James Borzi is the executive vice president and chief supply chain officer at Baxter International, a healthcare company; he joined Heidrick & Struggles’ Fabrice Lebecq to discuss how AI is helping leaders of the supply chain function across industries deliver value. Borzi shared how AI was rolled into the function at Baxter, as well as his perspective on finding the talent needed to make the most of these tools and managing the culture changes necessary to integrate the tools into ways of working. He also shared how he approaches balancing the opportunities of AI with its risks both ethical and sustainability-related; how he sees AI continuing to optimize the healthcare supply chain; and what it means to him as a leader to lead in an AI-enabled world.

Below is a full transcript of the episode, which has been lightly edited for clarity.

Welcome to The Heidrick & Struggles Leadership Podcast. Heidrick is the premier global provider of diversified solutions across senior-level executive search, leadership assessment and development, team and organizational effectiveness, and culture-shaping. Every day, we speak with leaders around the world about how they're meeting rising expectations and managing through volatile times, thinking about individual leaders, teams, organisations, and society. Thank you for joining the conversation.

Fabrice Lebecq: Hello, I'm Fabrice Lebecq, a partner in Heidrick & Struggles Brussels office and global head of the supply chain and operations offices practice. This interview is one in an ongoing series exploring AI and its impact on leaders across functions. That is, how they are embedding AI tools into their teams, how they are managing its use to drive performance, and how they are adapting their leadership skills and capabilities to best address the challenges AI presents and seize its opportunities. In today's discussion, we will explore the evolving role of the chief supply chain officer in an AI-enabled world and gain insights into how transformative technologies are reshaping supply chains in healthcare. I'm very excited to speak to James Borzi, executive vice president and chief supply chain officer at Baxter International. James has been instrumental in driving supply chain resilience and digital innovation in the healthcare industry, and his strategic leadership in leveraging AI and advanced analytics has not only optimized Baxter's current operations but also ensured the continuous delivery of life-saving products during challenging times. James, welcome, and thank you for taking the time to speak with us today.

James Borzi: Thanks, Fabrice.

Fabrice Lebecq: Jim, to kick us off, can you give us an idea of how widely Baxter is using AI?

James Borzi: We take a look across the business. So we're using it for business issues, supply chain issues, manufacturing issues, data management across the company. So it's widely used at Baxter.

Fabrice Lebecq: If we drill down a bit more specifically into your function, how has AI helped you deliver value in the context of the integrated supply chain?

James Borzi: I'll start with manufacturing. So using AI from an improvement tool to improve things like OEE, waste reduction, quality inspection across the planning—demand planning, particularly—and looking for patterns and cues that would help us do better both demand and supply planning. And then from a logistics perspective, route planning, distribution optimization, pick order optimization. And then, you know, I think one thing [that’s] key for everyone right now is really understanding the impact of tariffs and how you may use an AI tool from a routing perspective, to minimize the impact of the tariffs that are being considered.

Fabrice Lebecq: Would you say the application thus far has been more, let's say, directed towards risk management or value creation?

James Borzi: I think both, to be honest with you. I think from a risk perspective, looking at areas that provide risk to the business, but using AI as a tool, again, to mitigate risk on things, for example, like quality, where you could use AI as a means to inspect self-learning inspection systems, vision systems. But also an improvement tool across the enterprise, particularly where it comes down to really providing opportunities in the manufacturing and supply chain space, those items I mentioned, but other things like predictive maintenance to ensure your asset utilization is being improved. Basic things like training and assessment of new hires through virtual reality, ensuring that we are really looking at areas of opportunity across the broader spectrum of the business, down to ensuring that people on the factory floor are wearing the correct PPE, and really ensuring that they're safe and they're wearing the appropriate PPE for the jobs that they're doing.

Fabrice Lebecq: So obviously, you've been busy with that for some time. So, if you walk us through a bit, through to the inception of that. So, could you share with us how you've actually rolled AI into your function? I mean, who led the charge? Were there any specific challenges that surprised you? Any sort of culture modification, culture changes you found were needed? So it's a big topic, but I mean, help us understand a bit beyond the technology, how you've been able to bring that within the organization.

James Borzi: I think it's come down to really we're all data overloaded, from the devices we carry every day in our pocket, to the data we analyse through the various systems we use on the job. I think AI has really helped make that data relevant and is helping us not just introduce AI, but integrate it into our business processes. I think it's really come down to making sense of the data and providing data in a format that's useful to the person who's going to use that data. We have spent a lot of time—clearly it's a cultural transformation, I think, learning and using AI to aid both in job performance and as a means to be more impactful and efficient use of time, effort, and also the data that's available. We've spent a lot of time, particularly in our advanced engineering team, looking at the ways to be able to use AI in a constructive manner. And when we've targeted specific areas, we've run pilots and focus groups to introduce AI to help solve the problem that was a very relevant problem for the team. But that adapting what I would call real time with the input of the team, that trial and error and improvement process they go through, we found that the AI tools that we implemented were more impactful and adopted quicker because people were involved in the process. I think from a leadership perspective, the skills have evolved as well. You have to be open to both the change and the technology. But I think, you know, much like when robotics were introduced, I think people had to understand how they were being adapted to the process and how they were really helping them solve a particular problem. The same thing is really [true] with AI. And then I guess the last thing I would hit on would be really the talent that you're trying to source. You need leaders who are both tech-savvy but really open to change and not hesitant to both adopt and teach AI and how that can really, again, drive impactful results for the business.

Fabrice Lebecq: On that last topic of talent, did you face any specific issues recruiting or attracting the needed talent?

James Borzi: I think our bigger challenge was with our, you know, existing employee base. Finding the right talent, obviously, particularly with everyone looking at how to utilize AI, obviously, it's become a tighter market, but we have found very good data scientists [and] AI experts, that really help us drive our AI agenda. But it's really getting those folks that are new to AI to really understand what it is, how it can help them with their particular job, how to be able to use data more effectively in their day-to-day, and again—I go back to running the pilot and really engaging those people and getting them firsthand experience and knowledge on how AI can really be beneficial to their day-to-day job and their job performance.

Fabrice Lebecq: So obviously you talked about managing cultural change and getting the, let's say, the legacy leaders to the next level on AI. I mean, if you look at your organization, have you maybe created new roles, maybe re-scoped some roles, or extended your leadership team to cope with this change?

James Borzi: Yes, we completely revamped our advanced manufacturing engineering team, and really have staffed them with what I would call AI experts, technology experts, as well as integrating and working with our IT partners. I have a vice president of IT who sits on my staff, along with my advanced manufacturing engineering leader. Together, the whole team partners on what I would call identifying the opportunity, putting together that that pilot that I explained earlier, and really getting everybody's hands-on experience in implementing AI to help us at the end of the day, drive the business forward. We have really, I think, a great team at Baxter really embracing AI, and I think we've seen significant results in where we have implemented it. And as I mentioned earlier, everything from manufacturing, to supply chain, to actual business results, we've been able to see the improvement in those areas with the adoption of AI.

Fabrice Lebecq: There's no doubt, I think, that AI is obviously one of the key priorities in the minds of many executives and certainly chief supply chain officers. But it's also seen sometimes as kind of a bit of a double-edged sword, bringing opportunities on the one hand and potentially on the other one, some ethical challenges. So, how do you approach basically those dynamics as a leader? If we take an example of sustainability, organizations have been focused on sustainability for a long time. Now we know, obviously, that AI is not super sustainable as such. Any views on how we are going to go through that, through that basically conundrum?

James Borzi: I think it's, it really centers on, ‘AI isn't the solution to every single problem.’ I think you need to start there. I think you need to understand very simply what problem it is that you're trying to solve and have that open discussion with the team. I think the second thing is you're not always going to have the right resources within the existing team, and it's key that you're sourcing good partners, where need be, that have those tools and expertise, because you're not going to have the full basket of everything that you need at your fingertips. Nor do I think that that's the right path to go either, because I think people will tend to overload it, versus really understanding: Where do we want to apply AI? why do we want to apply it, and what results and improvements are we expecting from that? And then you take a look at what resource requirements you have and where do you have internal resources that can help, and team members that can help, versus where do we need to source good partners for specific tools that we want to implement to solve that said problem? I really think—this is an old adage, but I would tell you: It comes down to people, process, and tools. I think that's the most critical element when you're implementing AI, is that you keep that fundamental concept in the front of everybody, and then I think you make the right decisions as you move forward.

Fabrice Lebecq: I mean a subsidiary question on that one. If you look, if you were to pull actually your organization, where would you think the cursor would end, between on the one side fear and on the other side the excitement about AI?

James Borzi: Yes, I think if there were a dial on that schedule or that spectrum, it would be leaning towards excitement. I think early on, people were still trying to grasp what AI was, how it was going to be used? Is it going to eliminate everybody's job, to more of a tool to really help solve a problem. And whether it's a data problem or you're doing inspection through a vision system, a self-learning tool, or preventative maintenance, how do you improve your forecast accuracy? I really think it comes down to people really understanding how AI is used, and really, for us, I think it's really pointing towards the excitement scale versus the fear scale.

Fabrice Lebecq: So let's maybe switch a bit to, I mean, more industry-specific. You're in the healthcare supply chain, obviously. So I mean everybody remembers still the, obviously, the pandemic. How do you see AI evolving in the future to ensure that we can further secure and optimize the healthcare supply chain?

James Borzi: Yes, I think in a lot of ways it can help you understand more of a risk-based approach to your supply base, but I'll give you a very practical example that we've seen. During the pandemic, everybody remembers when the ship got stuck in the Panama Canal. It literally took us weeks to understand what we had on that ship, and by then, we were essentially waiting in line, if you will, to get prioritization, to get our containers moved. Versus last year, post implementing some AI tools, when the ship was hit in the Indian Ocean, we knew within two minutes what we had on that ship by SKU; we were able to be front of the line for rerouting of that material—we had, you know, other boats lined up, planes, etc. So just by implementing that tool and standing up our own control tower, we were able to really understand all of our material movements globally, in real time. And I think it just gives you both an advantage, but also a clear picture of your risk and mitigation, strengthening the supply chain significantly compared to, let's say, where we were three years ago.

Fabrice Lebecq: Excellent. So that's the state of AI today, which I think is, I mean, through that example, shows us how big of a leap has been made, certainly in the areas of supply chain. So now, if we turn back to leadership, what actually does it mean to you, as a leader, to lead in this AI-enabled world? How does that maybe reshape your leadership style and priorities?

James Borzi: Yes, I think the adaptation as an improvement tool and really connecting the dots for people, if you will, on how AI can be used to solve problems, improve business results. And most importantly, ensuring that you have the right team around you, both from a technology perspective, but also people that, to your earlier question, really tip that scale around excitement, understand what AI can do, and how to apply it. I think the combination of those things, from a leadership perspective, is really the fundamentals of what you need to be successful here. But also, I think it's ensuring you have the future talent being developed for the next generation of AI tools. And really, there are some really exciting things out there that people are looking at that have great adaptation to, particularly in supply chain and manufacturing, that I think we’ll continue to develop and look at. But at the end of the day I think it gives you also a competitive advantage, because you're getting results that, quite frankly, your competitors can't achieve, number one. Number two, you're getting to those things at a much faster pace, which both combined, I think, gives you a competitive advantage. So from a leadership perspective, I think it's really being open, understanding the people that you need, what processes and business results are you targeting, and then ensuring again you have not just the right tool, but the right partners and team behind you.

Fabrice Lebecq: So, in terms of actual skills and maybe changing or evolving skills, what are those that you believe leaders will need to thrive in the future?

James Borzi: I think from an engineering perspective, days gone by where you had what I would call a particular engineering expertise, whether it's mechanical or electrical, have really changed today, where people understand—new graduates really understand how AI can benefit their particular specialty and job, and really how those things are integrated into both the knowledge base but also the technical approach on how problems are solved. So ensuring you have, from my perspective, a good balance of core engineering, as well as new talent that understands those AI approaches, tools, and applications. And I think,, if you do that, you have a very successful mix, particularly in the engineering space but also in the specialties of fulfillment and planning, where you have implemented advanced planning tools and how AI is integrated into those tools and how it can be used. There are some great tools out there that have AI embedded, and if people aren't utilizing and pulling those levers, both in the planning and fulfillment space, you're really not getting your full money's worth, if you will. So really understanding the tools that are available and how AI has adapted to and integrated into those tools, is key from a leadership perspective as well.

Fabrice Lebecq: On that specific point of, let's say, new tools, any emerging technologies or tools that you really have an eye on, and probably more from a functional expertise here?

James Borzi: Yes, one is rolling stock forklifts, if you will. I think a lot of businesses still require the use of those. We're targeting zero in our plants, but when you get into, particularly in the fulfillment space, you need those to load and unload trucks. It still provides us a great opportunity for improvement, and there are a lot of new technologies emerging that really excite us in that space. And I would say the second one is just the application of humanoids, whether it's repetitive work or you have somebody in a position that requires a very tactical approach to the handling of material. Some of the advancements that they've made in that space are very exciting and I think provide future opportunities for everyone who's looking at AI. And then I just think the speed of advancements in this space, and the tools that are available and going to be available in the future, is something everyone has to ensure they have a good way to stay up on. Because it's a very fast-paced change, and if you're not personally engaged in that, you need to be, your leadership team has to be. And again, as I referenced earlier, I think it gives you a huge competitive advantage to really understand that how it's applied, not to mention also what's coming down the road from a technology perspective, that could be a benefit to your business.

Fabrice Lebecq: Jim, based on I mean your breadth of experience that you shared some highlights of during the past few minutes, what would be a piece of advice you have for peers or leaders of other functions who may not have made the most out of AI thus far?

James Borzi: I would encourage everyone to make AI a part of your business improvement, your continuous improvement toolbox. I think a lot of people have implemented different OpEx tools and Lean tools. I think AI is a great tool, and really dip your toe in the water, pilot something relative to AI, and I think everyone will be quite surprised by how quickly the improvement comes. But again, you've got to have the right team. You have to ensure that the team that's engaged understands what problem we're trying to solve. I think that's an early learning. If you don't do that, you can get mixed results and also not get the targeted improvement you were looking for. And then, last but not least, I think it's again a people process and AI as a tool to really implement improvement across the business.

Fabrice Lebecq: Jim, thank you so much, it's been very insightful. Thank you for being with us today and taking time out of your busy schedule for this podcast. So, thank you so much.

James Borzi: Thanks, Fabrice.

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About the interviewer

Fabrice Lebecq (flebecq@heidrick.com) is a partner in Heidrick & Struggles’ Brussels office and global head of the Supply Chain & Operations Officers Practice.