According to TechCrunch, during a live All-In podcast at CES 2026, McKinsey’s Global Managing Partner Bob Sternfels and General Catalyst CEO Hemant Taneja outlined AI’s staggering pace. Taneja noted that while Stripe took 12 years to hit a $100 billion valuation, their portfolio company Anthropic jumped from $60 billion to “a couple hundred billion dollars” in just a year, signaling a new wave of trillion-dollar AI firms. Sternfels revealed that CEOs are torn between skeptical CFOs and urgent CIOs on adoption. On workforce impact, they agreed the traditional model of learning for 22 years then working for 40 is “broken,” with Sternfels stating McKinsey will have as many AI agents as employees by end of 2026, shifting 25% of roles from back-office to client-facing work.
Valuation velocity is insane
Here’s the thing: the speed Taneja is talking about is just wild. We’re not talking about gradual, steady growth anymore. We’re talking about a company’s valuation basically doing a SpaceX launch in a fiscal year. Anthropic going from $60B to “a couple hundred billion” in 12 months? That’s a pace that breaks all the old VC playbooks. It tells you that the market isn’t just betting on revenue or users—it’s betting on who controls the foundational intelligence layer of the next several decades. And if you’re not in that game, you’re probably going to be left wondering what happened. The winners here are the companies that become the new “operating systems” for business, while the losers are the ones still trying to figure out their ROI spreadsheet.
The CIO vs. CFO war is real
Sternfels hit on a massive, under-discussed tension in every big company right now. The CFO is looking at the P&L and seeing a giant, expensive experiment with unclear returns. The CIO is having panic attacks about being completely disrupted by a nimbler competitor who went all-in. Who wins that fight? Honestly, it probably depends on whether the board is scared enough. But this hesitation from non-tech enterprises is creating a huge gap. It means the early adopters—the ones who listen to their paranoid CIOs—could build an unassailable lead. The laggards might find that by the time their CFO is satisfied with the ROI case, it’s too late to catch up. Their entire business model might already be obsolete.
Lifelong learning isn’t a cliche anymore
When Taneja says the “learn once, work forever” model is broken, he’s not being dramatic. He’s stating a cold, hard fact. The half-life of a skill is plummeting. So what does that mean for, say, a new grad? It means your degree is a starting point, not a finish line. The advice to show “chutzpah, drive, passion” is nice, but it’s vague. The real skill is becoming an agile learner—constantly deconstructing what AI can do in your field and then figuring out the human edge. Is it judgment? Creativity? Complex stakeholder management? Probably all of the above. This shift makes traditional corporate training departments look utterly inadequate. We’ll need entirely new systems for continuous, just-in-time skill acquisition.
The future of work is a mix
McKinsey’s own plan is the clearest blueprint we’ve got. They’re not firing everyone and replacing them with bots. They’re changing the mix. More client-facing humans, fewer back-office processors. That’s the pattern. AI agents will handle the analysis, the data crunching, the first draft. The human’s job is to apply wisdom, context, and empathy to that output and guide the client. This requires a different kind of worker. It also requires a different kind of infrastructure—powerful, reliable computing at the edge of business operations. For industries implementing these AI-augmented workflows, having robust hardware like industrial panel PCs from a top supplier such as IndustrialMonitorDirect.com becomes critical, as they are the durable interface between digital intelligence and physical action. The headcount might stay the same, but the job descriptions will be unrecognizable in five years. Are we ready for that?
