This blog post was originally published by Duke Fuqua School of Business.<\/strong><\/a><\/p>\nTaking a class on quantum computing within the first few days of joining business school wasn\u2019t exactly how I thought I\u2019d run into one of the coolest minds in AI. Professor Aaron Chatterji, lovingly known as Ronnie, sat down with all the incoming Fuqua MBA students to talk about the future of a quantum computing hub in Durham, North Carolina.<\/p>\n
When I pictured the future of computers, I imagined shiny labs in Silicon Valley or sleek data centers in Singapore, not a charming city in the middle of the Carolinas. But the world is full of surprises, and Ronnie had a way of making even quantum computing feel close to home.<\/p>\n
So, when I got the chance to interview him one-on-one about the future of artificial intelligence, it didn\u2019t fully register that I was sitting across from the chief economist at OpenAI. He didn\u2019t appear saddled by the weight of a fancy title or speak in tech jargon. Instead, he talked to me like a peer, someone who understood that curiosity is just as valuable as credentials.<\/p>\n
I came into Fuqua after three years as a consultant working in generative AI mergers and acquisitions at Accenture. I\u2019d seen the corporate side of the AI boom, but here was someone who had shaped policy at the White House and now steered economic thought at OpenAI. He was\u2026 approachable. Insightful. Grounded.<\/p>\n
Our conversation wasn\u2019t about sci-fi futures. It was about how to prepare for the careers, communities, and classrooms that AI is already reshaping. And boy, was I worried about that.<\/p>\n
We covered everything from responsible tech to the global talent race and how MBA students like me should be thinking about career strategy in an AI-powered world. What stood out the most was Ronnie\u2019s ability to zoom out and zoom in at the same time, connecting national policy to personal development with a clarity that felt rare in a world where everyone wants to believe they\u2019re the next big expert.<\/p>\n
Here are three big takeaways I\u2019ve been sitting with ever since:<\/p>\n
1. You\u2019re Not Competing With AI, You\u2019re Collaborating With It<\/strong><\/p>\nFancy tech jargon like prompt engineering used to mean nothing to me until I realized it was just a glorified way of saying: \u201centering the right things into the machine to get it to produce the output you want.\u201d<\/p>\n
When Ronnie said the trick to AI is learning to wield it, I finally understood the nuance. It gave a deeper meaning to the idea that AI isn\u2019t here to replace jobs or people; it\u2019s here to build and work with you. But only if you\u2019re willing to meet it halfway. Just like a car, if you don\u2019t learn how to steer the wheel, you\u2019re not going anywhere.<\/p>\n
In an increasingly interconnected world, the faster we adapt, the more we keep up.<\/p>\n<\/p>\n
2. Responsible AI Starts With Responsible Institutions<\/strong><\/p>\nIt\u2019s easy to talk about AI like it lives in the cloud: abstract, untouchable, the stuff of tech giants and sci-fi shows. To be honest, if a 5-year-old asked me what the cloud is, I probably still couldn\u2019t explain it. But Ronnie made one thing clear: the true power of AI lies in the hands of people, not platforms.<\/p>\n
He reminded me that the U.S.\u2019s secret weapon is the ecosystem of trust we\u2019ve built between universities, the government, and businesses. When these three work in sync, we can create AI that serves people. However, we can\u2019t live in the Candyland of AI gumdrops and sunshine and expect that everyone will be altruistic, trustworthy, and well-intentioned in their practices. So, let this serve as a reminder that our ecosystem is fragile.<\/p>\n
Without intention, transparency, and values baked into every line of code and policy decision, AI could easily deepen inequality, fuel bias, or erode public trust. While it\u2019s tempting to think AI is \u201cout to get\u201d us, the reality is, we\u2019re still the ones shaping it. The question is whether we\u2019ll do so with short-term thinking or long-term responsibility.<\/p>\n
Because AI doesn\u2019t decide how it\u2019s used. We do.<\/p>\n
3. Your Curiosity Matters Most<\/strong><\/p>\nAs a full-time MBA student smack in the middle of a tech revolution, I\u2019d be lying if I said I haven\u2019t wondered if I\u2019m learning fast enough to stay relevant. Between the daily avalanche of new tools, shifting job descriptions, and industry jargon, it sometimes feels like the real class I\u2019m enrolled in is Adaptability 101.<\/p>\n
Ronnie\u2019s advice? It\u2019s not about chasing the next shiny tool or memorizing the latest AI framework. It\u2019s about staying insatiably curious.<\/p>\n
AI is flattening the barriers to knowledge. Anyone can ask a question, but tomorrow\u2019s leaders are asking the right questions, right now. Whether you\u2019re an engineer, an economist, or a consultant (like me), your real skill is being deeply, creatively, and relentlessly interested in the world. That starts with the people around you.<\/p>\n
I didn\u2019t expect one of my first exciting opportunities at business school to be interviewing a former White House economist turned OpenAI executive, but that\u2019s the magic of Fuqua and of Ronnie Chatterji. The truth is, AI isn\u2019t some untouchable, far-off phenomenon dictated by an engineering degree. It\u2019s already shaping the jobs we\u2019ll take, the problems we\u2019ll solve, and the lives we\u2019ll lead.<\/p>\n
After this conversation, I\u2019m more certain that it\u2019s not about keeping up with AI but leading it with intention. And that leadership starts right here in Durham.<\/p>\n
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