Andreas Welsch: 0:30

Today we'll talk about how you can successfully adopt. When you have the right mindset as a leader, and who better to have talked about it than someone who's actively championing that? Matt Lewis. Hey Matt. Thank you so much for joining.

Matt Lewis: 0:43

Andreas, thank you so much for having me back on the program. I'm thrilled to be here. Being on the show last time was transformative for me and for my directions. I'm so happy to be back with you and with the audience. Thank you for having me, and thanks for the time for everyone watching.

Andreas Welsch: 0:58

So great. You're one of the few that have actually been on, the show for three times already and it's always an enlightening conversation when you're on. So I'm really excited for what we'll cover today. But for those of our audience members who might not know you, maybe you can introduce yourself real quick, who you are and what you do.

Matt Lewis: 1:15

Sure. Happy to do it. So my name's Matt Lewis. I'm founder, CEO and Chief AI Officer at LLMental. I've been in healthcare and life sciences for my whole career, about 27 years. I started in data science and advanced analytics at a firm that is now AbbVie. It was Proctor Gamble personal healthcare at the time. I've been in artificial intelligence for about 18 years. Most of that time was not nearly as fun and exciting as it is now. Prior to starting LLMental, about two and a half years ago, I was Chief Artificial Intelligence Officer at Inizio Medical, a large private equity owned life sciences consultancy, and now progressing forward into the ecosystem in a kind of general AI native platform as enterprise organization, solving those problems that need solving and helping to improve patient outcomes.

Andreas Welsch: 1:59

I think that's so I important, such a great mission. Especially right in these times when people are wondering what is it with AI? Is it going to replace me? I'm feeling a lot of tension and stress and angst. Championing the mental wellness aspect is critical. I think so. Super excited to see you do that. Now maybe in good old fashion, should we play a little game to kick things off?

Matt Lewis: 2:23

Sure. Let's do it.

Andreas Welsch: 2:25

So let's do this. So this one is called in your own words, when you or when I hit the buzzer, the wheels will starts spinning. You'll see a sentence. I would love for you to answer with the first thing that comes to mind and why, in your own words, to make it a little more interesting. You only have 60 seconds for your answer, so should we go? Let's do it. All right, so if AI were a book, what would it be? 60 seconds on the clock

Matt Lewis: 2:53

Bible.

Andreas Welsch: 2:54

Okay. All right. And why?

Matt Lewis: 2:57

Cause it is that meaningful and means something different to everyone, and it touches your heart, mind, and soul in ways that are possible to make you be the best version of yourself.

Andreas Welsch: 3:07

It's super concise and obviously super in inspiring too. Wonderful. And, with Easter just around the corner and Passover not too long ago, right? Super timely now from, that holy script if, you will, moving on to another holy and sacred topic which is how do you actually bring AI into a business successfully? And I know you've recently held a workshop at the World Economic Forum for a large number of CEOs to help them better understand that. And I'm just curious, what are CEOs asking these days about AI when it seems like there's so much talk chatter and so many different vendors whispering in the air. What are they asking about when it comes to AI?

Matt Lewis: 3:52

Yeah. First of all, you know this opportunity to go and speak to the World Economic Forum's New Champions program, which I did last week, was really the highlight of my professional speaking career. I've been in front of the C-Suite and boardrooms, customer conferences, professional associations, medical groups, patient advocacy, healthcare delivery, you name it, I've done it. But this was really a special you opportunity to engage with this community. The folks that were in assembly were world leaders, business executives some allied closely with heads of state really moving the ball of innovation and responsibility up the hill. And it was a really humbling experience. Everyone was there by choice and was there fully attentive and engaged and you speak, I know Andreas at conferences and the rest. And it's not always the case that you're in front of an audience that's A, paying attention and B actually wants to take what you're saying back to their place of work and. Make it help their people and help their people do better and be better as a result. And being in an environment like that was really quite wonderful. I, was fortunate enough to be part of the program before I was actually on the stage and, stayed around for what followed, and it was amazing discussion about global public health and global economy, geopolitics. And the time that we're in right now across the. The world's trajectory is an, interesting one. Having informed citizens globally is, critical that we think about where we are and where we're going. So it was really just a, delight being amongst that group. I think one thing that was really interesting is that the, group there was all like, very interested in augmented intelligence, understanding where AI is and where it's going. They're all adopting and utilizing artificial intelligence in their businesses and their places of work. Many had experience with RPA. They have a history and a legacy where they've seen automation be helpful in some regards and been doing things like copilot and other implementations in their current environments right now. But like many of us maybe not seeing the full benefit of a full AI transformation that they would like to see, but not quite understanding why. Really a great group to come across and, engage directly with. The talk that I gave was really focused on mindset and really thinking about what proportion of the success of an artificial intelligence transformation is due to algorithms. The models, the platforms, the things that we're talking about. What is likely to be a contribution of underlying tech and the considerations of the broader kind of digital kind of. Ecosystem that enterprises are currently considering, if you will. And then what is the balance that is really contributed by people, by leaders, by executives, by processes, and by the other human factors within the environment. And I've been talking about this human factors consideration for a long time. But there, there is a lot of research now that suggests that. At least 70% of what makes or breaks an organization with regards to AI success is actually people driven. It is not about the platforms, it's not about the models, it's not about the algorithms. It's not about whether they have the right kind of technology or technologists on board. It's really about the direct experience with the, technology and what their disposition, their mindset their mental wellness, their considerations are as they progress forward into the ecosystem and. This group was quite interested in, that consideration and had a number of kind of questions and thoughts around. How practically they can understand where they are on the kind of mindset continuum, if you will. And then whether those things are even amenable to intervention. Does someone just show up with a fixed mindset, no pun intended, and stay there forever. Or are these things that can be trained, can they be taught? Can take someone into a workshop and change the way that they think so they can be a better leader, be a better manager, be a better. Colleague and work better with customers, and that was most of the discussion around what are the kind of facilitators that enable success versus those types of barriers or things that kind of frustrate the ability of an organization to accrue value.

Andreas Welsch: 8:05

In all that you have shared and I always hear that passion for the topic and, helping others, helping leaders understand how they can elevate themselves and their organization and their people. I think that's just so fundamental to the things that you do. So hearing what you're sharing and what you've shared with them, I think is a profound and impactful message, right? It depends also on your leadership and your mindset as a leader. How you take that to the organization, how you show up so that your people can show up as their true selves as well.

Matt Lewis: 8:40

Yeah that's really critical and I think it really can't be overstated both the subject of what augmented intelligence is able to enhance and amplify and extend and optimize is essentially at the core of it, it's a people solution. What we're really doing is transforming humanity. We're helping to enable and augment human potential. That's really what we're doing. And at the same time, it is also both subject and object. It's the people that are helping others transform. We're as leaders in the business as enterprise executives. We're the ones that are putting that into the world. The way that we show up, the way that we are authentic and vulnerable and come to our colleagues in the business is critical. I get we, when we run large workshops or we implement technology, when we build platforms and we design systems, how we tell teams of what is now and what is likely to exist in the near and far future. Is critical because they ultimately will decide whether or not they trust us as leaders, whether they want to work with or for us, whether or not they can imagine or envisage a role for themself in the organization. In two months, two weeks, two days as this technology rolls out. And if they don't have that trust and they don't believe that we're in it for them. Then no amount of software or systems is gonna change that for them. So it's, really critical that whether we're in healthcare like myself, or life sciences or human services, or really any business, all our businesses are people, businesses. And the most important thing is that we connect with the people in our businesses and try to do right by them.

Andreas Welsch: 10:37

Now doing right by our team members. It starts also with us as leaders. And there's so much hype and so much noise in the market about AI. How do you recommend leaders, CEOs determine what is actually factual and what is just fictional?

Matt Lewis: 10:58

Yeah. Yeah. I think this is one of those perennial topics within the augmented intelligence environment that you know I, think we all kind of wish that it'll go away, but at the same time we'll be worried when it does go away. I think you it, lives on, a little bit of a distribution curve right there, there is a lot of hype. But now also a couple years into the generative AI wave, there's also a lot of hope, and I think it's not like that the, these things are on opposite ends of a spectrum there both together juxtaposed one right on top of the other. It's it might be the case that in a large enterprise, like a large life sciences company, for example. There could be a division where there's still a tremendous amount of, hype and they haven't yet seen that hope. Maybe because within that division, say like within continuing medical education or within customer services or within supply chain, they haven't yet architected a, strategy for AI, haven't hired a Chief AI Officer, haven't built a POC or project to see the value yet. So for them, it's still vaporware and like misty, if you will. Whereas within another division of the same company, they're quite mature and they're already progressing towards the hope side and see more help than they see hype. So it's, not like it's either fact or it's kind of fiction. It's really both end all at the same time. It's just not evenly distributed to use a William Gibson kind of expression where the future is here, it's just not evenly distributed. I and I, it is like that in a lot of big enterprises where there, there is a lot of true value being accrued, but it's not evenly distributed across the whole company. And you, if you look at one pocket, you might see a lot of bullshit because people just don't know any better. But if you look just down the corridor, you look at a different business unit, you look at different. They're seeing tremendous impact just because of where they're in the market and their stage of maturity. So I think it does take a sense of discipline to understand where there's alignment between strategy and operations and people and, culture and other considerations, and also to know what can actually be done in this environment.

Andreas Welsch: 13:03

Now I've heard different approaches by, different leaders how they go about this. And, some have shared that they have started to catalog the use of AI in the business that they've reached out to different business units. That they basically put their ears to the ground, where is AI actually happening? Where it being implemented in our large enterprise? And then find these pockets of innovation and elevate them and say, Hey, look. This is what's happening maybe in Portugal. This is what's happening in in a vaccine division. That's what's happening in, oncology and so on. What's your recommendation there? How do you bring all of that innovation that's happening in different parts of the company together? Isn't, that the, role of the Chief AI Officer? Or are they overstepping if they try to elevate that?

Matt Lewis: 13:51

Yeah again, it really depends. It's not a great answer for, a a podcast and for a wide audience like this, but it really depends on a number of factors like the stage of maturity of the organization itself, like what their disposition is with regards to transformation whole, or in part like where what they're actually. Doing with regards to building their own intellectual property. Are they of a nature where they're building a lot of that own IP in house? Are they buying or partnering? And I think we, when we had this conversation, you and I, maybe two years ago the, there was still a, healthy consideration out in many large verticals where many firms were building their own models or actually building them from scratch or doing a lot of fine tuning and other kinds of considerations. Now, I think a lot of the, consideration has shifted from that. Almost entirely certainly to a great degree where unless are born out of Silicon Valley or y come or type of consideration to build entirely from scratch and a large enterprise is not happening nearly to the degree that it used to. And if it is happening, it's not getting much traction. So it's a very different world now than it was even 18 months ago because like a weak generative is like a quarter in the real world. So things just move very quickly. And if you don't have the kind of staying power to really. Turn that into, value, the market will tell you where you're, where you need to be. So I think it, there is definitely a thought towards cataloging use cases and also seeing what's working. I think some of the recent literature that suggests the value of native AI within different environments, like the study from Procter and Gamble, that was shared just recently outta the the team at Harvard suggests that even just very general purpose. Generative working in concert with a single person is more effective than a team of people working without AI. And there are a number of cases like where this is happening across many large organizations where they don't even have a proof of concept or a pilot in place that just someone's using GPT, they have something on their phone and they're working now in concert with AI. Much more efficiently and much more effectively than with a team that is human only essentially. And a lot of this is not cataloged because it's essentially like secret cyborg shadow IT activity and, the business doesn't necessarily need to catalog all of this, but I think they need to cultivate it. They need to encourage it. They need to ensure that. The ways of working in 2025 become really the soil in which future work is, encouraged. Otherwise, people in those businesses will start feeling like this type of activity is not condoned. And if someone is doing this type of work at AstraZeneca and they feel like it's not something that is helpful with an environment, they're a very innovative shop. So it's maybe poor example, but another organization, they might feel like another. Life sciences organization is a better place for innovation and they might flee to go there because it's that's more likely to speed, time to value for, patients in this regard. So I think there is a place for leaders within the business to identify these kind of pillars of light, if you will, and cast a spotlight on them and show the organization. What good looks like, not so much to just put a big spreadsheet together and say, look, we captured this somewhere, but to really show people what good looks like and find a way to scale that brilliance, if you will. I.

Andreas Welsch: 17:11

I think that's a very practical suggestion, practical advice right there. So find the happy medium as, always, between looking for, these things or even if, you find them, elevate them, but don't just make a spreadsheet exercise. That's awesome. Now you mentioned something earlier and, obviously it's also the, title of our episode that a lot of it has to do with the leader's AI mindset, how we show up as a leader. To this transformation to our organization, how we bring our team members in parts of the organization along. But what does it actually mean? What does it mean to have an AI mindset as a leader?

Matt Lewis: 17:51

Yeah, it is definitely an evolving concept. I think Gartner really is one of the forebearers of, this, of consideration in their digital thinking, digital mindset, digital dexterity consideration that they offered maybe about eight years ago or so, where digital thinking is more than just like skillset and tool set. It is also mindset. And in digital mindset, you need to have a proficiency with the digital systems and skills of the organization. But it's also a way of working and a lot of it has to do with the sense of urgency with which leadership adopts its tactical and operational practices and the agility with which they operate them and can adjust to changes within the environment ecosystem. One quick example of this is this thought. A kind of exercise of how one becomes proficient in generative AI. Even as early as like early 2023, there was still a lot of discussion around for like professional services firms like the, large holding companies, agencies. I. Arms length consultancies. Does it make sense for firms like that, for example, to build their own models? And there were many groups trying to do that on their own, if you will. And then very quickly it became resonant that perhaps partnering or buying with a third party might make more sense to do that much faster than say the technology advances and innovations that occurred a decade earlier with cloud or a generation prior with the internet. And I think teams that were flexible and could adapt quickly. Recognizing that the market was shifting under their feet, didn't make those large capital investments to build technology that was quickly obsolete, that the market didn't need and still have the resources to invest in the future, if you will. Where groups that kind of committed to a, rapidly eroding past found that really just wasn't creating the considerations that they needed out the ecosystem. And it is that mix of. Having a sense of urgency to stand up a strategy that actually is reflective of the current consideration considerations, but also being flexible and agile to adopt and adapt as things move forward. Coupled with really an understanding of, what it actually takes to accrue experience on the ground. And I think this is might be a little bit controversial, but the, typical ways in which we upskill in artificial intelligence it, is. Probably the, most important responsibility that a leader in the business has in the modern era, but it, often isn't given the proper time and space and thought before it's actually rolled out to frontline staff. And I, the reason I say that is that, that I, you know, when we've talked and I've shared out in previous commentary and publications I, use this. Albert Einstein quote that the only source of knowledge is experience. You know that just doing a didactic training course where you share a lot of information about how Transformers work and what GPT is and zero shot learning and all the rest, and that's helpful to a point. But if you don't give staff, frontline staff, especially actual experience in the workflows that are gonna be relevant to their jobs, the tasks they're responsible for. And all you do is give them lots of modules of courses that help them understand what artificial augmented intelligence is capable of, and then there's a lot of daylight between the time that you train them and the time they actually apply it to their work. The literature in this is very clear and has been clear now for the last nine to 12 months. All that happens is that their fear levels go up, way up, their anxiety goes through the roof, and then productivity plummets between 30 and 40% within the first three of months post-training, and it ends up having the exact opposite effect that upskilling is desired to produce, which is instead of them becoming more competent and productivity improving, it actually plummets to the point that people that are on the front lines. Feel like almost that AI is gonna take their job. They become like terrified of it. And then the AI adoption and the transformation really can't work because most of the people that have to do the work are so fearful that they can't really do the work that's required. And as leaders, we've almost done this to them. So it's like the, antithesis of what we desire. We want people to be embracing and engaging and running towards. The machine, if you will, as opposed to running away from the danger. But unfortunately, but by just telling them, look, this is amazing, and then not giving them any direct exposure experience to it, it has the opposite effect. And we, create a problem that then needs to be solved.

Andreas Welsch: 22:17

So two thoughts here. One is I'm thinking about an analogy and something like driving a car comes to mind, right? You show somebody this is a car. Here's the steering wheel. Here are the pedals. Maybe you shift manually or automatic, doesn't matter, but you don't actually let them sit in the car or have them driving have them have driving lessons. So you tell'em about driving a car, maybe even a race car. But by the time that they actually get to sit in the car, they're so afraid. Although they know everything about physics and combustion engines and acceleration and whatnot did. They're too afraid to actually take the wheel, right?

Matt Lewis: 22:52

Yeah. It'll be the same type of thing. If you, if say you rewind back to 1906 and do that exact demonstration at the same time, you take away their horse and buggy and you prevent them from doing anything in that similar reign, you, you don't let them buy another horse. There's no way that they can produce they can't do anything on the farm. They can't get to town, but you told'em that the automobile is coming. They know that it's gonna take away their horse and any mode of transportation they have. But they don't actually have access to it. So all they have is the fear that everything they have known since they were a child is disappearing. But the new thing isn't there yet. So the natural reaction for most people is just to be terrified. And then in most businesses, you don't have leaders standing up and saying, look like I don't have a crystal ball. Augmented intelligence is likely to produce significant value. The roles might shift, the organization might evolve. But it's likely to create new opportunities for everyone here. And here are some of the things that it might mean for you in your job in the near future. And here's the first way of starting. Here's this pilot project that we're gonna pull you into, and we'd love to get your feedback and perspective, but a lot of people don't do that in an interim, you just have people coming home and they're quite scared. And as a result that, that fear turns into lots of negative outcomes for people and for professionals.

Andreas Welsch: 24:06

I think all the things that you mentioned that, we need to do are, then the ones that help leaders promote that mindset in the organization. Be vulnerable to some extent, right? This is new for pretty much any leader and very few have the answers if, anybody even has the answers. So I think I there's no shame in saying, Hey, look, we are going through this transformation, this is what it will eventually bring. But there's some interim steps and maybe there's also some uncertainty where we need to figure this out together or where I'm available. For, your questions and, concerns.

Matt Lewis: 24:38

Definitely. And I think also it, the earlier part of what we were discussing is also resonant, where if organizations recognize that AI can potentially provide a lot of consideration of value to them as an enterprise. They, might need to crawl before they can walk, before they can run. And you know that, that might be, for example, the first thing they might need to do is to bring someone into the organization as the head of AI or chief AI officer, and it, might be prudent for them to have that person be enrolled for a period of time, three to six months before they start figuring out, are we gonna build this technology ourselves, which is probably unlikely in 2025/6, are we gonna partner with the third party firm? Are we gonna work with a startup in the ecosystem? And then are we gonna start doing real upskilling and strategic enablement with our teams the right way? To think about how we work in partnership with our teams, which, because it is a people oriented consideration to progress forward rather than try to do everything all at once and then find that they, the results are less than what they had desired.

Andreas Welsch: 25:38

Now you've, shared so many great insights from on one hand your session at the World Economic Forum the other week, but also generally how leaders can build this AI mindset. And I was wondering if you can summarize the key three takeaways for our audience today.

Matt Lewis: 25:53

Yeah I think everyone's walking this path like at their own pace, so there isn't like one overarching consideration that everyone needs to do identically. But I think based upon the stage of maturity that, that everyone's at, I think AI is still one of those things that I. Reflects back to the person what's best for them and their own strategy. Un understanding for the organization at the enterprise level, where the organization is, what its strategy is, what they hope to achieve and, what parts of the business are best optimized or enhanced by artificial intelligence is the best place to start. Because knowing where there is friction, where there are opportunities for improvement is a good consideration to then determine what makes sense in the external environment to partner and to progress forward. Whether that means identifying additional leadership in house or whether it looks more externally from partners and those considerations. The, mindset piece is really critical and from a, time and a capital standpoint should be probably three quarters of the total investment. And thinking about not just what the organization looks like in spring of 2025, but what is it going to look like in the winter of 2030? And getting from here to there is, not just a matter of taking some chairs to the table and changing them around. It's a, real kind of transformation of what the enterprise looks like today to a moderate enterprise as roles and skills and tasks evolve. And it is changing the disposition from like the late. Legacy approaches to more of an agile, urgent sense of, action across the business. And thinking about if we do a pilot or a POC in late 25, how will it scale across the enterprise? Can we even take this into an organization of multiple billions of dollars of revenue? And is this something we want to be doing as a firm as we evolve into the future? Can we be competitive in this way? And then mostly in the thing that's most critical really is like thinking about it from. The perspective of, our staff, our frontline colleagues, people that are on the front lines that are talking to customers. Maybe if it's patient facing or clinical facing how, is this going to be received? How does it complement and enhance the work, the knowledge work of the people that really are using our products and developing or, supporting our services. And if we were with them across the table and they saw what we were doing. How does this enable them to make better decisions in a faster way that speeds time to value? And if it's not doing that, then we need to rethink how we're both either expressing it or considering it because perhaps it's not really truly supporting human potential. We just we're thinking that it should, but it's not quite there. And until it's, fully synergistic, it might need a little bit more work because we, should always be thinking about it with the human at the center and that idea of it. Artificial intelligence plus human intelligence really equals brilliance.

Andreas Welsch: 28:47

Wonderful. I love that. Such a powerful message, right? We need both technology and, humans, but put humans in the center of what we do, because at the end of the day that's where the value and where the capital is. So Matt, thank you so much for joining us and for sharing your experience with us. It was a pleasure having you on again and hearing how your advice leaders built at AI mindset.

Matt Lewis: 29:10

Thanks Andreas. Again, thanks for everyone for the time. Much appreciate it.