AI’s Impact Accelerates

Artificial intelligence has rapidly shifted from experimental technology to a foundational driver of business strategy. Companies across sectors are rethinking how they operate, invest and compete — and the results are becoming more evident. Despite the perception that adoption is still in early stages, new data show AI’s impact is both measurable and accelerating faster than expected.

A new Morgan Stanley survey of companies across the five sectors that the Research team deems most likely to experience significant near-term impacts from AI adoption reveals a powerful dual trend: meaningful productivity gains paired with noticeable workforce reductions. On average, these companies reported an 11.5% increase in net productivity and a 4% net decline in headcount over the past 12 months.

“Companies across industries are beginning to realize tangible gains through technology diffusion,” says Michelle Weaver, Morgan Stanley's U.S. Thematic and Equity Strategist. “This transformation is not just about the technology: It's also about how businesses evolve, reallocate capital and unlock new efficiencies.”

The survey of 935 corporate executives in the U.S., Germany, Japan and Australia focused on five sectors identified as the most exposed to AI adoption:

• consumer staples distribution & retail;
• real estate management & development;
• transportation;
• healthcare equipment & services; and
• automobiles & components.

Survey respondents said that AI adoption had led to elimination of 11% of jobs and an additional 12% were left unfilled. This is partially offset by 18% new hires, resulting in a 4% net job loss globally. That was an unexpected outcome as previous analysis indicated that AI would have a positive effect on employment growth.

“The magnitude of net job loss surprised us,” says Stephen Byrd, Morgan Stanley’s Global Head of Thematic and Sustainability Research. “Although the results likely represent the worst-case scenario for workforce impact, the data provide an early warning about the potential negative effects on employment as AI technology continues to rapidly improve.”

The net loss of positions indicated in the survey is not consistent across countries and sectors. In fact, U.S. companies reported a 2% net gain of jobs over the last 12 months, with more hiring due to AI than roles eliminated or not backfilled. The biggest negative impacts are expected for Europe.

Across sectors, automotive companies in the survey had the highest net loss of positions at 10%, whereas real estate saw a net gain of 1%.

Smaller companies—or those with fewer than 49 employees—have the highest staff retention and a 4% net gain in positions. Larger firms—with 501 to 1,000 employees—cut 15% of positions, the highest net loss.

The results also highlighted that early-career positions are the most at risk: The number of roles eliminated and not replaced was highest among early-career employees, or those with no previous experience. Workers with two to 10 years of experience showed the highest rates of being retrained or redeployed, a consistent pattern across sectors and regions.

Productivity Gains Are Nearly Universal

Across all countries, nearly half of the companies in the survey said their productivity increased 1% to 10% as a result of AI adoption; about a third noted an improvement of 11% to 20%; and 14% reported a jump of more than 20%. 

The biggest productivity gains were seen among Australian companies and the smallest in Germany. 

When ranked by sectors, AI-driven productivity gains were the highest in healthcare and lowest in real estate.

What This Means for Investors

1.  Prioritize industries with outsized potential: 

At full adoption levels, some sectors could achieve savings of more than 50% of their estimated 2026 consensus pre-tax earnings. Consumer staples distribution  and retail, real estate management and development, and transportation are the leaders, with potential benefits of more than 100% of earnings.

2.  Expect rising focus on bottom-line effects:

The main investor debate in 2026 should shift from pricing pressure concerns to how effectively companies translate AI-driven efficiencies into financial performance.

3.  Assess AI adoption across portfolios now:

Many investors may be underappreciating the impacts of AI adoption. If AI capabilities continue to improve at a non-linear rate, the magnitude of value creation could far exceed current expectations.

4.  Monitor companies well-positioned for workforce reskilling:

Survey respondents noted that 27% of employees had been retrained in the past 12 months. Staffing and education providers stand to benefit as organizations expand reskilling programs to meet evolving needs.