Ep 57: Turning Process into Product with Wolters Kluwer EVP & CIO Mark Sherwood

Evan Reiser: Hi there and welcome to Enterprise AI Innovators, a show where top technology executives share how AI is transforming the enterprise. In each episode, guests uncover the real world applications of AI for improving products and optimizing operations to redefine the customer experience. I'm Evan Reiser, the founder and CEO of abnormal AI.

Saam Motamedi: And I'm Saam Motamedi, a general partner at Greylock Partners.

Evan: Today on the show, we bring you a conversation with Mark Sherwood, executive vice president and Chief Information Officer at Wolters Kluwer. With over 21,000 employees, they’re a global leader in expert information, software and professional services for over 100,000 customers worldwide. 

There's three interesting things that stood out to me in our conversation. 

First, Wolters Kluwer is building AI into every product. Moving beyond generic search to guidance professionals can trust using deep subject matter expertise to deliver precise, context-aware answers. 

Second, Mark is taking a pragmatic approach to AI adoption, starting with user productivity and real training, by identifying and targeting a few manual, high-leverage processes. He measures success through value brought back to the business, not just chasing shiny objects.

Finally, I was really impressed with the scale of Mark's AI roadmap. The team has individual projects that are quite impressive on their own, such as auto-generating SOPs from incident data. However, they're applying the transformation across every area of the business with more than 60 projects. Everything from contract lifecycle, the incident management and disaster recovery.

Mark, thank you so much for joining us today. Really excited to having you on the show. Looking forward to this one. Maybe to start off, do you mind giving our audience a bit of overview about your career, maybe your current role at Wolters Kluwer?

Mark Sherwood: Yeah, career. You know, I won't go back from the absolute beginning. But, you know, it's been technology roles from getting right out of school, a company called File Net, which ended up getting acquired by IBM. A technology company, document imaging back then in the day was cool technology. It's been a long a lot of years at Cisco Systems, both on the product development side and then switched over to it about halfway through, moved to Symantec security Company.

Which was absolutely an education. I mean, security was booming at the time, so it was a good move. And then got an opportunity for a CIO role at Nuance. Not a lot of people have heard of Nuance. It was actually the company that started Siri. So a lot of people have heard of Siri.

Apple ended up buying the licensing for it. And basically to all the engineers. But if people in the health industry have heard Dragon software, they do speech-to-text. That's where. That's a Nuance product. And then, Nuance about three years ago got acquired by Microsoft. So it's a big deal for the company.

And so I didn't actually expect to join Microsoft, but they, you know, they asked if I would come join them to play it, play around there for a while. I was at Microsoft for coming up, about two years, and then, I got an opportunity to move into another CIO role here at Wolters Kluwer. I’ve been here for nine-ish months at this point.

Evan: Nine months. It feels like nine weeks or nine years, probably at the same time.

Mark: That's. Wow. That's accurate. Yeah. I think I get my sort of satisfaction out of the role is, you know, if you have a need for sort of instant gratification, I'd say a career in leadership or management, it’s probably not for you because you, you don't get that, you know, you get it over a period of months or years, hopefully. But, you know, I think getting to see the business grow, but also getting to see the people grow, that to me is the sort of the magic combination that I enjoy, still stay involved with and still being, you know, part of a company that is, you know, continue to stay focused on that.

Evan: That resonates with me. I think there's obviously pains and problems, but, it gets bounced out when you see, you know, when you see a team come together, really start kicking butt, you're I’m not even contributing. They're set up to kick off in a great direction. 

For our audience that may not be familiar, can you share a little about kind of Wolter Kluwer’s scale and kind of like, what is the real, you know, scope of the global impact? 

I think that it's probably not as common of a household name, but I think people may be surprised about, you know, the impact you guys have in the world. Do you mind sharing a little bit there?

Mark: Yeah, of course I'd be happy to. And for anybody who's listening that has never heard of Wolters Kluwer, you're not alone. There's a lot of people that have not heard of the company. It's actually based in the Netherlands. My team is essentially, I've got about from an FTE, full time equivalent standpoint, about maybe 1200 people. So about a third or in most of us, but I think North America third or in Europe, not surprisingly, since the company is headquartered in the Netherlands and another third, I'll say in Asia, it's mostly in India, in Pune and in Chennai in India.

You know, the company has been around for almost 190 years. So if you haven't heard of it, you know, maybe, most people haven’t for one reason or another. You know, Edgar Allan Poe was still alive when the company began. So you can get a sort of a feel as to how long the company's been around.

So the company essentially has five sort of main divisions, and they range from we have a health division, we have tax, we have legal, we have corporate performance, we have financial. So it really sort of extends the gamut across a lot of different industries. And think about the goal really, is that we're providing this content and subject matter expertise out to professionals.

So, healthcare professionals, doctors, nurses, right, on healthcare side. Tax professionals, people that are, you know, preparing your taxes, making sure that they always have the most accurate data available to them, like literally at their fingertips. And then, you know, basically the company operated as that for many years. And then what's happened is the technologies being able to provide better capabilities into that data.

So we got a tremendous amount of subject matter expertise, like on-staff. And then looking at how they get access into that data. And so now more than 50% of our revenue comes from products that are AI-enabled. So now we're building AI capabilities into every product, literally every product we have out there now. So some, you know, came out initially a while back, some are coming out now, some are coming out, you know, in the next couple of months.

But basically providing this AI capability, much-enhanced capability to get exactly the information you want, again, right at your fingertips without having to go and do a traditional search of the internet where you get, you ask for something specific and you get, you know, 50,000 things and 45,000 of them are not really relevant to your ask.

So that's the goal is helping the users, you know, actually get to the data that they want, the information that they want as quickly as possible and as accurately as possible.

Evan: Okay, I got to come back to the AI topic, but maybe as follow up there, like you can maybe help give the audience a sense of scale, right?

When I was doing research for this talk with you, you guys have like 100,000 customers or over 100,000 customers. Did I get that right?

Mark: Yeah. Oh, definitely. Yeah. I mean, depending on how you count doctors and hospitals and offices and things like that, but I mean, it is it the gamut of companies – I don't know if I'm supposed to say all the companies –  but the gamut of companies, I'd say, I don't know the exact count, but without question, more than 100,000, all across. So again, you look at corporate performance, a tremendous amount of companies out there that want to stay involved in that, you know, just from the doctors and the healthcare providers a lot out there.

And then tax.

So all big, big, big names, I mean, all the names you would expect. The people who are out there preparing your taxes, maybe yours or maybe not yours. All are leveraging the knowledge base that we provide out to again, lots of different industries. Some of that you probably wouldn't think of like oil and gas industries, for some of the corporate performance testing and things that aren't normally associated, maybe with a sort of an information-type company.

But yeah, a lot of size-wise we're about, I think, 21,000 people, but 6 billion a year in revenue. So not a small company, just one that again, not a lot of people have heard of.

Evan: Unlike the other hype technologies, it seems like there's real substance here. But you know what? What's your view? Where are we on the spectrum of hype to substance and like, you know, what do you feel kind of bullish and bearish about? 

Mark: I think of it more la technologie de notre vie, of life. It is here. It's here to stay. It's not going away.

And to be fair, I've never experienced something like this in my career where you've got such a growth overnight, you wake up in the morning and you got all these new developments and new releases and you're looking at what else it can do. 

There's a category of companies out there. Ones that are of course, trying to monetize AI.

They're trying to sell you products and toolsets around it, which are great. But I also think they're they're of course pushing and they're making. Yeah, that's to me is the overhype portion of it is because they're promising and you can do everything. You know it can. It can make everything happen.

And then I think there's the under-hype part where it's capabilities. I mean, I still think we're just starting to scratch the surface right. There was, you know, sort of basic usage of AI. Everybody jumped on ChatGPT. And then now starting, you know, where companies and we're doing the same building out agents. And then, you know, having this sort of orchestration of agents together where they're taking on an entire workflow in the process.

So I think it has a foot in both camps where the ones that are trying to monetize the products are going to overhype it and say, you're behind. “The sale ends Friday! Buy now! Or you'll never get a chance!” Because, you know, there's a wave and you're trying to ride a wave here.

And you actually see that some of the things in the hype curve are further back to the left. And what I would have guessed, some things are, you know, moving forward. But I think Gartner is trying to get their own arms around saying, maybe it's not at the speed that we think it is because you don't know who to trust, right?

It's sort of like do you trust the company that's selling the product? You trust the company that's using the products? You have to look across everybody. So I it's the desert topping in the floor wax. You know, depends on how you use it. Depends on how you bring it into the company.

I do think, it's important to have it be viewed as: it is not a solution in search of a problem. But that it's there and you can leverage it to address whatever problems, issues, challenges, worries you may have. I hate to put it in a box and just call it AI, but the power and the capabilities are almost unbelievable to me at this point.

Evan: Yeah, it's quite amazing, for myself. I've been working on machine learning for 15 years.

Mark: Yeah, same.

Evan: Like every two months, the things I thought were insurmountable be difficult are now super easy with AI. 

Mark: Yeah

Evan: Who knows where this takes us.

Mark: I'm in. I'm excited to be on the part of the ride. You know. Where we can fit.

Evan: Yeah. So, you know, you guys are using firm because at some level, like the business about kind of sharing information and helping people make, you know, better decisions, right. And you obviously are using AI for that. Can maybe share a little bit about, you know, how you guys have approached that kind of AI adoption?

Mark: You know, from an internal perspective, you know, one that I probably pay more attention to just from being, you know, more of an internally facing role is when we when I joined, we started to look at all the work that's being done.

And we have our own, you know, we call it code games. But it's like a hackathon. I mean, I think a lot of companies run things like that, and there were so many great ideas that came out of it. We pick winners, but I hate to I hate to get to a point where we're letting, other great ideas.

You said, okay, maybe they didn't win, maybe they weren't the best, but they show great ideas. So we pulled them all together. At this point, we have 66 sort of, you know, the number probably grows every day, but we we tallied up 66 ways where we thought we can actually leverage AI in these situations to provide value to the company because that's, you know, part of what we're trying to do.

It isn't just a fun science experiment, right? We're trying to provide value. Three of them that have really bubbled to the top for us in I'd rather do, you know, five things really well than 50 things, sort of, you know, poke around at them or not, not, not achieve. So, you know, and I think this is probably a fairly common one is on the CLM, the contract lifecycle management, there's just so much data out there, and it's so great to be able to have a tool like AI that can parse through there and get exactly what you want and pull it out of, you know, we have a lot of contracts out there, but to be able to go in search and pull that out, I mean, in the past it was done with just humans. I mean, that was the only way we had. So now rocket speed, accuracy, everything's there. 

Another one is around, incident management and then, you know, hopefully being able to prevent some of these incidents. So there's so much data that gets gathered over every incident that gets opened. And to be able to parse through that again, it's you know, it was not not humanly possible literally. Now, you know, just leveraging AI and be able to take care of the, of pulling that data out of all the incident records, making sure that the RCA, the root cause analysis, getting all the information out and then trying to use it in a proactive manner where it's not just recognizing, hey, there's a problem, but saying, how can we try and catch some of these things before it actually becomes a problem?

And then I think last, maybe the last part that we're really focused on also is on disaster recovery and making sure that we're, we're basically checking all these systems 24 over seven to understand, do we have something brewing out there? I mean, hopefully we don't have a disaster, but we want to be prepared just in case we do.

So I think those are the three areas that we're probably putting the majority of the effort and time into now. But again, then it's just sort of working our way down the stack, you know, as we go forward from, from an internal perspective. 

Evan: Appreciate you sharing. But I want, I want to ask some more about those, the one you mentioned, a contract lifecycle management that is, for me is really interesting one, because I don't know some terms or clauses that kind of go against our kind of, you know, legal standards or policies.

But now what I've seen internally is, you know, it's like looks at red lines. This is an almost like it's gone from like, you know, I don't know, like fancy keyword detection. Right. To like actually like giving guidance input. So that that one I think is interesting because it's just a lot more in private. All these use cases like a basic version and then you can kind of upgrade and probably the limits of what the, you know, the AI technology can do across different processes are, probably still underestimated today. 

Mark: I agree and absolutely, that's one of the capabilities. And so every time we look at what we're going to, you know, sort of tackle next, it's really try and get an understanding of what, what do we what are the ideas. And then really understanding the business process. How do we do it manually today? I think it also helps us really get a better defined, sort of process mapping as to actually how it's done and then to understand, okay, are we going to build something or are we going to buy something, or are we going to use a managed service to help us provide some of these things?

So, you know, what we're seeing is, is that the third party tool providers are really making some great inroads into a lot of these tools. And, you know, I won't say the name, but the product that we use for contract lifecycle management, which is a popular one, but it the capabilities in there are really impressive and they're perfectly integrated into the, you know, into the capabilities of the tool itself.

So just like you said, you know, I think with with being able to go, being able to go and get that kind of information, but then being able to expand upon that. So it's not just a, you know, search and replace or search and find or go find all these things, but helping understand, you know, what is the best way to rephrase this? How can you know? Here's what we're hearing from, you know, obviously all these, you know, we're we're dealing with a contract from another, you know, other vendor. They've they've redlined these things. What are some ways we could potentially get around this. We could reword it. We could reword in our favor. 

Evan: Is there any like particular kind of applied use case maybe for like internal operations that you feel like really proud about or like you look back and like, wow, I had no idea. Six months that was even possible. Like what? What kind of stands out to you? Some it's been, you know, your most exciting or impressive innovation there. 

Mark: Yeah. I, you know, it's you're, there were a lot of exciting. I mean, it's going to be exciting to, to some people and probably not as exciting others basically as, as incidents come up, if, you know, we build what we call an SOP, standing operating procedure, right for the, the support engineers to be able to follow. So when something comes down, they don't have to just go, you know, ask the person next to them, hey, you know, what do we do now? They they basically can retrieve and sop the standard operating procedure and then go and troubleshoot. You know, if says, okay, you know, try this, try this, try this, try this all the way down.

And so what happens is after an incident is done, if there wasn't a standard operating procedure in place or it needs to be updated, we then take the the information from there and used to be manually updated. And it would take, you know, days and days to be able to take through that parse all the way through. It added in there.

And we've now leveraged AI to take all those incidents and say, build a standard operating procedure out of this. So it used to take, you know, 1 or 2 people, probably 2 or 3 weeks to finalize and get it done. I mean, it's essentially, I don't know, 15 minutes now, worst case, probably two minutes, best case to be able to pull the information and say, you know, basically build out a step-by-step procedure that would have understood quickly what was the problem and then what should be done.

And then how do you stop that from happening next time, even that one thing, I mean that's freed up and I do want to say, you know, our our goal at Wolters Kluwer is not to eliminate people's roles at the company. It's basically to eliminate a lot of these sort of day to day, you know, painful tasks and allow them to do something different, allow them to learn more, allow them to go focus on, you know, another area that needs them.

Evan: If you were giving advice to maybe, you know, technology leaders out there, IT leaders about, hey, here's kind of like three quick wins, right? Where you could kind of just like, you know, if you're trying to like put some points on the board, make some progress, you know, maybe, maybe help convince some of your peers that are maybe not quite as, you know, far along the spectrum about that, I had a real opportunity to kind of transform the business.

We'll be a couple of kind of quick wins you’d recommend?

Mark: You know, I, I think I would pick two sort of categories. So the first one is on user productivity. And there's lots of user productivity tools out there. Some of them I get I won't use the words, but it's like a person sitting next to you in a plane right? You can figure out the names. I think there's tremendous value in those sort of user productivity.

Now, the challenges, I think most companies, a CFO, which is fair and their job is, you know, managing the finances of the company, will say, how many jobs can I eliminate if I if I pay for licenses across the company? I think we need to use a different sort of thought process. At least I say from minute side, I don't want to tell a CFO how to do his or her job, but to be able to leverage understanding that this productivity is going to pay off.

It may be hard to look and say, every person saved, you know, three hours a week. I think the key part around that for us, has been and the the person who leads, are what we call workplace technologies. She's done just an incredible job of recognizing the need to train people, because a lot of them, you're going to give them a license and they're not comfortable.

If they didn't grow up with it. Or I mean, at this stage, right? Very few people grew up with AI, but some people are more comfortable because they've used it more in their private lives. But if if you're if your work experience is the first time you come into it, I would say at that point, make sure the training is there.

Help them understand prompts, help them understand what a a poor prompt is, what a great prompt is. How do you get the information out? How you leverage it, how to use it to update a document, how to use it to summarize an email. We could all use that, right? We all get a lot of email that should have been summarized at its source, but somehow get summarized.

So I say that's sort of one side of it. The other side to me is not looking at AI and saying, hey, I've got this tool now what am I going to go do with it? But saying identify some of the more manual processes that are going on within your organization, those that take a lot of people that a lot of time and say again, don't focus on, you know, ten different things.

Pick one, pick one thing and say, how do we actually go through this? I also think, lastly, it does depend on the profile of what that person is like, the job role that they have and again, I'll say the you know, one of the great things are the team did here was to look at picking out a few roles.

I think we actually picked out nine to say, what are roles that we think could actually benefit from this? There's some roles where you say, you know, probably not. They're not going to reinvent their business like a business relationship manager. Maybe they're not going to be able to, you know, leverage AI as much as like a developer would or an architect would, or someone in customer support would or incident management, something like that.

So there are roles, I think, that are much more apt to bringing in this kind of a technology to be able to show value quickly.

Evan: You know, how do you decide where to invest, right? Like, I think what you're applying is like, you can't go launch a thousand projects. You got to pick a couple things, couple use cases, a couple roles for us. How do you kind of yeah, what what's what's your process or thinking about how you prioritize and make sure you don't get overwhelmed too distracted.

Mark: Yeah. You know, I think and it is it is hard. And I think that's a legitimate thing because there's I don't think there's a company out there. I mean, I, I was watching, you know, on TV and eyeglasses and two toothbrushes. They're now like AI and you go like, is that are they, are they really. There's that.

I mean, I, I'm going to assume it's marketing stuff. I don't know, I don't I didn't purchase either of those things. But it seems hard to believe that a toothbrush is sort of AI enabled. But maybe they are. I do think you know that, folks, one thing that's worked well for us is understanding the vendors that you currently leverage today.

Great. But nearly everybody has a set of third party vendors, and vendors are partners. And then understanding what capabilities they provide. Because if if you go out and, you know, start to leverage some of these, you know, open, open AI type, you know, capabilities, it's a lot to understand. And that's where I think a lot of the marketing hype is contract lifecycle management, at least in my experience.

My opinion is the same at every single company. Every company has a million contracts. Every one of them were, I don't wanna say many of them are poorly written. Many of them were written, you know, ten, 15, 20 years ago. People trying to sort through they're there's amendments, there's adjustments. All the rest of those pieces talk to those vendors, understand how they've helped other customers find.

If you can find examples of what other companies have done, companies have had the same set of challenges and problems that you have. I don't say copy or steal. We call it leverage. Leverage what they did. I mean, there's no embarrassment in saying, hey, here's an example of a company that had the exact same issue you did.

Here's here's what we leveraged off of, you know, a capability that this third party vendor is using. Give that a try. I think it's a proven quantity that point and it takes you away from that fear of, you know, there's there's just a million. I mean, it's by more than a million, million vendors and startups. They're all saying, oh, we know we have the answer.

We can provide it. You. And it's this sort of one size fits all and go pick, you know, pick your, you know, like we talked about just a few examples and go find some problems that are very manual, that are very time-consuming. I guarantee you the vendor behind that will most likely have some sort of AI capabilities. Start with those. 

Evan: Mark, I hope that my off base here, but my sense from talking to you for a little bit is that you're a little more in the details, right? I've kind of like how technology gets apply than maybe the average CIO or you had a lot more hands on experience. I'd love to hear, just like, how are you using AI personally, right.

How does it change your personal workflow? The things you're doing today with AI that may be more possible six months or a year ago, like, yeah, give us a give you some pro tips about what I should be doing to kind of hear what all this can be done to kind of streamline work.

Mark: Yeah. Well, I mean, I there's a again I and I hate to, I don't want to be a company advertise but I will say I did, you know work at Microsoft for a couple years. And you know they are very forward thinking in terms of trying to push everybody to use AI. To be fair, they're trying to sell.

I got to be honest, I use it, I think probably every day in terms of summarizing emails where you'll get that or a slide presentation where I'll be like, this is 30 slides at a time is always the challenge, right? There's just never enough hours in a day and say, how do I use getting it? So you it becomes part of your life and becomes just sort of a natural part of a of a, like a personal toolset where you don't even think about it.

Also, I think ChatGPT right. No big deal. No, no, no surprise there. I don't use more traditional sorts of search engines anymore. You know, obviously a big company that we used to back up to in Mountain View, California when I was at Symantec. I just I get better answers and better responses.

It's not the I don't also get all the advertisements associated with, you know, many of the searches, but I feel like I get the answer much more. And that's, again what we're trying to do. Wolters Kluwer get you the answer exactly what you want. Quickly.

If I build the prompt accurately enough, we're getting, you know, three tries with a with a prompt to get it written correctly.

I feel like I've got a much better opportunity to get the information I'm searching for.

Evan: There is a lot of just your small time saved is going to large language model and get you if you prompt it right, you get, you know, a good enough answer pretty fast. I for one, welcome our new AI Overlords.

Mark: I do too, I want to go on record saying I do.

Evan: So okay. Forgive me. I'm gonna ask you to take out your crystal ball for a second. What do you think will be in, like, five years? Right. What's your vision of how professionals, whether their customers are to employees or interact with AI in in kind of 2030, right. Like, what is that going to look like in the future?

I mean, maybe it's too far outside and things are changing, but, you know, two, three, five years out from now.

Mark: I'm happy to give it a shot. I think there's some roles that are less likely to be, you know, taken over by AI, at least in the short term. So things like emotional intelligence, creativity, empathy, those kinds of things. My opinion of this stage is that that's not a mature portion of AI is now, I know a lot of people are saying, oh, it'll never be good at that.

I would not go on record saying, I won't be able to do X, because I think in time it will. I think that's I hate to say it, maybe beyond two years, probably not five, not probably be on five years because gosh knows what five years is going to bring. But I would say I, I do believe that level, the other side, because I think right now it's still growing on the, you know, the IQ side and the RB test, you know, beats humans.

Of course, that's us lowly little humans. But I think that you start to advance it on that side where there's more thought process, more reasoning, more learning, more capabilities around the sort of emotional side, the empathy side, you know, the emotional intelligence. I, I do think that's going to come.

Evan: Yeah. I mean, I, I'm, I'm pretty far in like the AI pilled spectrum. So it's hard to know what will let her know if what I believe is accurate. But, I, I agree with you. I think even on the question of, replacing jobs. Right. It's a little bit more nuance, right? Because probably, you know, every job is meeting some set of responsibilities today there, most of them by humans, by the future, certainly done with AI, some some kind of partnership with AI.

It's almost all done with humans.

Mark: And I think that, you know, the workforce will change it. Again, my opinion. I think the idea of having like agents and orchestrators is the that's just going to be part of the workforce and it's not going to be necessarily a good thing or a bad thing. It's just like another employee, like an AI employee that, you know, they work for cheaper and they don't need vacations, and they work 24/7, which is going to make us all look bad.

But I think the idea of like a sort of almost an AI employee that's doing that work, they still, you know, they're still doing work, they're still viewed almost as like, almost like a, you know, as an employee and you're working alongside of them, like you said, some roles 100% taken over by AI, some more of a mix and some not at all.

After that. It's hard to say, but I agree with you is that it'll be more of a mainstream thing where it's not going to be like, oh, I does this. You're you're just gonna be like, yeah, does that right? It's not that big a deal.

Evan: Okay, so we only got like five minutes left at the end of the episode, like do a bit of a lightning round. These are questions that usually take more than the one tweets to answer. I think like the one tweet version, just, for some, punchy segments.

So, maybe to start off, how do you take a company should measure success of the CIO.

Mark: Value back to the business. Measurable value, back to the business.

Evan: What's your advice for some of your peers so they can make sure they're keeping up with the latest technology?

Mark: Encourage your teams to learn and innovate. I, I only get I get what I get because I've got a tremendously smart team, who help me, leverage your teams. If you're moving into a leadership role, leverage your teams. Don't don't just allow them to innovate, like, push them, force them to innovate. I think I used up my tweet.

Evan: In a similar vein, like, what is, advice that you wish someone gave you when you first became a global CIO?

Mark: Don't be afraid to be yourself. I think. I think, they, I think many companies or, people will force you into something that, certain model. This is what a CIO looks like, acts like, thinks like, bring your own self into that role. Whoever you are, make that the role. Not not what somebody else tells you it should be.

Evan: Okay. So that's what you do. Maybe a little bit more on the personal side. What is the book that you've read that's had a big impact on you and maybe why?

Mark: Yeah. You know, I know it's a while back now, there was a book called, The Boys in the boat, and they end up making it into a movie. I love the idea of, I don't know if you know the story. It's about the, university Washington and their rowing team, of all things back, before World War two.

And competing in the Olympics. And I'm sure everybody's seen the movie or read the book, or if you have. But anyway, about building a team and what it takes to build a team and that some people that don't start out great become great because, you know, people help them and bring them along. But I think it's it doesn't it doesn't portray itself. I don't think is like a leadership book. I like the real-world examples of things that have happened in those.

Evan: Okay, so final question is, I know we're short on time here. What I'm kind of looking for, your contrarian. Take care. So, what do you think will be true about AI's impact on the world in the future that most of your peers today would consider science fiction or may disagree with?

Mark: I would say there will still be roles that humans will have to do, or humans will be doing. Even in even in five years. I mean, I don't see a world, I don't see Skynet, you know, coming around and saying, boom. You know, I think a tighter coexistence will continue to happen, but I do think there will still be roles out there in the DNA.

I'd say in a business technology environment, there will still be human led, even can I say ten years out? I can't guess like 20 years. That's a long time to go. But I do think there are some roles that will not be, just things that are more focused on strategy, AI, and I'm sure it can get there, but I just don't know if I can get there soon.

Evan: I will mark wrap wrap to our follow up episode a couple of years. We'll see. Kind of yeah I'm in.

Mark: Yeah, yeah you can, but but if I'm wrong on everything, then I'll probably say I'm busy or something like that, or I'll have my AI assistant respond back and say, I'm Evan. We're sorry, but Marcus, is predisposed.

Evan: Well, yeah. Worst case, we'll get the eight year AI avatar to do the show. So, but for now, we got the real mark. So I. We'll celebrate that. So I really appreciate you joining today. Share a little about your past, how I present your your views on the future. So thank you so much.

Mark: Of course. Thank you I appreciate it. Thank you for the invite, Evan.

Evan: That was Mark Sherwood, executive vice president and chief information officer at Wolters Kluwer.

Saam: Thanks for listening to enterprise AI innovators. I'm Saam Motamedi, a general partner at Greylock Partners. 

Evan: And I'm Evan Reiser, the founder and CEO of abnormal AI. Please be sure to subscribe so you never miss an episode. Learn more about Enterprise AI Transformation at Enterprise Software blog.

Saam: This show is produced by Josh Meer. See you next time.