Your career needs a ‘gym membership’ to keep up with continuous AI advancements, says Campus founder Tade Oyerinde

The days of learning a skill once and coasting on it for life are over. The new reality, according to AI Campus founder and chancellor Tade Oyerinde, looks a lot like a New York City gym before summer. Speaking during the first day of the 25th annual Fortune Brainstorm Tech conference in Aspen, Colorado on Monday, Oyerinde posited that AI’s rapid pace of improvement has permanently changed the calculus of education—no matter where you are in your career. All that scrambling to deploy AI that companies and executives are doing right now? That’s not a one-time project that will suddenly reach a final resolution once and for all, said Oyerinde “I’m sorry if you’re exhausted,” Oyerinde told the audience. “You’re going to have to do that every year for the rest of your careers, ad infinitum.” He predicts organizations will soon staff permanent “continuous learning, continuous development, continuous evaluation” departments, as standard as operations or finance. And with AI models now approaching recursive self-improvement—where each version helps build the next—the curve will only get steeper. “The era of learn once and then you’re done for life is over,” Oyerinde said. “We’re going to have this exponential takeoff.” Which brings us to the gym, another place where consistency matters. Just like “everyone in New York wants to be hot and fit for the summer” and puts in two or three hours a week to get there, Oyerinde said, staying competitive at work will demand the same dedication and focus. “If you want to be the equivalent of hot and fit in your career, you’re going to have to spend two or three hours a week learning how to use the most recent advances in AI.” A faster, smarter way to learn The reframing of continuous education as maintenance rather than a single milestone also applies to the traditional thinking around the way schools and curriculums are designed and built. Colleges and universities often take the same approach for vastly divers