Meeting Sabrina Hsueh in Hudson Yards
Making AI Work for the Business
I’m exiting the subway at Hudson Yards and making my way into one of New York’s coolest business districts. Hudson Yards is highly designed, with glass buildings and wide pedestrian spaces.
I enter the Pfizer building, check in at reception, and head for the elevators.
As the elevator climbs to the 66th floor, I’m thinking about the coincidence that Dr. Sabrina Hsueh has also worked across 66 countries. Over more than two decades in AI and computer science, Sabrina has worked across Asia, the U.S., Europe, and beyond. She has built partnerships, contributed to global standardization, and spent years working at the point where technology, governance, and business meet. Today, much of her work is about helping companies make AI useful inside the business from the start.
The elevator opens onto the 66th floor, and I’m shown into the Pfizer Clubhouse. A few minutes later, Sabrina walks in.
She greets me, we take a seat, and before long we are talking about AI, business, and what companies are still trying to figure out.
I start with the question that feels most obvious. “Sabrina, a lot of companies are still trying to figure out where AI belongs. How do you see it?”
She answers quickly. “AI is not the business,” she says. “But it has to be part of how the business runs.”
That becomes the main focus of our conversation.
Sabrina began her career teaching machines how to understand human language. Today, as a PhD in computer science with more than two decades of experience in AI, she describes her role more simply: helping AI and people understand each other, so they can work together in a way that creates value.
I ask her how she ended up in this field so early.
“I’ve rarely taken the expected path,” she says. “Growing up in Taiwan and attending an all-boys school, I learned early what it meant to challenge expectations and find my own way forward. When it came time to choose a career, I went into computer science instead of following a more traditional route. At the time, it was not the popular path, but it was where I saw possibility.”
I turn to what has changed most over time.
“The speed,” she says. “That’s what changed most. There is no longer time to define principles first and implement later. AI is moving too fast for that. It has to be built into how decisions are made, how processes run, and how outcomes are delivered.”
For boards and leadership teams, that changes the discussion. The question is no longer whether AI should be discussed. It is whether the company knows how to use it in a way that is practical, responsible, and tied to how the business actually works.
Sabrina explains that one of the biggest gaps is that technical teams, business teams, and governance teams often work separately. The technical side builds. The business side tries to apply. Governance often comes in later. Her role is to connect those pieces early enough that AI becomes usable inside the company, not added on after the fact.
I’m curious whether her international experience shaped that perspective.
She nods. “Traveling and working across 66 countries taught me how differently people think, and how easily disciplines can misread one another. When progress depends on alignment, you have to find common ground.”
That may be one reason she talks about AI in such practical terms. She is not interested in AI as a separate initiative. She is interested in whether it can be built into the system in a way that business leaders can rely on.
“That also changes what responsible AI means,” she says. “It cannot live only in policies. It has to be part of the architecture. It has to be enforceable, usable, and present in everyday operations.”
I wonder what companies still misunderstand.
“Sometimes companies treat AI as if it sits outside the business,” she says. “As if it is an initiative, or a layer, or something separate. But in the end, the business is the business. AI should simply make it work better.”
Before we wrap up, I ask her how she explains her value in the clearest possible terms.
She smiles. “AI is incredibly powerful,” she says. “But power without direction does not help a business. My role is to put a harness around it, so it actually moves the business forward.”
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