Nvidia CEO Jensen Huang has offered a clear explanation for why AI is unlikely to eliminate jobs, emphasizing the crucial difference between "tasks" and "purpose" in the workplace. In a recent appearance on the No Priors podcast, Huang argued that while AI automates repetitive tasks, it doesn’t replace the fundamental purpose of most jobs—leading to job transformation, not disappearance. He illustrated this with the example of radiology. Despite early warnings from AI pioneer Geoffrey Hinton that AI would make radiologists obsolete, the opposite has occurred. In 2025, U.S. diagnostic radiology residency programs offered a record 1,208 positions—a 4% increase from the previous year—and vacancy rates are at historic highs. Radiologists also now earn an average of $520,000 annually, over 48% more than in 2015. The reason? AI has taken over the task of analyzing scans, but the core purpose—accurate diagnosis, guiding treatment, and advancing medical research—remains deeply human. With AI handling more images faster and more reliably, hospitals can treat more patients, increasing demand for skilled radiologists. Huang extended this logic across industries. He noted that while he spends much of his day typing, that’s a task, not his job’s purpose. AI tools that automate writing don’t make him redundant—they free him to focus on higher-level strategic work, often increasing his workload rather than reducing it. “It hasn’t really made me less busy. In a lot of ways, I become more busy because I’m able to do more work,” he said. In software engineering, AI can speed up coding, but the real value lies in problem-solving and identifying new challenges. At Nvidia, hiring remains strong even as AI tools like Cursor are adopted, because increased productivity allows teams to pursue more ambitious projects, driving growth and creating more roles. The legal profession follows the same pattern. While AI can draft contracts and summarize documents, the purpose of a lawyer—protecting clients, negotiating outcomes, and exercising judgment—remains human-centered. The need for skilled, trustworthy attorneys hasn’t diminished; it’s evolved. Even in restaurants, Huang pointed out that while AI might take orders or deliver food, the purpose of a waiter is to enhance the guest experience. Their role shifts from task execution to relationship-building and service quality, which AI cannot replicate. Huang’s message is not that AI won’t disrupt jobs. It will. But the evidence suggests disruption leads to job redesign, not mass unemployment. Workers whose roles are defined by repeatable tasks face the greatest risk. Those whose work centers on outcomes—diagnosis, customer experience, strategic thinking, conflict resolution—are more likely to thrive with AI as a tool, not a replacement. The future of work, he argues, isn’t about humans versus machines, but about humans using machines to do more meaningful work.