Professor Jackie Hunter is a pioneering force in life sciences and health innovation. With a distinguished career spanning academia, industry leadership and government advisory roles, she has held senior positions at GSK and Benevolent AI, and is widely credited for shaping collaborative models of R&D across sectors.
A Fellow of the Academy of Medical Sciences and the Royal Society of Biology, Jackie’s influence reaches across drug discovery, AI integration, and open innovation. She played a key role in launching the Stevenage Bioscience Catalyst, one of the UK’s leading life science hubs, and continues to advise on the ethical application of emerging technologies in healthcare.
In this exclusive interview with The Motivational Speakers Agency, Jackie shares actionable insights for healthcare leaders navigating digital transformation—from applying AI responsibly to overcoming cultural resistance and embedding ethical standards into innovation.
Q: What lessons can healthcare leaders draw from innovation strategies in other sectors?
Jackie Hunter: “The potential to solve problems around climate change, around diseases, around social care with these new technologies is just tremendous. Traditionally, innovation in other sectors has moved more rapidly than in the healthcare sector—both in terms of public healthcare and also in terms of private healthcare. Industries like the pharmaceutical industry, healthcare, tended to hide behind the fact that there are, of necessity, a lot of regulation and rules in place.
“But you see large corporations in, say, the petrochemical industry, like British Petroleum, can move very quickly and adopt change. If we look at the example of electric vehicles—you know, within a few years, the industry had pivoted from being downplaying the potential impact of electric vehicles to really embracing the fact that they were being driven by many governments to really accelerate their development in this area.
“In healthcare, I think we have to look at ways in which these industries have been able to incorporate new methodologies and principles more rapidly. And it’s also by looking at the way in which they have utilised their employees and educated their employees and incentivised their employees to take up that new technology, rather than feeling threatened by it.
“This is a particular issue, I think, in healthcare because there are concerns from people that think that, for example, technologies like artificial intelligence will replace people. But actually, I think the way to phrase this is that they will allow people to work more effectively and efficiently and to focus on those things that are harder to solve, those more difficult cases, and free them up to really engage with patients a lot more.
“So I think we have to look at how these large healthcare organisations can embrace being agile and innovative at the same time as still maintaining their ethical and legal responsibilities.”
Q: In what specific ways is AI already transforming healthcare delivery—and what needs to happen next to realise its full potential?
Jackie Hunter: “Artificial intelligence is already shaping the future of healthcare. It’s being employed in radiology, in pathology, in triaging patients and downstream in terms of being able to do more remote home care, and other implications for health services more generally.
“I think the issue to really realise the potential of artificial intelligence in healthcare is to ensure that you have a commitment to adoption across the healthcare landscape in a particular area. You need senior management buy-in, but more importantly, the users must be fully engaged. Because artificial intelligence in its implementation is not just technology—it’s also a social science.”
Q: What are the most urgent ethical considerations around AI in healthcare, and how can they be addressed responsibly?
Jackie Hunter: “A lot of people are worried about the ethical challenges of artificial intelligence—and they are right to be so. First of all, the quality of the data is really important. For example, when you’re developing clinical trial algorithms, you must really look across a whole range of patient populations—incorporating different ethnicities, socioeconomic class, etc.—for it to be truly representative. This is especially true where people are using synthetic data to enhance the size of their training sets.
“The second ethical question is really about bias—not just the data bias but also the bias in terms of interpretation and downstream application of AI.
“Then, of course, we need to have transparency. How are the AI models coming up with their solutions? In terms of supervised learning, this is quite easy because you know how you’ve trained the algorithm.
“But for unsupervised learning, where you don’t really know the parameters on which the algorithm is making decisions, you really need to be able to delve down and explain how the algorithm is coming up with its recommendations.
“Demis Hassabis of DeepMind and now at Isomorphic Labs says that one of the key things he’s looking to do in his organisation is to develop AI solutions where the AI will come back and tell you how it’s actually come up with its recommendations.”
This exclusive interview with Jackie Hunter was conducted by Mark Matthews of The Champions Speakers Agency.
