Executives fill conference rooms with bold predictions. AI will upend hiring. It will slash headcounts. It will rewrite the rules of work within months. Svenja Gudell hears these claims often. As chief economist at Indeed, she pushes back.
“I think we’re overestimating the speed at which we’re going to see this transformation,” Gudell told executives at Fortune’s Workplace Innovation Summit on May 19, 2026. “I think we’re underestimating the long-term impact it will have.”
Her message lands with force. Data from Indeed’s platforms and external sources reveal a labor market in transition. But not the breakneck one many boardrooms imagine. Adoption remains uneven. Large firms drive most activity. Small ones lag far behind. And while AI touches tasks across roles, full replacement stays distant.
Consider the numbers. As of April 2026, just over 5% of job postings on Indeed mention AI, up modestly from earlier readings. Only 5.7% of U.S. firms posted at least one AI-related job in late 2025, concentrated heavily among the biggest players. Nearly 90% of those AI-related postings came from 1% of companies. The largest firms show 49.9% adoption. The smallest third? Just 1.3%. A WSJ partner report featuring Gudell adds that U.S. Census Bureau data puts AI integration into regular business processes at only 17% of companies. Ninety-five percent of firms have zero AI-related postings.
Reality Check on AI Hype
These figures paint a picture of early days. Gudell stresses the point. AI will change how work gets done. Not tomorrow. Not the day after. But over months and years ahead. Companies need data now to prepare. They must start building the foundations today.
Her caution finds echoes in fresh analysis. A recent BCG report from April 2026 estimates 50% to 55% of U.S. jobs could be reshaped by AI over the next two to three years. Yet only 10% to 15% face outright vulnerability to elimination once demand expansion is factored in. Reshaping dominates. Elimination stays limited. And new demand for skills emerges alongside.
Indeed’s own 2025 AI at Work report, referenced by Gudell at the summit, breaks it down further. Twenty-six percent of jobs could be highly transformed by generative AI. Another 54% moderately so. Less than 1% of work skills can be performed by AI alone. Every job feels the touch. None disappears completely. “All jobs touched by AI but none completely done by AI yet,” she explained in related remarks covered by Fortune.
But here the story turns. Sectors most exposed to AI post the strongest demand growth. Software development offers a clear case. Job postings in that field rose 14% year-over-year in April 2026. More than 47% of them mention AI. AI-related postings overall jumped 130% in the same period. “The sectors that are most exposed to AI right now are seeing the most growth in terms of demand for those jobs,” Gudell said. AI software developers enjoy a wage premium. Their skills command more.
And. This pattern challenges the pure displacement narrative. AI creates roles even as it alters others. It demands new expertise in prompt engineering, system oversight, and hybrid human-machine workflows. Workers who adapt gain ground. Those who wait risk falling behind.
Yet broader labor market signals show restraint. Hiring slowed for a fourth straight month by April, per Indeed data. Postings sit 8.5% below year-ago levels and 27% under pre-pandemic marks. Unemployment holds near 4.4%. Quit rates match 2014-2015 figures. The environment stays low-hire, low-fire. Gudell expects 2026 to resemble 2025. No collapse in postings. No sharp rebound. Uncertainty from policy, tariffs, and immigration weighs on decisions.
Young workers feel particular pressure. Research from Stanford’s Digital Economy Lab, cited in analyses from the Dallas Fed and others this year, shows employment declines hit harder for those under 25 in AI-exposed occupations. Job-finding rates for new graduates in tech and related fields have cooled. Entry-level roles that once built experience now face automation pressure. MIT researcher Andrew McAfee warned in a May 1 Fortune article that removing these positions could starve companies of future talent pipelines and AI-fluent leaders.
Executives at the summit wrestled with execution. Becky Schmitt, chief people officer at PepsiCo, described the internal challenge. Some parts of organizations race ahead on AI. Others move slower. Standard processes, shared data sets, and translatable core job elements help scale efforts across borders. Without them, investments stay siloed. “If you want to let everybody have their own kingdom, you’re going to invest heavily in one part of the world, and then it can’t go someplace else,” Schmitt said.
So the gap widens. Large tech firms, hyperscalers, and consultancies pour resources into AI. They hire aggressively for roles that blend technical fluency with domain knowledge. Smaller firms watch. They experiment cautiously. The result? A labor market splitting between AI leaders and laggards.
Public sentiment adds tension. Polls show seven in ten Americans worry AI will make work harder to find. Headlines amplify fears of an impending jobs apocalypse. Yet current data tells a more measured tale. Employment in AI-exposed sectors has declined modestly in some readings since late 2022. But overall U.S. job growth persists. Healthcare alone drove 73% of net job gains in recent years despite representing just 11% of employment.
Productivity gains offer the upside. When firms integrate AI effectively, they see higher sales growth and employment expansion over time, according to MIT Sloan research. Legal roles, for instance, benefit from augmentation without heavy task substitution. Top-paying positions in management and engineering may shrink in headcount per firm but grow in strategic importance.
Gudell returns to preparation. Companies must act on data now. They need to identify which tasks AI can augment first. They must train workers for the hybrid future. They should anticipate the wage premiums for AI-adjacent skills. The transformation arrives slower than expected. Its eventual depth could exceed forecasts.
Recent commentary reinforces her view. Goldman Sachs CEO David Solomon noted in March that embedding AI proves neither cheap nor easy. Process changes spanning decades meet resistance. A recalibration may hit in 2026 as leaders confront the gap between pilot projects and enterprise scale. The Economist warned of an apocalypse but acknowledged current employment remains high. The debate continues.
One truth stands clear. Adaptation beats prediction. Workers who build AI literacy. Managers who learn to direct augmented teams. Organizations that treat data as strategic. They position themselves for the longer arc Gudell describes. The labor market shifts. Gradually at first. Then with greater force.
Executives would do well to listen. The speed feels slower today. The impact builds for tomorrow.
Indeed Economist Warns Executives Overestimate AI’s Labor Market Speed first appeared on Web and IT News.