Bold, Fast, Responsible Workflows with KPMG US Vice Chair, AI & Digital Innovation Steve Chase

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

Speaker B: And I'm Sam Motamity, a general partner at uh, Greylock Partners.

Speaker A: Today on the show we're talking with Steve Chase, Global head of AI and Digital Innovation at KPMG International and vice chair of AI and digital innovation at KPMG US. KPMG is one of the big four accounting firms with over 250,000 people globally spanning tax consulting and deal advisory services from acquisitions to finance transformation. Their cross industry client work makes his AI perspective especially relevant. As Steve notes, now every client conversation centers on tell me how we're going to do this with AI. A few things stuck with me from this conversation. First, Steve shared how they discovered that embedding AI training directly into the workflow rather than teaching it as a separate concept course, made adoption rates soar. This was especially critical for new hires coming off college campuses who'd been told using AI was cheating. The lesson contextualize AI within actual job tasks, not as an add on. Second, Steve believes AI is fundamentally flattening decision making structures. He talked about pushing decisions to the edge, right to the person in the moment, because, as he put it, slow decision making terrorizes teams. His message to his teams is direct. We're going to rewrite the org charts. You are going to rewrite how work gets done. And finally, Steve's top advice for leaders was to establish responsible AI principles upfront and publish them publicly. When you bring risk and legal teams into designing those guardrails early, they feel ownership and it becomes a big unlock for a program. Overall, KPMG's mantra is bold, fast, responsible. And Steve made clear that you don't get to choose just two. Steve, thank you so much for joining us today. Maybe to kick us off, do you mind sharing with our audience a little bit about your career and maybe your role today at kpmg?

Speaker C: Yeah, sure. So my, my, my title is I'm, um, the vice chair of AI and digital innovation for KPMG in the us. I'm also the global head of AI for the firm. I've got the coolest job at kpmg, so I feel very fortunate about that. Prior to that, I was running our consulting business for a number of years, which was also a great job. And I've held variety of different roles, helped start a number of our practices, including being a lead account partner. You know, that was one of the best jobs that I had. And so that's kind of, kind of what I've been up to.

Speaker A: I think KPMG is probably one of the better known firms. Right. Some people may have seen it on the side of a building driving through a city.

Speaker C: Right.

Speaker A: But my guess is that everyone fully appreciates kind of, you know, what you guys do and kind of scope operations. You might kind of just like stepping back and talk a little bit about kind of the firm, what you guys do, who you work with.

Speaker C: We're one of the big four accounting firms. That's how we're known, that's how we got our start. We're, uh, one of the largest tax businesses in the world and we have a very large consulting and deal advisory business. Right. So we work across different parts of the Enterprise. Enterprise. Over 250,000 people globally, all pursuing this agenda to like, deliver great client service to our clients and meet the expectations of our stakeholders in the capital markets, in our communities and what have you. So anyways, that's who we are. We have large digital platforms that run big parts of our business. We have a big investment in bringing AI in a variety of different ways into it. But we also directly work with our clients on those journeys for themselves. Right. And whether. And what's interesting is wherever those journeys are, I need to, um, you know, I want to grow through acquisition. Um, hey, I need your help in thinking through my tax position globally. I need to transform my finance department. Whatever the topic, it's all becoming. Tell me about, and then tell me about the opportunity for AI. Right. It's not a staple on thing either. Just like, like, okay, let's also think about now. It's like, tell me about how we're going to do this with AI. And um, my job is very much about like both preparing our people and our capabilities, but also being out and being able to talk about our experimentation and what we've done to overcome things like the innovator's dilemma. Our mantra is bold, fast, responsible. You kind of run in a revolution in a certain sense because most of the things are set up not to do bold, fast. You know, they certainly want you to be responsible, but bold and fast, it's kind of hard. And that unlock with that mindset, that abundance mindset. We can do this. And not only can we do it, we can do it completely different than we have before.

Speaker A: She talked about kind of bold, fast, responsibility, talk about unleashing people. Like, how do you activate that? Right? How do you get someone to maybe realize that? And it could be like a new consultant, it could be a, uh, client of yours, right? How do you realize it is possible? How do you kind of enlighten them to realize they can be unleashed?

Speaker C: The first thing is we figured out on effective use, that part of the effective use thing, uh, and it's an obvious point, we've known this for a long time. But if I train you how to do something, in the course of training you how to do your job, you're going to be way better at using the AI when it's contextualized for you, right? And if I can emerge the capabilities inside where, you know, the Paneglass, where you do your work, it's also going to be. That's not something I go over here to go do necessarily. I'll be able to make that interaction, that experience more seamless. So we try to do those things right. At the same time we have the general purpose tools that sit beside it that, you know, when I need to, I can go there, but then it in the pane of glass, I'm over here. So like an example of that would be, is we see some of our newer employees especially you know, early on who are coming off college campuses, they weren't trained to use this stuff, right? Like they come over to KPMG and you're like, hey, uh, I'm expecting you to use this like every day. Like it's in your work. This is an everyday tool. And there's a, uh. Well, I was told this is cheating. Like, well, okay, you know, so I know I've got to like, I gotta, I've gotta bring them up to speed. One of the things we did was, it's a little bit AB testing, but with some of our audit professionals coming through, training them in the. We just redesigned training altogether to put their, the AI right in the moment. The adoption rates through the roof compared to what they were when we were training separate AI courses, you know, and so that's just, that alone was a, was uh, a big unlock of um, you know, year and a half or so ago.

Speaker B: Help us imagine what that's going to look like. The AI native. Like, you know, if we walk, you know, into the office of a company that's truly AI native and not just using AI as a bolt on, how do you think the work is going to feel different compared to a company that's using AI more as just an add on?

Speaker C: There's A certain flattening of where decisions are taking place. You'll hear some of them talking about. It's actually a new management lesson, I think like a context graph all of a sudden opens up the opportunity for decisions to be made in a very dispersed way. Right. Like, so I'm trying to take those lessons and figure out what that means in bigger entities as well. Like if I can push more to the edge, push more right. To the person who's right in the moment and that, and help them with that decision, get them the decision. Because slow decision making terrorizes teams. Right? Like it terrorizes them from being able to move forward. A no is a gift, right? And a yes, it's a gift. But like uh, uh, let me get back to you. Is a. Like it just holds everybody and it just like grinds everything to a halt. I see that in that, that question you're asking about, like, how are they, uh, what does that mean? What's it going to look like? Faster decision making, more diffusion of the, of our strategy. You know, getting strategy out to everybody is really hard. And also getting them to be able to process it well, again, that AI should be good at that. And I think it is. I think flatter is what we're seeing. Right? Flatter seems to be, um. And that doesn't mean less people, it just means flatter. And we're all going to be like, we've got a new resource constraint, which is some version of tokens. Right. Like, I don't think people have really ever thought about that. But when you see what's going on in some of the leading Silicon Valley companies, you know, it's like, how many GPUs do I have, not how many people? Right. I think that concept is coming as we think about putting clogged code in more people's hands or putting advanced Gemini or Microsoft tools. Like all of a sudden I've got that going on. So it's clearly about pace and urgency, but also pace of decision making. Like how quickly are you shipping? And I think the AI is going to open up management structures we haven't really thought about before. I think we really, I mean my fundamental message to uh, our teams is we're going to rewrite the org charts, we are going to rewrite how work gets done. And process thinking won't necessarily be the way through that also because that's a construct for human minds, but wouldn't necessarily be the way agents and we've seen that in the way that they think about how they go do things Right. So long answer. But that's how I'm thinking about M and what I'm trying to learn from because I do spend time like we, we make minority investments in companies all the time. One of the things that we, we look at is their management structures and how we can bring that kind of thinking into our own organization and even

Speaker A: just like our ability to plan for the future. Like I don't know how valuable is a five year plan when there's like new technology every week. Right. Your five year product roadmap is kind of silly at some moment. Uh, not for every business but for some fast forward business. So it'd be really interesting to see how the, how these best practice or old best practices will just become common practices and the new best practices I think are probably still get to be written.

Speaker C: Those five year plans are strong opinions loosely held at this point. Right. Like and regularly checked. And then you can build that agent assistant that actually does a really nice job of helping you and flagging like hey, well there's these expectations in there and how is, you know, M. Most organizations are doing some version of that. Right. Like they have the, the, the agents that are helping them with that sort of planning. Again, we ought to be able to do a ton of that. Right. Like at, at and, and maybe hundreds of that somewhat regularly. Right. The problem is, is who's, who's, who's benefiting from that. Like where is that going and how do we then take action, real action on what we're learning and seeing in a world where there's lots of summarization and documentation and like ideas and whatnot. Like maybe it'll only be the agents that know what's going on. I'm not sure that's, I'm not sure that's the outcome I'm looking for either.

Speaker B: Evan, I'm curious about pmg. Is there a specific AI use case that you're currently running that you're particularly proud of or you think is particularly innovative?

Speaker C: First off, you know, given the size of the organization, there's just tons of them. Right. Like let me give you a mundane one and let me give you some kind of like some, some pretty cool like out there ones. Right? So on the mundane side, you know, enterprise knowledge is really hard to unlock, especially an organization like ours. It's highly diffused, right. Highly distributed. We got people who work all over the place, they're in different offices and whatnot. So one of our number one early objectives with our AI program was to solve for enterprise search, make I Should be able to find out the answer to what we're up to, what we think about something, what have you. Solving that problem, which we m. I feel really good about what we've done there. We happen to have used Gemini Enterprise for that. But like, but there are lots of ways you could have done that, but that's the way we chose to do it. And then being able to bring agents close to that, you know, once you surface the information, then what can I do? That was. That was a pretty big unlock and I think people underappreciate that. I hear too many people, oh, I'm going to do this, but I'm only going to give this thing to like discipline work group. I'm going to do this on this. Like, I think you have to have a combination of I did this for like I'm solving problems for everybody and I'm enabling experimentation and use at the edge for everybody. And then you have to have the specifics. Right. So I'm going to come in and you know, we have a process we go through around innovation. We run ideas through a sort of a studio concept like an incubator, like you might do externally, but we have an internal and you know, we think about the idea that's been brought to us and we whittle them down. Just anything you would, you would know through stage gates and have a really cool solution, uh, called Contract iq that's all about helping in a particular procurement solution area. It's a combination of like lots of agents that are working a bunch of software that's wrapped around it to go after a problem that you just couldn't have solved prior to which. Which had to do with a particular sector problem around contracts in buy side contracts. Right. So I'm buying services from somebody anyway, so, so and getting through that, right. And finding the, the customers that were willing to be design partners for that and being ready to like walk away from if it didn't prove out through the things. I mean that's. That was uh, that was just a cool, that's a cool process. But um, it's certainly not the only one. We only, only product we brought through it. I'd like to bring more, but being able to demonstrate our ability to go do that also the unlock to our people to see us building a solution, it's wrapped with our services, allows us to do better services. I don't know, like, it's gotta be both things though.

Speaker A: A couple weeks ago I was talking to Matt, your guy's chief security officer, as much as I want to talk about, you know, cool CIA stuff with him. Since he was the C of the CIA, we talked a lot about kind of innovation at kpmg. And one thing he mentioned was, um, you know, when he was kind of exploring his generative AI tools, right. KPMG didn't block it, but they actually encourage experimentation. And so like I'm curious, like maybe it's a two part thing, like how do you guys kind of like build that culture of experimentation, right? And then are there things you've seen that have maybe kind of come out of that culture, right that might not otherwise be there, right. If kind of you weren't willing to take some of those experimentation risks.

Speaker C: When we started our program, I usually have a big poster behind me. We called the program aiq Little a large IQ with this notion that this was going to be about unlocking the capabilities of our people. Right. I firmly believe that that's what we're up to, right? Like I, we're a growth business, want to be a growth business. We want to, we want to like be in front of this, you know, the biggest wave that's come through business, not technology, but through business maybe ever. And like when you, when our leaders are talking that way, when we're saying we want to be bold, fast and responsible and you don't get to choose two, right? We want to do, you know, we want to do all and we create expectation for folks that we want you to be using this and we want you to be a bit self sufficient in being able to do the, you know, it is no coding but there's a lot you can do with no code. And then when I put our data with it and I uh, give you the ability to secure place to be able to work with client data as well, all of a sudden I got some really big unlocks about things and bring better solutions. Our clients, it's not natural for us like uh, like to just think about innovation at the edge. But I really, you know, our, our leadership on down has been really committed to that because that's how you win in a disrupting market. Right. And it's interesting when we tell folks about the journey we've been on because that's a journey, right? Like it didn't work immediately out of the gate. Every time they're like, oh, I liked it, I like it so much. Like you know, a couple of folks have uh, actually taken our name AIQ and named their projects that.

Speaker A: So are there maybe advice you have for leaders out there that are trying to Inject this culture of kind of speed and agility, which is obviously becoming more valuable in the age of AI. It would be your kind of pro tips there. How do you kind of, what would you advise someone listen in about how they kind of activate that urgency and speed which um, maybe in some cases, you know, take more risk to help them capitalize on some of these new technologies.

Speaker C: So one of the things I always tell people is the first thing we did was establish a set of responsible use or what we call trusted AI principles. And we decided to publish them. If you go to our website, you can find uh, the sort of 10 domain areas and the principles that we live by for everything we do. And when you're willing to design that in up front and you then engage your risk and legal and others in that process, they feel like they have some ownership in that. It is a big unlock for a program overall. It's not like, oh, that thing that sits on. I mean Matt posted and I, who you mentioned, our CISO and our global ciso, guy named John Israel. I mean we're on the phone a lot talking about what are we, how are we going to think about identity in a world of agents, for example, and I want to be right there with him as a design partner on that because he's responsible for knowing whatever is going on. I got another team who needs to know a bit more observability item out of that. Thinking through like, okay, but what's the cost implication going to be about doing it a certain way? I mean, I don't think people talk about this quite enough, but like I'm going to be, I mean I have visibility, observability, uh, agents everywhere. We're talking about semi autonomous agents. Tell me about ex, where my control structures are, where's my kill switch, et cetera. I don't want to uh, you know, so we obviously do a lot of trusted AI services and I'm not shilling for them. I'm saying like there is no AI journey without that. Right? Everybody needs to have a certain percentage of their dollars going towards that. And it needs to be something you talk about regularly. You got to train it. The only mandatory classes we do on AI that are specific AI are trusted AI training. And when you do that, I think that what happens is again, you've unlocked. So I get like in the first line at the edge. Everybody sort of understands that it's not just about going fast, it's about going bold, fast and responsible. So anyway, I think that's been one of the things that's really worked for

Speaker A: us, you know what I mean? The more we kind of brace that mindset and move faster and get closer to that frontier of what's possible, AI is that kind of cultural mindset that's going to make or break a lot of leaders and a lot of companies, not the lack of access to certain technologies.

Speaker C: Yeah. And the other thing is we, at the same time as that's going on, uh, you know, we're all terrorized by the, the next headline that's about to come out, like, well, why don't I have access to. Well, you know, we made this choice. It's like, yeah, but like, for five minutes, I'm not going to have the latest tool. It's like, okay, well, you're not really using the existing stuff that we gave you. And now you're telling me the reason is because there's a better tool out there. Right. I mean, come on, we can move quickly. We will make highly capable tools available. Then we will be committed to that. But also, there's a gift get. I mean, I need to see you using the stuff that you do have. Right. And I tell that to organizations all the time. You got, you're going to choose, choose some partners that you feel good about, have other experiments going on with others, be, have a path to get new stuff in, but really focus on the investments you made because there's so much in there. And I, you know, I think people don't talk quite enough about that. Like, going long on one is probably not enough. Going long on 10 is like, that's not, I mean, you might as well not have any at that point.

Speaker A: Uh, that's right. Yeah. Like the, it's really about the kind of culture and the business process changes. Right. The kind of organizational transformation. You're right. The reality in the future is like, four years from now, the dumbest AI tool, way better than the best one available today. So, like, it'll get there. Right. But if you don't kind of start some of these, um, again, cultural organizational changes now or the process kind of transformation, you'll never meet a place to use any of the tools. Right. In the future.

Speaker C: Yeah, yeah, absolutely. You know, it's funny. There's a funny, like, narrative that's no longer. I don't hear as much in the last couple of months. It's like, oh, well, you know, we're not going to need, uh, nearly as many engineers. Like, are you kidding me? Like, we're like, this is going to be the software glory days. Here all of a sudden, like, we need to be really careful about sprawl, but I think we've really reduced the cost of access to software, which I think is a great unlock. I think I really give credit to some of the frontier models for having sort of sorted that idea out that that's, that given access to the models, to that tool, which is coding languages all of a sudden in the way that opens up, you know, because I'm not sure it's always going to be about agents. A lot of this could well be about the agents that built the software and maintain it, that allow me to do things that I couldn't have done otherwise. But I can do it really repeatably and scale it. Right?

Speaker A: Yeah. And what's exciting that I just find invigorating every day is like, there will be an explosion of software, but it's not just me from the software engineers. Right. The value of a computer science degree in like 99% of use cases. Not all. We still hire PhDs in some areas. But, um, the value of kind of computer science degree is going down. And the value of your kind of business expertise, your understanding of the customer problem. Right. That's going up. Right. And I'm sure there's, I'm sure there's some consultant at kpmg, KPM today, they couldn't write a line of code, they couldn't write a line of Python. Right. If they had to. Right. By the end of the day. But they understand the customer problems better than anyone else. Right. Maybe better than the customer. If all these tool technologies can supercharge them. Right. The impact they can have is getting multiplied by 10x100x. So it's exciting time for all of us.

Speaker C: Yeah. Again, it's an abundance point. Right. I've now democratized that question of like, where the code is coming from. Now we all have this problem of pathway to production. Right. Like, so I, when I give that experimentation opportunity, I gotta figure out how to, how to get the pathway to production unlocked. So we spend a lot of time on that. I'm sure you guys have had plenty of people talking about that too. That's a, that's a. But when we think about like, well, why do people call kpmg? It's our industry knowledge, it's our functional knowledge, it's our depth and things like taxes and when they've got, you know, right now, tariffs a big issue, it's a lot of confusion around there. If I can come to them with a simple way for them to engage with us and get answers to tariff exposure or what have you. And, and part of that's because we built an AI solution. It's a tariff modeler that our clients can then get access to that I couldn't have built as fast as that if I hadn't had the advanced tools that I do. I mean, that's when it's right. That's when, uh, that's sort of when magic is happening.

Speaker A: So, Steve, we're going to run up on time in a second. One, uh, thing we like to do at the end of the episode is do a bit of a lightning round and basically, um, it's a really mean game where Sam and I ask you questions that are pretty big and we ask you to answer them in like a one tweet. So just hopefully this won't destroy our friendship. But, um, you know, so, but we're going to, we're going to, we're going to try this out. So maybe Sam, um, you want to go first.

Speaker B: Absolutely. So to kick us off, Steve, if someone is entering a company and they're going to be the company's first chief AI officer, what are the three things they need to get done in year

Speaker C: one, Trusted AI adoption, access and awareness. So access, awareness, adoption, in that order, and innovation at the edge.

Speaker A: You're obviously kind of pretty up to date with the latest AI stuff, right? And I think it's undeniable that in this era right now, kind of understand what's possible. Being close to technology is probably more valuable than it's ever been. So what would be your advice about how do you stay up to date on kind of, you know, all the new technology, all the new AI stuff?

Speaker C: I'm, um, an audio, like an auditory learner and so. And I like to go for long walks, sometimes weighted. So my answer is podcasts. I'm not selling to you guys, but actually I really get a lot of value, especially out of the regular podcast. I like to have a bit of a wide group from market to like sort of the daily thing and then down to the builders.

Speaker B: So maybe to switch gears to the more personal side. What's a book you've read that's had a big impact on you and why? And it doesn't have to be work related.

Speaker C: Well, I was a philosophy major, amongst other degrees. I've gotten so I loved the book by Gore Vidal called Creation. It just really opened my mind to like that I just actually had no idea how history had really. I mean, so then I ended up reading a lot about what that was about. It just opened my mind to what had been happening. And so anyways, that was an interesting one. Snow crash. I sort of go back to. I know if you guys have uh, picked up a little snow crash. I mean I think it's interesting how ahead of what we are up to that these, these science fiction writers have, you know, they thought about a lot of these, these site. If you're not, listen, if you're not reading science fiction. It is actually required work reading right now to read some of the AI to, to understand what the interface is going to be like, what the use cases are going to be like, what some of the issues are.

Speaker A: So Steve, what's the upcoming technology you're just most excited about? It doesn't have to be AI, but

Speaker C: no, I mean I'm fascinated by what's coming with world models and embodied AI. The unlock that is likely right around the corner. I mean I'm not saying nobody's talking about it. Yann Lecun just what he raised like $3 billion. So uh, clearly people are talking about it, but I think we've yet really thought through just how transformative this next wave is going to be. You know, AI kind of right at the edge in everything and in everything we're doing. That's the one I'm really tracking.

Speaker B: What do you believe will be true about AIs uh, impact on the world that most people would consider science fiction?

Speaker C: Today I'm going to go with. We're going to call this the fifth Industrial Revolution. I think the fourth one maybe has already happened. Truly like the explosion of innovation in every domain, every science, biotech, what have you and the things that are going to come from that. I don't think we're talking enough about just one outcome. We're all going to live a lot longer because of it, because of all the innovation that's going to come. Uh, I don't think we never talk enough about the secondary effect of all this capability that's about to be unleashed on the largest industrial project that's ever been launched in the history of mankind.

Speaker A: I think that's an exciting uh, note. To end the podcast, we'll stop our uh, game show questions. And Steve, thank you so much for joining us today. I'm looking forward to catching up on uh, trade some sci fi notes with you in the future and um, hopefully we'll get a chat again soon.

Speaker C: Yeah guys, I really enjoyed it. Thanks for the time today.

Speaker B: Thanks a lot, Steve.

Speaker A: That was Steve Chase, Global Head of AI and Digital innovation at KPMG International and vice chair of AI and digital innovation. Ah@KPMG US.

Speaker B: Thanks for listening to Enterprise AI Innovators. I'm Sam Motamity, a General partner at Greylock Partners.

Speaker A: And I'm Evan Reiser, the founder and CEO of Abnormal M AI. Please be sure to subscribe so you never miss an episode. Learn more about Enterprise AI Transformation at enterprisesoftware Blog. This show is produced by Abnormal Studios. We'll see you next time.