Morgan Stanley: AI Is Creating a Surge in Demand for Skilled Trades, Even as White-Collar Jobs Erode
The bank's post-conference research identifies electricians, construction workers, and AI trainers as the fastest-growing job categories in the AI economy, despite net workforce reductions in knowledge work.
As Morgan Stanley's Technology, Media and Telecom Conference concluded in San Francisco, the bank's research team published analysis identifying three specific sectors of the labor market experiencing AI-driven job growth, even as the technology eliminates positions in adjacent areas. The findings challenge a binary narrative around AI and employment, presenting a more segmented picture of winners and losers that does not map cleanly onto traditional distinctions between white-collar and blue-collar work.
The most urgent category of growth, according to Morgan Stanley, is skilled trades. The unprecedented scale of AI data center construction — spanning physical facilities, power delivery systems, and networking equipment — is driving demand for electricians, electrical engineers, and construction workers that 'far exceeds supply.' The buildout is creating a structural labor shortage in physical trades even as it displaces white-collar knowledge workers whose tasks are more directly replicable by AI systems.
The second growth area is workforce education and reskilling services. As companies restructure roles around AI tools, demand for training has surged.
Coursera reported that AI-content enrollments reached 15 per minute in 2025, up from 8 per minute in 2024, nearly doubling in a single year. Corporate spending on upskilling is accelerating as enterprises recognize that the employees most likely to thrive alongside AI are those who can direct and supervise it rather than simply use it.
The third category is AI-adjacent technical roles — prompt engineers, AI trainers, model evaluators, and the humans who supervise and contextualize AI agent behavior. C.H.
Robinson told conference attendees that future jobs will involve managing standard operating procedures and providing context for AI agents rather than running operations directly, a formulation that captures how human roles are being redefined rather than eliminated in some sectors.
Morgan Stanley's survey data remains sobering: a 4 percent average net workforce reduction across 1,000 executives in five countries, directly attributed to AI adoption, was recorded over the prior 12 months, with the pace accelerating. Snowflake cut roughly 200 positions tied to AI efficiencies while adding only 37 workers net despite accelerating revenue growth to 30 percent.
The bank's modeling predicts a K-shaped economic outcome, with high-income households benefiting from AI-driven portfolio gains while middle-income workers face the most direct exposure to automation.
Read the original reporting at Fortune.
