You can still outpace AI: Wharton professor reveals a ‘skill bundling' strategy to safeguard your future from automation

Economic Times

3 days ago

iStock Artificial Intelligence is rapidly changing workplaces. Wharton professor Ethan Mollick suggests professionals focus on roles requiring diverse human skills. These include emotional intelligence and creativity. (Image: iStock)
As artificial intelligence reshapes the modern workplace with stunning speed, one Wharton professor has a sobering message for today's professionals: the safest jobs of tomorrow aren't necessarily the most technical—they're the most complex.
Ethan Mollick, associate professor at the Wharton School and author of Co-Intelligence: Living and Working with AI, says job security in the AI era will increasingly depend on choosing roles that bundle multiple human skills together. That means emotional intelligence, judgment, creativity, and domain expertise—all woven into one. 'AI may outperform you in one or two things,' Mollick tells CNBC Make It, 'but if your job requires five or six of them, it's a lot harder to replace.'
It's the kind of insight that redefines how we think about employability in an increasingly automated world. And with AI usage surging—40% of U.S. workers now use it at least a few times a year, per a Gallup poll—these career choices have never mattered more. Mollick doesn't sugarcoat the AI wave ahead. Tech labs aren't just chasing progress—they're chasing a paradigm shift. 'Labs are aiming for machines smarter than humans within the next three years,' Mollick warns. 'They're betting on mass unemployment. Whether they succeed or not is still unclear, but we have to take it as a real possibility.'
Even Nvidia CEO Jensen Huang, whose company powers some of the most advanced AI systems, echoes that sentiment—albeit from a different vantage point. In a recent All-In podcast, Huang predicted AI will create more millionaires in five years than the internet did in 20, while also cautioning: 'Anybody who is not using AI will lose their job to someone who is.' What's the solution? According to Mollick, job seekers must rethink their strategy. 'Don't go for roles that do one thing,' he says. 'Pick a job like being a doctor—where you're expected to be good at empathy, diagnosis, hand skills, and research. If AI helps with some of it, you still have the rest.' This idea of "bundled roles"—where a single job draws on varied skills and responsibilities—could be the firewall against replacement. These complex, human-centered positions are harder for AI to replicate wholesale and leave more room for humans to collaborate with AI, not compete against it. AI's evolution could make entry-level roles scarce—or at least, radically different. 'Companies will need to rethink entry-level hiring,' Mollick notes. 'Not just for productivity, but for training future leaders.'
Without the chance to learn through repetition—what Mollick calls 'apprenticeship'—younger workers may miss out on foundational skills. The result could be a workforce with knowledge gaps AI can't fill, even as those same gaps are used to justify greater automation. Nvidia's Huang calls AI the 'greatest equalizer of our time' because it gives creative power to anyone who can express an idea. 'Everybody is a programmer now,' he says. But critics caution that this accessibility may also deepen divides between the AI-literate and those left behind.
Eric Schmidt, former Google CEO, has a different concern: infrastructure. On the Moonshots podcast, Schmidt warned that AI's growth could be throttled not by chips, but by electricity. The U.S., he says, may need 92 more gigawatts of power to meet AI demands—equivalent to 92 new nuclear plants. As AI spreads into every corner of work, from payroll review (yes, Huang uses machine learning for that too) to high-stakes decision-making, the one thing that's clear is this: the rules are changing faster than most organizations can adapt. 'The tools are evolving fast,' Mollick says, 'but organizations aren't. And we can't ask employees to figure it all out on their own.' He believes the real danger isn't AI itself—but the lack of vision from leadership. Without a clear roadmap, workers are left adrift, trying to 'magic' their way into the future. In the race to stay relevant in the AI era, the best defense isn't to out-code or out-process a machine. It's to out-human it—by doubling down on the kind of nuanced, multi-layered work AI can't yet replicate. And by choosing jobs that ask you to wear many hats, not just one. Or as Mollick puts it: 'Bundled tasks are your best bet for surviving the AI takeover.'