​Talent Is The Bottleneck: Why AI Strategy Now Depends More On People Than Models

Innovation​Talent Is The Bottleneck: Why AI Strategy Now Depends More On People Than ModelsByRussell Sarder,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 13, 2026, 08:30am EDTRussell Sarder, CEO & Founder of AI CERTs – advancing global AI certification & education. gettyMost AI strategies still read like shopping lists: Pick a model, pick a platform, hire a few specialists and then wait for productivity.That’s not where the constraint is showing up. In the U.S., most workers still aren’t using AI meaningfully in day-to-day work. The Pew Research Center found that, as of October 2025, 65% still “don’t use AI much or at all.”If usage is low, model capability doesn’t matter. The bottleneck is people and how work is designed.The productivity promise is real but slow to show up.This is why the “ROI debate” keeps coming back every budget cycle. The Conference Board captured the gap: In 2024, 86% of CEOs expected boosted productivity, but a year later, only 44% said workforce productivity was the biggest improvement they’d actually seen from AI.​That gap isn't solved by upgrading models. It’s solved by turning AI into a workforce capability with new roles, new standards and new operating habits.Skills churn is now a CEO problem.AI is reshaping work faster than most companies can reskill. LinkedIn’s 2025 Work Change Report says that "by 2030, 70% of the skills used in most jobs will change, with AI emerging as a catalyst."​The labor market is already signaling it. Stanford’s AI Index 2025 reports that "in 2024, U.S. job postings citing generative AI skills increased by more than a factor of three" year over year.​So, the "talent strategy" can’t be a hiring plan alone. It has to be a redesign plan.Define AI talent the right way. if (!window.cnxel) { window.cnxel = {}; window.cnxel....