Indeed Chief Economist Says AI-Exposed Sectors See Surging Job Demand and Wage Growth

Industries most exposed to artificial intelligence are seeing the strongest growth in job demand, according to Svenja Gudell, chief economist at Indeed. Speaking at Fortune's Workplace Innovation Summit, Gudell directly challenged prevailing narratives about AI-driven mass unemployment. The sectors facing the greatest AI disruption, including software development and financial services, are not shedding workers but actively expanding their workforces.

This pattern runs counter to widespread predictions that AI would rapidly automate away entire categories of knowledge work. Gudell's data suggests a more complex dynamic where technological exposure correlates with labor market expansion rather than contraction. The implication is stark: being in AI's crosshairs may signal job security, not obsolescence.

Gudell argues business leaders are getting both the speed and severity of AI's labor impact wrong. "I think we're overestimating the speed at which we're going to see this transformation," she told executives in Atlanta. "I think we're underestimating the long-term impact it will have." This dual miscalculation carries significant strategic risk.

Companies preparing for rapid workforce displacement may be underinvesting in the deeper structural changes AI will eventually demand. The gradual nature of current transformation masks a cumulative effect that could prove more disruptive than sudden replacement. Organizations that treat AI as a slow-burning fuse rather than an imminent explosion may still find themselves unprepared when the full consequences materialize.

Research from MIT Sloan supports Gudell's assessment with granular data on how AI actually penetrates workplaces. A study tracking AI adoption from 2010 to 2023 found that when AI handles most tasks within a job, that role's share of company employment drops by approximately 14%. But when AI affects only some tasks within a role, employment often grows as workers shift to complementary activities.

This task-level disruption pattern explains why wholesale job elimination remains rare. Most positions experience gradual transformation rather than sudden disappearance. The research indicates companies seeing substantial productivity gains from AI typically translate that growth into expanded hiring rather than reduced headcount. The mechanism resembles previous technology waves where automation of routine components allowed workers to tackle higher-value work.

Gudell identified a developing "wage premium" in AI-exposed roles, suggesting the market is rewarding skills that interface directly with emerging technology. This premium structure indicates employers are competing for talent capable of operating alongside AI systems, not just surviving them. The compensation dynamic reflects genuine scarcity rather than speculative bubble behavior.

The wage pattern also reveals something about how AI integrates into production. If employers simply wanted to replace workers with cheaper automation, they would not bid up salaries. Instead, the premium suggests AI-augmented workers produce meaningfully more value than either humans or machines alone. This complementarity between human judgment and machine capability creates economic returns that flow partly to labor.

The broader economic environment amplifies these dynamics. Business Insider reports labor supply is tightening as workforces age globally, creating structural pressure on employers to retain and attract workers. This demographic constraint means AI arrives at a moment when companies already face recruitment challenges, reducing their appetite for mass displacement even where technically feasible.

Skill requirements are simultaneously shifting, creating transition costs that favor retention over replacement. Organizations investing in worker adaptation alongside AI deployment appear better positioned competitively than those pursuing pure substitution strategies. The aging workforce dynamic adds urgency to Gudell's argument about gradual transformation, older workers may require more substantial reskilling support to remain productive as their roles evolve.

A complicating factor emerged from Bureau of Labor Statistics data showing the U.S. economy created nearly 1 million fewer jobs than previously estimated, with technology-linked sectors showing the largest downward revisions. Some economists interpreted this as evidence AI is automating tech jobs specifically. Bill Adams, chief economist at Comerica Bank, noted the revision showed "the economy entered 2025 with less momentum than previously understood."

Yet this dataset sits uneasily with Gudell's findings of growing demand in AI-exposed sectors. The discrepancy may reflect timing differences, measurement challenges in rapidly evolving occupations, or sectoral variation within broad tech categories. Software development and IT services may diverge from other technology-adjacent fields in their AI exposure patterns. The BLS revision caution against overinterpreting any single labor market indicator in a period of unusual structural change.

The converging evidence suggests a workplace future defined by task evolution rather than job extinction. Workers in AI-exposed fields face changing skill demands but not obsolescence. The imperative is adaptability, both for individuals navigating role transformations and organizations restructuring work processes.

Gudell's framework implies a specific action agenda: identify which tasks within roles are most susceptible to AI handling, develop adjacent capabilities that leverage human comparative advantage, and negotiate compensation that reflects the emerging productivity premium. For employers, the lesson is that workforce investment and AI deployment are complements, not substitutes. Companies treating AI as a labor replacement strategy risk missing the productivity gains that come from human-machine collaboration, and finding themselves unable to hire the talent needed to implement AI effectively in the first place.