‘Not AI, pandemic over-hiring is’: IBM CEO Aravind Krishna on what’s really driving tech layoffs

When headlines blame artificial intelligence for sweeping layoffs across Silicon Valley and beyond, IBM CEO Aravind Krishna says that explanation misses the bigger picture. 

In a wide-ranging interview with The Verge, Krishna pushed back on the notion that AI is the primary driver of the current job cuts, arguing instead that much of today’s correction is a direct aftershock of pandemic hiring binges between 2020 and 2023. While he conceded AI will cause some displacement, he described the immediate wave of reductions as a market realignment — not a technological apocalypse. 

Krishna used blunt language to describe the staffing boom in the pandemic years. “If you look at the total employment numbers, I think people gorged on employment… during the pandemic and the year after,” he said, pointing out that many companies expanded headcount by eye-watering amounts — “30, 40, 50, 100 percent” in some cases — to meet a surge in demand and new product bets. 

That rapid expansion, Krishna argued, left many firms overstaffed once demand normalised and priorities shifted. “There is going to be some natural correction,” he said, using an engineering analogy to explain the cycle. “Business is never completely optimized. I think in engineering terms, it’s an underdamped system. When there’s a need, it goes above. Now, it has to correct. It’s probably going to go below what’s needed, and then it’ll hit the correct equilibrium, depending on market demand and growth.” 

AI will displace jobs but not catastrophically 

Krishna did not dismiss AI’s impact. He projected that AI could lead to “up to 10 percent” job displacement in the U.S. employment pool over the next couple of years — a meaningful but manageable figure compared with more apocalyptic predictions that circulate in some corners of the media and policy debate. 

“It’s not 30 or 40 percent, but it is up to 10 percent of the total US employment pool. It is very concentrated in certain areas,” he said, stressing that the effects will be uneven across sectors and job types. 

Productivity, retooling and new roles 

A recurring theme in Krishna’s remarks was the idea that AI is a productivity multiplier that will reshape jobs rather than simply eliminate them. As companies adopt AI to automate routine tasks, he said, they will increasingly hire for different functions — roles that emphasize oversight, strategy, product design, and other skills that complement AI tools. 

“Now, as you get more productive, companies are going to then hire more people but in different places,” Krishna noted. He described internal discussions where managers say an AI agent can handle an entry-level task — and urged leaders to “think strategically” about how to redeploy human talent. 

What this means for workers & policymakers 

Krishna’s framing has several pragmatic takeaways: 

• Hiring cycles matter. Companies that expanded quickly during the pandemic are now trimming to match current demand — a normal but painful market correction. 
• AI will change job composition. Displacement is likely to be concentrated in routine, entry-level, and narrowly defined tasks; other jobs will evolve. 
• Reskilling is central. The shift toward AI-complementary roles implies an urgent need for training programs, upskilling initiatives, and education pathways that help workers transition into higher-value roles. 
• Policy can smooth transitions. If Krishna’s 10 percent estimate holds, targeted safety nets and workforce development efforts could blunt the social cost of displacement without stopping technological progress. 

A counterpoint to the doom narratives 

Krishna’s perspective adds nuance to a polarized debate. On one side are commentators warning of mass, AI-driven unemployment; on the other are CEOs and venture investors who treat layoffs as an inevitable byproduct of growth cycles. By spotlighting pandemic over-hiring as the proximate cause of many cuts, Krishna reframes much of the current turmoil as cyclical correction rather than an existential labor market breakdown. 

That doesn’t eliminate the challenges: sectors and communities hit by both correction and automation will need support. But Krishna’s argument suggests the labor market may ultimately absorb AI’s productivity gains — shifting rather than shrinking the demand for human work. 

Krishna doesn’t deny AI’s disruptive potential. He simply warns against a single-cause narrative. The layoffs making headlines today, he says, are largely a market recalibration after an extraordinary period of hiring — with AI acting as an accelerant for change, not the primary arsonist.