Reckitt, a global manufacturer of everyday health and hygiene products, recently embarked on a bold effort to simplify its business by focusing on core brands. A key part of this journey is embedding AI into its “Fuel for Growth” strategy.
CEO Kris Licht is spearheading this shift. He recently sat down with BCG CEO Christoph Schweizer to talk about taking a deliberate approach to how AI can create value. The following interview has been edited for concision.
Christoph Schweizer: Kris, you made a decision that AI would be central to your organization’s growth strategy. When was that point, and what triggered it?
Kris Licht: When ChatGPT was released in late 2022, I was running our global health business and was not yet CEO. I took my leadership team to San Francisco, and we spent a week immersing ourselves, figuring out what the technology could do and where it might go. That was a pivotal moment. We decided this was one of the few things worth going fast on—worth real investment and real time. And it was important that we engaged everyone in the journey.
How did you decide the best way to frame the program, what function to focus on, how much experimentation to allow, and how rapidly to scale?
The first choice was to go fast. And the second decision—and I think this is the most important choice we made so far—was not to go out and buy whatever people were selling us.
We took a first principles approach instead, and said, “We want this to change the way our whole organization works.” To figure out what that would look like, we used good old time and motion studies and mapped the work people were doing in a given domain. Before we deployed a tool, we studied what people did, where effort was being spent, or where handoffs or complexity slowed things down.
That has turned out to be a profound exercise. It helps us understand where AI can create value by enabling a different way of working.
You made the choice to go right into the heart of what makes you win, starting with marketing and R&D versus a support function. What drove that choice?
We thought these tools would change the game on what “good” looks like and what excellence requires. Marketing drives our growth, and R&D drives our innovation, so the stakes were highest there. It was counterintuitive, but starting in those domains forced a more serious conversation. It was not simply, “Where can we use AI?” but “How are we trying to change the company?” Once we had successes in these harder domains, it proved something to the organization: if it works in marketing and R&D, it can work anywhere.
One of the things I’ve observed in my own company and at many of our clients is that people say, “Yeah, we tolerate failure, and there will be some of that.” But reality can feel different. How did you manage this at Reckitt and evolve the culture?
You have to keep people focused on the long term. One use case may fail. One piece of the investment may not generate a big return. But as long as, in aggregate, you’re moving forward, you’re on the right path.
I’ve found empathy to be one of the big unlocks. You give the model a little space, you interact with it more productively, and you are less disappointed when it doesn’t do exactly what you wanted the first time. Ownership also matters. The executives who deployed AI in their functions own it because they cocreated the solution. The foundational work they’ve done is now helping us move faster in later waves of expansion through the company.
AI models get better with every release. So the question isn’t about the technology itself, it’s about how your organization embraces it. That has big implications for talent. How are you approaching this and ensuring your teams build the right expertise?
One of the things that we have to figure out is, “How do we create mastery in our more junior people?” In many industries, including ours, junior people previously developed mastery by doing a lot of the basic work.
But AI is reducing the most repetitive and least interesting parts of work, which makes many jobs better and the output more consistent. But this means we have to think harder about career paths and capability building. How do people learn more about AI and its capabilities while simultaneously developing deep functional expertise? We have not fully cracked that yet, but it is one of the most important questions.
Empathy, judgment, and an ability to bring people along are differentiating factors in an organization’s success. You’ve been at the forefront of this AI transformation. What advice would you give to other CEOs who are trying to move beyond experimentation?
Be clear about the impact you want to create, then work backward. What work has to change? What analysis is needed? What design choices have to be made? What needs to happen for the value to show up?
There are many ways to approach AI, and I would not claim there is only one right path. But for us, the first step is a hard conversation about how you want to change your company. Plenty of people have strong products, but buying technology comes far down the line.
What has helped you lead this as CEO?
Curiosity! I found myself in a panel presentation about how AI enabled the discovery of entirely new compounds. It immediately captured my imagination and made me wonder what that kind of capability could do for Reckitt.
When things get hard or when we have to revisit our assumptions, I continually go back to that moment. It reminds me that this is worth doing despite all the challenges.
