Wharton professor Ethan Mollick advises young jobseekers to focus on mastering concrete tasks rather than chasing specific AI skills that can quickly become outdated. He frames AI as a tool for "task distribution," able to take on weaker parts of a role while people concentrate on strengths and judgment. Mollick emphasizes the importance of knowing how to instruct AI and evaluate its outputs, and recommends pairing broad knowledge—especially in the humanities—with deep expertise. He warns that AI threatens many entry-level jobs and calls for urgent redesign of roles and training.
Master Tasks, Not Trends: Wharton’s Ethan Mollick on How Young Jobseekers Can Outpace AI
Wharton professor Ethan Mollick advises young jobseekers to focus on mastering concrete tasks rather than chasing specific AI skills that can quickly become outdated. He frames AI as a tool for "task distribution," able to take on weaker parts of a role while people concentrate on strengths and judgment. Mollick emphasizes the importance of knowing how to instruct AI and evaluate its outputs, and recommends pairing broad knowledge—especially in the humanities—with deep expertise. He warns that AI threatens many entry-level jobs and calls for urgent redesign of roles and training.
16:24, 09.11.2025Technology
Wharton AI expert: Focus on tasks, not transient AI skills
Wharton professor Ethan Mollick, author of Co‑Intelligence, told Business Insider that young jobseekers should prioritize mastering concrete tasks rather than accumulating narrowly defined AI skills that can quickly become obsolete.
Mollick argues that many technical abilities tied to current AI tools lose value as models and interfaces evolve. Instead, he recommends identifying the specific tasks you do well—those where human judgment still outperforms machines—and building your career around them.
"It would be helpful for young people to think more about what tasks they're actually really good at, because that's where they stay ahead of machines," Mollick said. "And then you can find a job where the machine helps you with the other pieces of your task."
He explains that every job consists of a bundle of tasks, and it is rare for one person to excel at all of them. AI can enable smart "task distribution," taking on weaker components while people focus on strengths. Crucially, workers must learn to give clear instructions to AI and to evaluate its outputs: "Being able to be an expert enough in something to know whether it's good or bad turns out to be really important," he added.
Mollick also recommends combining broad general knowledge—especially in the humanities—with deep expertise in particular areas. Because large AI systems are trained on wide-ranging sources, a contextual, human-centered perspective helps in detecting errors, spotting nuance, and improving machine-generated work.
He warned that AI threatens many entry-level roles across industries, making it harder for Generation Z to break into the workforce. Having consulted on AI with organizations including JPMorgan, Google and the White House, Mollick said his chief concern is whether employers and policymakers are moving quickly enough to redesign jobs and career pathways for this new environment.
As automation handles some technical tasks, soft skills—communication, leadership, organization and critical judgment—become increasingly valuable. Employers and educators should focus on restructuring roles and training so young workers can pair uniquely human strengths with AI assistance.