Goldman Sachs strategists have identified companies poised to significantly benefit from future AI-driven productivity gains, even as enterprise-level impacts are still developing. Their analysis, combining labor intensity and AI sensitivity, points to potential beneficiaries in the Russell 1000, including CoStar Group, Dollar Tree, and eBay, with clearer earnings impacts anticipated soon. While the AI boom has been infrastructure-focused, early application successes like Doximity underscore the substantial profit potential.
The long-term success of the artificial intelligence revolution ultimately depends on tangible productivity enhancements stemming from automation, which will translate substantial investments in computing power into robust corporate profits. While these enterprise-level gains have not yet fully materialized, as the AI buildout remains primarily in its foundational infrastructure phase, strategists at Goldman Sachs have developed a framework to identify companies best positioned to capitalize on impending AI-driven productivity increases.
Their methodology involves assessing a company's wage bill exposure to AI automation and comparing it against its labor costs as a percentage of sales. This analysis, which combines labor intensity with AI sensitivity, has generated a list of potential productivity beneficiaries within the Russell 1000 index. "The recent acceleration in enterprise AI spending suggests that the earnings impact of AI adoption should become clearer in coming quarters," noted Ben Snider, chief U.S. equity strategist at Goldman, in a recent client research note.
Goldman's curated list includes prominent names such as real estate data firm CoStar Group, discount consumer retailer Dollar Tree, and e-commerce giant eBay. Key commercial sectors exhibiting high labor intensity and significant AI sensitivity span software, professional services, finance, and biotech.
Despite the AI boom being nearly four years old since the launch of ChatGPT in November 2022, Goldman strategists emphasize that the focus has largely been on hardware and infrastructure capacity rather than widespread application-level software implementation. Snider elaborated, "Investors have rewarded companies involved in the AI infrastructure boom due to the large and visible near-term earnings impact of that spending. In contrast … investors want to avoid speculating about which companies will be most effective at implementing AI and where long-term profit gains will accrue."
However, recent weeks have seen notable exceptions to this cautious investor sentiment, with unexpected productivity gains emerging. For instance, shares of medical platform Doximity surged after CEO Jeffrey Tangney revealed that the company’s AI search product is generating revenues-per-search at a rate ten times its operational cost.
Looking ahead, a 2023 Goldman Sachs paper projected that AI could boost productivity growth by 1.5 percentage points over the subsequent decade. Consultancy McKinsey offered even higher estimates, suggesting gains of up to 3.4 percentage points through 2040. In contrast, researchers at MIT presented more conservative figures, estimating productivity increases of 0.53% through 2034. The MIT researchers also cautioned that a potential consolidation of AI tools among a few dominant companies could hinder broader productivity enhancements. "If generative AI tools become monopolized in the hands of a few companies, this might further slow down their adoption by small and medium-sized firms," stated MIT economist Daron Acemoglu in 2024, warning that "The true numbers could be much smaller."
