of the technology to wider profit margins.

A strategy team led by Michael Wilson said companies with AI embedded in the investment case and at least stable pricing power are seeing the clearest improvement in margin assumptions. The strategists estimate adoption could contribute roughly 100 basis points to net margins by 2027.

“The outlook for AI adopters is becoming increasingly compelling,” Wilson wrote in a note. He added that the point matters because several sectors often treated as exposed to automation risk now rank well in the screen, including transports, software and services, and professional services.

Wilson screens margin winners

The Morgan Stanley work shifts the market debate from who builds AI infrastructure to who can turn AI tools into operating leverage. That distinction has grown more important as investors question whether the largest technology groups are spending too aggressively on data centers, chips and cloud capacity.

The strategy team named Halliburton Co., Bank of America Corp., CVS Health Corp. and NextEra Energy Inc. as stocks that screen as major beneficiaries of AI adoption. Alphabet Inc., Meta Platforms Inc. and Nvidia Corp., which were central to the first stage of the AI equity rally, also remain strong in Wilson’s framework.

Cost savings beat capex anxiety

The market has become more selective about AI exposure this year. A Bank of America Corp. basket tracking AI adopters has outpaced the hyperscaler group, while semiconductor-linked shares have faced pressure from concerns that valuations already price in too much future growth.

The timing is sensitive because second-quarter earnings are putting profitability under close inspection. Companies representing about one-third of the S&P 500’s market value are expected to report this week, making the period one of the busiest stretches of the season.

Wilson said the adoption story is gaining force because companies are beginning to show measurable benefits rather than pilot projects. Roughly 40% of firms in the adopter group have cited at least one quantifiable gain during the current earnings season, he said, versus 21% in the comparable period last year.

Productivity claims face earnings tests

Across the past year, companies in the analysis reported average net productivity improvement of nearly 10%, according to Wilson. The strongest cited areas were software development, customer service, finance and operations, where AI can automate routine work or shorten production cycles.

That evidence gives investors a cleaner test than broad AI narratives. If companies can show lower unit costs, faster workflows or better customer handling without sacrificing revenue quality, the margin argument becomes easier to defend.

The risk is that adoption benefits remain uneven across sectors. A company with weak pricing power may see efficiency gains absorbed by competition, wage pressure or technology costs, while a firm with stronger customer retention may convert the same tools into durable margin expansion.

Adoption thesis splits two paths

If Wilson’s margin thesis holds, the global equity story tilts toward productivity rather than capital spending. For companies such as Halliburton, Bank of America, CVS and NextEra, documented savings could support earnings growth even if revenue growth cools; for the wider market, software, professional services and transport operators could attract more capital as adopters rather than AI victims.

If the savings arrive more slowly, the mechanism runs the other way. Global investors may demand higher proof before paying for AI exposure, large technology companies could face sharper questions about infrastructure budgets, and chip and cloud suppliers may carry more valuation risk until end users show clearer returns.

The next test is earnings language, not just earnings numbers. Investors will be watching whether companies attach AI to specific margin gains, productivity metrics or cost lines, because vague adoption claims are becoming less useful in a market now asking who actually earns more from the technology.