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Home » Leadership in the Age of AI – Paul Hudson and Lindsay Levin (Transcript)

Leadership in the Age of AI – Paul Hudson and Lindsay Levin (Transcript)

Here is the full transcript of a conversation between TED’s Lindsay Levin and Paul Hudson at TED conference.

In a thought-provoking conversation between TED’s Lindsay Levin and Paul Hudson, CEO of Sanofi, the duo explored the transformative impact of Artificial Intelligence (AI) on the business landscape, particularly in the pharmaceutical industry. Hudson emphasized Sanofi’s commitment to leading the pharmaceutical sector by leveraging AI at scale, highlighting the company’s aggressive approach towards integrating AI into daily operations to enhance decision-making and efficiency.

He candidly discussed the challenges of data transparency and the initial resistance within organizations to embrace AI fully. Hudson also addressed the broader implications of AI adoption on the workforce, suggesting that AI’s role is not about job displacement but rather about creating more meaningful work and driving innovation. The dialogue touched upon the importance of leadership in navigating the complexities of AI integration, with Hudson pointing out the shift towards younger talent driving change and offering fresh perspectives on AI applications.

The conversation also delved into sustainability and healthcare, underscoring the need for collaborative efforts to tackle global challenges. Overall, Hudson’s insights painted a picture of an era where AI acts as a catalyst for significant industrial transformation, urging leaders and organizations to embrace change boldly.

Listen to the audio version here:

TRANSCRIPT:

The Era of AI and Its Impact on Business

LINDSAY LEVIN: So, we’re living in an era with multiple overlapping disruptions that business is facing, and I want to dive straight in and talk about one of the biggest of those, which is AI. How are you approaching AI?

PAUL HUDSON: You know, AI at scale, it’s a whole big subject, of course, but for us, at Sanofi, we aim to be the world’s leading pharmaceutical company using AI at scale. Why and how are we going to do that? It’s pretty straightforward. We have 23,000 people using AI as often as every month, 9,000 people in the company using AI as often as every day. We’re boldly taking on the opportunity to completely disrupt the business. We don’t have a choice. It’s the fourth industrial revolution. It’s here whether we like it or not.

And it’s amazing how resistant people can be across organizations and across industries. But we’re all in and have been quite public about that. Our aim is to provide daily decision intelligence, to give people a sort of nudge in the right direction, to give them deeper insights, to allow them to be more effective at what they do. And it’s real. And it’s such a privilege to be involved in it.

LINDSAY LEVIN: I mean, you’re taking a very aggressive, active stance. What surprised you?

PAUL HUDSON: Well, a lot of things surprise you about AI. I mean, for some people it’s Skynet and Terminator. For some people, they confuse AI with cyber. I’m not saying everything is perfect, but I’m surprised at the number of CEOs or executives who — Their first response to an AI conversation is “Governance, controls, rules, principles.” Of course, everything has its place, but I think we have to be honest with ourselves.

If it is the fourth industrial revolution, which we believe it is, then hesitating, this fear that can take over, can deprive you of so much opportunity. And you have to go for it. I find that when you talk to lots of CEOs, they really are very hesitant. Some would say even frightened. I look internally, people are frightened that you get this radical data transparency. You can see their data real-time.

The Challenge of Data Transparency

LINDSAY LEVIN: And you’re experiencing that.

PAUL HUDSON: I’ve experienced that and still do. You know, people are often shocked that you may get the insight at the same time as somebody lower down the organization. And then there’s the lost opportunity to polish a slide deck and re-present it in the way that I’m supposed to be informed. It’s not a deliberate, sort of, misleading approach. It’s what people know. They get the insight, they craft the story, they push it upwards. And that’s life in many corporations.

For us, we get the data, I get the same data every level of the organization does. I get the insight exactly the same time. And then people say, “Paul, don’t look, the data is not 100 percent correct.” Well, make it correct because the data is live. So if you really jump in and make it correct, it’ll better reflect what you’re doing, right? But if we wait for perfection it’s simply not going to happen.

AI and the Workforce of the Future

LINDSAY LEVIN: So, we’re seeing fear and some of that, I guess, is not unreasonable. You know, we read reports about the impact on job losses, for example, to come from AI. I wonder what mindset you believe people need to adopt in the workforce of all generations, as they approach or we all approach this new future?

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PAUL HUDSON: You know, the adoption of AI in particular is not about jobs. And I know people will think that and inevitably, more meaningful work is created. And of course, some roles change or some skills don’t match. And therefore, you know, with the help of many of the people in the room, you get to reshape organizations. But in the end, it’s really about using artificial intelligence to create this real momentum of decision making and to be able to take such an advantage over the competition.

And we believe, I believe, that if you create more meaningful work and people focus on insights and action and less on Excel and PowerPoint and Word, then there is a chance that they enjoy their work more. Now it may lead to productivity gains, it may lead to efficiency. It may lead to all those things, nobody’s sort of denying that. But what I’ve discovered so far is when it does, people see it quite quickly and they put their hand up to do something else, or to focus more on insights than data crunching and aggregation.