Morgan Stanley predicts a significant increase in employment across three AI-related sectors, despite current revenue not meeting expectations

The Changing Relationship Between AI, Revenue, and Workforce Growth

According to a recent analysis by Morgan Stanley, artificial intelligence is fundamentally altering the traditional link between increasing staff numbers and boosting revenue. While AI was expected to reduce the need for human workers, many business leaders still plan to expand their teams, even as the nature of work becomes more demanding. This highlights a new paradox: AI is intensifying workloads rather than simply automating them away.

AI’s Surprising Impact: Creating New Job Opportunities

Drawing insights from its annual Technology, Media & Telecom Conference in San Francisco, Morgan Stanley identified three key sectors where AI is actually fueling demand for employees, even as it automates other roles. The report comes at a time when many U.S. companies are signaling a shift—revenue is rising without a corresponding increase in headcount. Executives from firms like Snowflake and Shopify shared how AI allows them to achieve more with leaner teams. Yet, Morgan Stanley’s experts argue that the story is more complex, with certain segments of the labor market experiencing a surge in hiring thanks to AI.

“While some organizations have trimmed their workforce, most discussions at the TMT conference focused on how AI is transforming productivity and enabling growth without expanding staff,” the analysts noted.

AI’s Disruptive Effects: Job Losses and New Roles

Last month, the Deutsche Bank Research Institute posed a provocative question to AI itself: how many jobs will be lost? The response predicted 92 million positions could disappear, but also forecasted the creation of 170 million new roles, more than offsetting the losses. While Deutsche Bank’s analysts warned of a disruptive transition, Morgan Stanley believes this upheaval is already underway.

Skilled Trades: The Overlooked Shortage

Morgan Stanley highlights skilled trades as the most critical and underrecognized area of need. The rapid expansion of AI infrastructure—including data centers, electrical systems, and networking hardware—has created a huge demand for electricians, engineers, and construction professionals, far outstripping the available workforce.

Executives from CoreWeave pointed to a significant gap, noting a shortage of thousands of skilled workers needed to build data centers. Since acquiring these skills takes years, the imbalance is expected to persist. Nvidia CEO Jensen Huang echoed these concerns, especially regarding electrician shortages in states like Texas, which are slowing expansion efforts. CoreWeave emphasized that the real constraint isn’t just power supply—it’s having enough skilled people to install and maintain the necessary infrastructure.

AI Training and Workforce Reskilling: A Booming Sector

The second area experiencing rapid growth is employee training and reskilling. As businesses adapt roles to integrate AI tools, there’s a race to upskill workers. For example, Coursera reported that enrollments in AI-related courses soared to 15 per minute in 2025, up from 8 per minute the previous year—a dramatic increase.

More companies are now investing in workforce education, with CTOs and Chief Data Officers turning to platforms like Coursera to train employees in generative AI, data science, and software development. Docebo, a provider of learning management systems, described AI as a catalyst forcing every organization to retrain their teams, making scalable learning platforms essential.

AI Supervisors and Orchestrators: The Rise of New White-Collar Roles

The third emerging field isn’t a traditional trade or training job, but a new type of knowledge worker. As AI systems handle more routine tasks, companies are redefining white-collar positions to focus on overseeing, coordinating, and contextualizing AI operations.

C.H. Robinson, for instance, is preparing its staff for future roles that involve managing procedures and providing context for AI agents, rather than directly handling operations. Salesforce has even introduced a new metric—“Agentic Work Units”—to measure the combined productivity of AI agents and the humans supervising them. The consensus from Morgan Stanley’s conference: those who can guide and direct AI will be best positioned for success.

Two Diverging Labor Markets

These three growth sectors contrast with the challenges facing traditional white-collar jobs. For example, Snowflake eliminated around 200 roles in the fourth quarter due to AI-driven efficiencies, resulting in only a modest net increase in staff despite strong revenue growth. Shopify has also seen its workforce shrink for several consecutive quarters.

Morgan Stanley describes this as a story of diverging trends: AI is simultaneously reducing some jobs, elevating others, and generating entirely new categories of employment. The organizations and professionals most likely to thrive are those adapting to all three dynamics.

“Companies are increasingly relying on natural attrition to manage staffing, reallocating resources to technical talent, or shifting investment from labor to technology while keeping headcount stable,” Morgan Stanley concluded. This shift is also redefining job roles, moving workers toward positions that involve supervising and coordinating AI systems.

The transformation of the workforce is already underway—and accelerating.

Originally published on Fortune.com.