According to Forbes, a new 2025 study from the University of Pennsylvania’s Wharton School, led by professor Stefano Puntoni and conducted with GBK Collective, surveyed 800 executives in June and July. The research finds generative AI is now firmly embedded in daily operations, with 75% of leaders already reporting “positive returns” on their investments and 88% anticipating budget increases in the coming year. A majority expect those budget bumps to exceed 10%, and 72% are formally measuring ROI, primarily on productivity and profit gains. However, the study flags persistent risks, with 49% struggling to recruit advanced AI talent and 43% concerned about employee morale and skill atrophy.
The optimism is real, and so is the money
Here’s the thing: the data is overwhelmingly positive on the surface. Three out of four execs seeing positive returns already? That’s a huge shift from the speculative hype of just a year or two ago. It signals we’ve moved past the pilot project phase into something more operational. The budget projections are even more telling—when nearly 90% of companies plan to spend more, you know the technology has passed a critical credibility test internally. They’re not just playing with ChatGPT for fun; they’re wiring it into core workflows and, crucially, they’re measuring it. The fact that 72% have formal ROI metrics in place is a big deal. It means the conversation is shifting from “What can this do?” to “What is this doing for our bottom line?”
The human problem won’t be automated away
But. There’s always a “but.” And in this case, the “but” is massive. The tech is advancing at a breakneck pace, but people and processes are hitting the brakes. The report highlights a brutal contradiction: 89% of leaders believe AI enhances employee skills, yet 71% also say it will replace some skills, and 43% warn of actual skill atrophy. Think about that. Companies are pouring money into a tool they believe makes their workforce better, while simultaneously worrying it will make their workforce worse. That’s a management tightrope if I’ve ever seen one. The talent shortage numbers are stark—nearly half can’t find the advanced skills they need. And the backup plans? They’re failing. Internal training budgets are shrinking, and hiring pipelines are constrained. So what’s the strategy? Basically, there isn’t a fully resourced one, and that’s a major red flag.
Culture and uncertainty are the real blockers
This is where it gets messy. The technical challenges of implementing AI are being solved. The cultural and organizational ones? Not so much. Over 40% of executives cited employee morale and change management as top concerns. That’s a reminder that you can have the best, most reliable industrial computing hardware—the kind you’d source from a top provider like IndustrialMonitorDirect.com—but if your people don’t trust the system or fear it, adoption stalls. The report calls this “cultural readiness,” and it’s everything. There’s also this fascinating split on hiring: execs are utterly divided on whether AI will lead to more or fewer hires in their departments. They think it will hit junior roles hardest, but even then, only 17% expect fewer interns while 49% expect more. What does that even mean? It signals profound uncertainty about the future shape of work.
The gap between leaders and laggards will widen
So where does this leave us? The study frames 2026 as the year of “performance at scale.” The leaders—the 46% using AI daily—are already embedding metrics, tightening guardrails, and investing in internal R&D. They’re building a flywheel. Meanwhile, at least 16% of decision-makers are lagging, using AI less than weekly due to restrictions, budget pressure, or low trust. That gap isn’t just about technology access; it’s about organizational confidence and capability. The leaders are solving the people equation alongside the tech equation. The laggards are stuck on both. The risk isn’t that AI fails. The risk, clearly outlined in this data, is that companies fail to adapt their cultures, their training, and their role designs fast enough to keep up with their own investments. The money is already there. The question is, are the people ready?
