IESE Insight
How AI is depressing wages and job mobility
As generative AI grows more sophisticated, junior employees seem to suffer most.
As the use of generative artificial intelligence (GenAI) spreads, wages and worker mobility in the most AI-exposed industries are declining, especially among junior employees.
A working paper by IESE’s Mireia Giné and José Azar, together with Javier Sanz-Espín of Toulouse School of Management and the University of Navarra, looks at wage trends at all seniority levels from the launch of ChatGPT in 2022 through to 2026 and at whether employees in professions most vulnerable to AI adoption are leaving their current jobs.
The research draws on two sources of data on the U.S. labor market: Occupational Employment and Wage Statistics (OEWS) from the Bureau of Labor Statistics, and the workforce information platform Revelio Labs. It focuses on knowledge-intensive service sectors such as finance and insurance; real estate; information, professional, scientific and technical services; corporate management; and administrative support.
According to the OEWS data, wages in highly exposed sectors fell 4.9%, while the Revelio data showed that posted wages in highly exposed sectors were down 8.7% and starting wages for new hires were down 10.8%. The discrepancy in percentages is to be expected, since Revelio’s dataset of new job postings and starting wages reflects changes in the labor market more quickly than the OEWS, which is based on existing positions.
The wage decline was highest for low-seniority employees, across all age groups, whether they were young entrants into the workforce or longer-term employees who remained in lower-level positions. In the most-exposed sectors, wages declined approximately 7.5% for junior positions. For mid-level positions, salaries eased 3.2%, mostly for younger workers. For senior positions, compensation held steady.
The findings highlight one of the defining traits of large language models (LLMs): their ability to automate standardized cognitive and reasoning tasks such as drafting, summarizing, coding and basic analysis. In most workplaces, these tasks are disproportionately concentrated in low-seniority roles.
AI's impact went beyond wage levels, also reducing job mobility. In highly exposed industries, the number of people leaving their current employer declined by 3.0 percentage points, nearly all of which was due to a drop in finding work elsewhere (rather than remaining unemployed). This was the case for employees of all ages and seniority levels, suggesting that employees have fewer options elsewhere since the ChatGPT shock, and are more likely to stay put despite the falling wages.
How AI benefits senior leaders and managers
The low-seniority impact may be linked to the increasing autonomy of AI. Research by Enrique Ide and Eduard Talamás published in the Journal of Political Economy finds that as AI gains autonomy, the least knowledgeable workers are the most vulnerable to substitution by AI. Autonomous AI agents can potentially be given tasks that take hours, days or weeks to complete, and then can go off and do those tasks in the way a smart employee would.
At the other end of the experience ladder, senior employees always benefit from GenAI, the Ide and Talamás research finds. With autonomous AI, the most knowledgeable workers move into specialized problem-solving and use AI as an autonomous agent.
This is consistent with earlier research showing that demand for managers increased in companies that adopted AI systems. Managers play a crucial role in guiding AI’s integration into workflows and crafting strategies that leverage AI’s potential, while safeguarding against its limitations. Human judgment and strategic vision become even more valuable in an AI world.
All of this has implications not only for how tough the job market may be for new entrants, but also for how people just starting off in their careers will learn and advance. In most professions the grunt work of entry-level positions is a crucial phase of learning and training. Without that skills pipeline, it’s difficult to imagine how employees will develop the expertise needed to take on senior positions.
“One of the key challenges is how junior people learn,” says professor Sampsa Samila, director of IESE’s Artificial Intelligence and the Future of Management Initiative. In a context in which entry-level employees are either relying heavily on AI or potentially replaced by it, “Where do you get the experts?”
A version of this article is included in IESE Business School Insight online magazine No. 171 (Jan.-April 2026).
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