In recent weeks, a list of the most prominent figures in technology today –Nvidia CEO, Jensen Huang, AMD CEO, Lisa SuHI Google CEO, Eric Schmidtamong other things – took the podium at the beginning of the university for him address an anxious class of 2026, the first group to spend all of their college years alongside generative AI tools. (ChatGPT launched in November 2022, during their first year.) Across campuses, industry leaders behind those podiums delivered a broadly similar message: embrace AI, but learn to master it. How that message came across, however, depended less on what was said than on who said it—and, perhaps, where it was said.
The starkest contrast emerged between Schmidt at the University of Arizona and Huang at Carnegie Mellon. While Schmidt’s lively optimism about AI drew loud jeers and cheers throughout his speech, Huang’s similarly upbeat message was met with quiet reverence.
Further south, at Middle Tennessee State University, Scott Borchettafounder of Big car tag set (which was famously launched Taylor Swift), also faced backlash when he told graduates to “get on with it” while discussing the disruption of creative industries by AI.
Meanwhile, at Grand Valley State University in Michigan, co-founder of Apple Steve Wozniak won standing ovation with a line that cleverly changed the narrative: “You all have AI – actual intelligence.”
Those polarized reactions were not the result of any single speech. If you listen carefully to what they said, the text of those prepared remarks was very similar. What differed was the tone of the delivery and the audience that heard it. If there was a pattern, students at elite institutions seemed more receptive to pro-AI messages than their peers at public universities. Huang spoke at a school widely regarded as one of the birthplaces of AI (where researchers created the first AI computer program in the 1950s.) Last week, his rival (and distant relative), Lisa Su of AMD, gave a commencement speech at her alma mater, MIT, where she was also warmly celebrated.
Of course, the person behind the podium was just as important. Commencement speeches, especially at alma maters, are among the rare moments when tech CEOs shed their corporate armor and offer something resembling personal advice. But they are also an unforgiving referendum on reputation. Huang and Su, who are actively building the infrastructure powering the AI boom, are seen as shaping the future in tangible ways while taking real business risks. By contrast, Schmidt has long been seen as an outspoken capitalist and the poster child for an older, the unconscious era of Big Tech. His awkwardly rushed, occasionally tone-deaf delivery in Arizona only reinforced that perception.
The rapid evolution of AI tools over the past three to four years has reshaped the way students choose majors and think about careers. While overall unemployment in the US remains relatively low, entry-level employment has shrunk severely. (Blame remote work, too, because employers are reluctant to hire recent graduates to remote teams because of training challenges.) According to a recent Federal Reserve survey, tUnemployment rate for graduates aged 22 to 27 rose to 5.7 percent, the highest level since 2014excluding pandemic years.
Against this backdrop, advice from technology leaders converges on a simple theme: expect disruption and adapt.
“My career started at the start of the PC revolution. Your career starts at the start of the AI revolution. I can’t imagine a more exciting time to start your life’s work,” said Huang. “Artificial intelligence is unlikely to replace you, but someone who uses AI better than you.”
“Technology itself doesn’t decide what the future looks like. The best people do,” Su said. “It needs people who know what to use it for – people with purpose and judgment and courage; people who see a difficult problem and say: this matters and we can figure it out.”
And, stripped of the snake that greeted him in Arizona, Schmidt’s core message was not that different: IT “will touch every profession, every classroom, every hospital, every laboratory, every person and every relationship.” But, he added, it only becomes useful if people do the work to understand it. “I think the main thing is that we, as people, have to keep feeling that hard work, going through the trouble of learning things, is worth it and it pays off, and that’s how you really improve yourself,” he said.
