AI won’t take your job, tech leaders tell VCU Business students — but someone who uses it well might
At a VCU Business panel on AI, industry leaders outlined the skills that will matter most as automation becomes a bigger part of daily work.
By Megan Nash
The question arrived midway through the hourlong conversation: Should students preparing for today’s job market be worried about artificial intelligence?
“AI is not going to take your job,” said Shamim Mohammed, executive vice president and chief information and technology officer at CarMax, to a packed auditorium at the VCU School of Business. “Who could take your job? The person who knows how to use AI better.”
It was one of many blunt assessments in a Nov. 14 panel hosted by the School of Business, where Mohammad and Ankit Mathur (B.S. ’03, M.B.A. ’12, M.S. ’13), chief technology officer at the United Network for Organ Sharing (UNOS), reflected on how AI is changing work, decision-making and the pace of innovation across industries that could not be more different: used-car retailing and organ transplantation.
The panel, moderated by School of Business Dean Brian Brown, Ph.D., unfolded against a backdrop of a year in which AI tools have become as commonplace in classrooms as in offices. But as the two executives told the audience, the headlines still miss the point. Technology alone isn’t the story. The story is how people use it, and how quickly the ground is shifting beneath everyone’s feet.
‘You can imagine, in a year from now…’
Mohammed, who came to the United States alone at 17 with “one semester worth of money,” traced his own career through several technological eras, from the rise of the commercial internet to the cloud. But nothing, he said, compares to the speed of change happening now.
A year ago, he spent a day at NVIDIA headquarters. “The capability we’re dealing with now, and we’re excited about? It’s not even tomorrow’s technology,” he said. “It’s yesterday’s technology. So you can imagine, in a year from now, all the new things you’re going to see.”
CarMax has been focused on leveraging AI technology for years. The company uses AI to streamline vehicle data, support software engineers and help customers navigate the process of buying and selling cars.
One early breakthrough came in 2021, when teams used generative AI to organize years of customer reviews and vehicle information. It was a task that would have demanded “11 years worth of work by our content team,” said Mohammed. With generative AI, “we did that in just a few months.”
‘Healthcare is not a machine’
Mathur’s world is far removed from showroom lots. At UNOS, the nonprofit that oversees the nation’s organ matching and allocation system, the stakes are measured in lives saved and lives lost.
“Over a hundred thousand people in this country are extremely sick,” he said. “They’re in desperate need of a life-saving organ.”
UNOS maintains the complex matching algorithms that route donated organs to patients. And in that process, Mathur said, surgeons must weigh “a hundred different decisions,” including blood type, clinical history, organ dimensions and even inevitable imperfections.
His team turned to AI not to replace judgement, but to better inform it. “We realized we have insane amounts of data,” said Mathur. Using that information, UNOS developed predictive models that estimate how likely a patient is to receive an organ over the next three years and whether a particular donation is likely to succeed.
“Healthcare is very, very human,” he said. “We’re not making the decision for the doctor. Absolutely not. But we can present data in a better way.”
The model has now been tested, piloted at transplant centers and integrated into the national system. For surgeons, Mathur said, the advantage is time — time not wasted reviewing fragmented information when minutes could mean survival.
“It’s amazing,” he said. “It’s totally amazing.”
A new worker: Human + AI
If the executives agreed on anything, it was this: the next decade will reward adaptability more than technical expertise.
“What you learn today,” said Mohammed, “will be obsolete by the time you graduate.”
He urged students to develop what AI still can’t replicate: emotional intelligence, critical thinking, domain expertise and a “beginner’s mindset.” The ability to keep learning, he said, will matter more than memorizing tools that change every quarter.
Mathur echoed the warning. Even seasoned professionals, he said, are falling into the trap of outsourcing their thinking.
‘Don’t ask how to prevent students from using AI’
Brown shifted the conversation toward educators. What should universities do, he asked, when the workplace is changing “even as we speak?”
“The wrong question is, ‘How can we prevent students from using AI?’” said Mathur. Universities, he argued, should teach students to use the tools responsibly while still holding them accountable for the quality of their work.
He also recommended a shift in mindset. With AI lowering the barriers to product development and experimentation, he said, students should learn to think like entrepreneurs.
“The bar to building a product and bringing it to market has gotten so, so low,” he said. “Man, what an opportunity.”
Mohammed agreed, adding that the next wave of breakthroughs may come from anywhere, including student teams leveraging AI in ways large companies haven’t yet imagined.
“Be inspired. Be excited,” he said. “We are living through a lightbulb moment in human history.”
The part that doesn’t change
For an audience of undergraduate and graduate students, faculty, staff and Richmond-area professionals, the panel delivered a rare combination: candor about the risks, clarity about the possibilities and a reminder that the future isn’t predetermined.
AI may automate tasks, restructure roles and change how companies evaluate applicants. But both executives emphasized what won’t change.
People who collaborate well will flourish. People who understand data will have an advantage. People who stay curious, adaptable and able to solve problems will represent the next era of the workforce.
And for all the talk of algorithms, the leaders returned to the same idea.
“You have to understand your data,” said Mathur.
But also: “You have to understand each other,” said Mohammed.
Even in the age of AI, it seems, the human operating system still matters most.
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