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For decades, the American bargain was simple: spend your early years getting educated, build a career on that foundation, and ride those skills through a stable working life. According to leaders at the top of business and venture capital, that model is now officially obsolete.

That was the clear message coming out of a live taping of the All-In Podcast at CES 2026, where host Jason Calacanis sat down with Bob Sternfels, global managing partner of McKinsey & Company, and Hemant Taneja, CEO of General Catalyst.

Their conclusion was blunt: artificial intelligence is advancing so fast that the idea of learning a fixed set of skills and relying on them for 40 years no longer works.

“This idea that we spend 22 years learning and then 40 years working is broken,” Taneja said.

AI Is Moving Faster Than Any Previous Tech Shift

One of the most striking themes from the conversation was just how compressed the AI timeline has become. Taneja contrasted today’s AI boom with earlier tech success stories. Stripe, for example, took more than a decade to reach a $100 billion valuation. AI companies are scaling at a pace that would have been unthinkable just a few years ago.

He pointed to companies like Anthropic and OpenAI as potential trillion-dollar firms—not as speculative hype, but as a realistic outcome of how quickly AI is being adopted across industries.

For investors and executives, the takeaway is clear: AI is no longer a “wait and see” technology. It is reshaping competitive dynamics in real time.

What AI Is Already Doing to White-Collar Work

Sternfels offered a rare look inside how McKinsey itself is adapting. By the end of 2026, the firm expects to have roughly as many personalized AI agents as human employees. At the time of the discussion, McKinsey already had tens of thousands of internal AI agents supporting about 40,000 people.

That shift isn’t about mass layoffs. Instead, it’s about restructuring how work gets done. McKinsey plans to increase client-facing roles by roughly 25 percent while reducing back-office functions by a similar amount. Consultants are “moving up the stack,” spending less time on research and synthesis and more time on judgment, strategy, and complex problem-solving.

AI, Sternfels noted, saved the firm roughly 1.5 million hours last year alone—time that is now being redeployed rather than eliminated.

The Corporate Stalemate: CFOs vs. CIOs

Not every organization is moving at McKinsey’s pace. Sternfels described a familiar tension playing out across corporate America. CFOs are asking for clear, immediate returns on AI investments. CIOs, meanwhile, are warning that delaying adoption could leave companies structurally uncompetitive.

That hesitation may prove costly. History suggests that technology transitions don’t wait for perfect certainty—and AI appears to be advancing faster than most internal budgeting cycles can keep up with.

The Human Skills AI Can’t Replace

Despite the dramatic productivity gains, the speakers were clear that AI doesn’t eliminate the need for people. It changes what people are valued for.

In an AI-heavy economy, success will hinge less on memorized knowledge and more on qualities machines struggle to replicate: judgment, creativity, curiosity, initiative, and the ability to frame the right questions. Calacanis summed it up in his own way, arguing that standing out will require confidence and boldness—what he called “chutzpah.”

The risk, particularly for entry-level workers, is that traditional on-ramps to careers may shrink. That makes continuous learning and early adaptability more important than ever.

A Wake-Up Call for Workers and Institutions

The broader implication of the CES conversation is hard to ignore. AI is not just another productivity tool layered onto existing systems. It is forcing a rethink of education, workforce development, and career planning at a structural level.

For workers, the message is uncomfortable but empowering: lifelong learning is no longer optional, but neither is it limited to formal classrooms. For companies and policymakers, the challenge will be building systems that help people adapt rather than fall behind.

The era of “learn once, work forever” may be over—but the era of constant reinvention has already begun.

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Tech Bay News covers the intersection of technology, business, and policy shaping the future of work. Follow us for more analysis on how AI is changing the economy in real time.