AI’s Impact on the Consulting Industry (Panel)

Transcription

We have four panelists today. We're really excited to introduce all of you. I'm going to have you go as we go through the panel just in order of your alphabetized order. So I'm going to walk through that. And hopefully I can get the alphabet right. We'll see.

We've got 2 'Ks, so that's always a little bit tricky. But our first question is just to please introduce yourself, you personally, the firm that you're here representing today, and an early memory of AI, a thought about it, an experience with it, etc. And that will kick off our conversation.

So FTI, you're up first.

Great. Thank you.

Hi, everyone. My name is Kyle Wetzold. I'm a Senior Director at FTI Consulting, and I'm based in New York. I'm the head of Strategy and Product for our global AI team, and the Chief of Staff for our firm-wide AI Steering Committee. I got my MBA at Columbia Business School, and did my undergrad studies at UChicago. And for those who don't know, FTI Consulting is a global business advisory firm, really focused on helping organizations manage change, mitigate risk, and resolve disputes.

We have 8,000 employees globally across 33 countries. So a really big reach, and we do a lot of interesting things. My earliest memories of AI are probably tied to watching a movie like Blade Runner, reading something by Isaac Asimov.

But if we think about moving beyond the world of fiction, I think my first true light bulb moment with AI was reading about Deep Blue, which was a chess playing expert tool from the mid-90s that beat the chess grand champion at that current point in time and was running an IBM supercomputer. So I think I was far too young at the time to actually understand what that meant. But I think when I ended up reading about that and understanding it, that really took something that felt like science fiction and really grounded it in the real world.

And I'm looking forward to the rest of today's discussion.

Thank you. Kyle, can I just probe on one thing? How long has FTI AI been a thing? Can you tell us a little bit about just the history of this specific group that you're a part of?

Absolutely. So we've been doing AI actually for quite a long time across a bunch of different areas. But really in the past, I would say, two to five years, we've formalized this group that's global and it works across all our different verticals to really help inject AI into the way we support our clients, whether that's from a strategic perspective, from a product development perspective.

And so working with that team has been a great chance to really bridge the technical and the strategic and really understand how to support clients think through these complex topics.

I love it. Amazing. Thank you. And thanks again for joining. All right. Kearney, you're next. Alfredo.

Thank you, Jenny Rae. And nice to meet every one of you from the panel. My name is Alfredo. I'm a Senior Manager based out of Durham, North Carolina, aligned with our New York office. I graduated from Sloan back in 2020 and have been a founding member of Kearney's Data and AI Practice. Recently, I led our Internal AI Transformation Program.

And let me give you some context on Kearney, for those that are not familiar. We've been around since the 1930s. We have presence in 40 countries, but we're small enough so everybody can feel that they have an impact, but we play with the largest players in the world.

We're bread and butter in strategic operations, and some of the interesting conversations we're having around AI are focused on AI in supply chain, and how that's shaping the future. Now, I don't have as cool of an example as Kyle, but my early memory of AI in this context came back from when I was at Sloan. We had a marketing analytics professor.

He just quit Facebook as a data scientist, and he said, we will not be able to imagine how much we will be able to achieve in the next 10 years. And we, of course, didn't believe him, and then it happened three years afterwards. So definitely we're at a faster pace than anything that we could have imagined.

I love it. He was telling the future before we were, right?

Exactly. So when somebody predicts the future, believe them.

All right. That's a good quote for today. I'm going to keep that. Wonderful. Thanks, Alfredo. We're excited to have you with us today.

John, KPMG. Excited to move over to you.

Okay. Good morning or afternoon, everybody. My name is John Norkus. My responsibility is for the Internal Pricing Group at KPMG US. What does that mean? That means that I need to be thinking about how the market is moving, think about the models that we are using when we think about being able to bring the greatest value to our clients, when that connects to how we're actually setting price for the services that we provide.

The earliest that I heard of AI was my first three or four months when I started consulting, and they wanted me to join the AI Special Interest Group that was there at my previous employer. Now, that was in the fall of 1990. And so, I've been hearing now for 34 years that AI is going to be putting us all out of business.

And so, when we hear about the latest wave in technology and gen AI, we have to ask ourselves the question, will there be disruption? I think that everybody agrees that the answer is yes to that. But we also have to ask ourselves the question, when is it going to show up and how is it going to show up?

So, we've heard the phrase out there, you may have heard the phrase of a jagged frontier of gen AI. What are the use cases? Are we all going to be using it?

And are there particular innovations that are going to change the business model associated with consulting? And quite frankly, running the pricing group at KPMG, that's what my responsibility is, is to question how the business model is going to be changing as we continue to move forward. And we will continue to move forward in a great way utilizing all these tools, both for ourselves and on behalf of our clients.

Thank you, John. I met John at a consulting magazine panel in the spring, and he brought a very spicy perspective. So I'm really excited that you're here today, and I can't wait to hear some of the updates from a few months ago.

You bet.

Wonderful. Last but not least, we have LEK. Dan, Welcome to the panel.

Very nice to meet everyone. I'm very much looking forward to hearing the spicy taste from this group. But I'm Dan Tadeski.

I'm a managing director in L.E.K.'s Boston office. I sit within our firm's consumer and digital practices and help to sit on the leadership team of our digital practice here. If you're not familiar with LEK., we were founded in 1983 by three partners in L and E and K out of London. We're now 20 offices, about 200 partners and 2,000 staff worldwide. Our bread and butter, it really sits in strategy consulting and growth strategy specifically.

We work across all sectors of the economy, whether it's consumer, where I sit, versus industrials, versus life sciences, versus TMT. But a lot of the work that we're doing is helping our corporate clients really think about profitable growth. And with that, sometimes we're leaning into sales and marketing, sometimes it's pure corporate strategy, sometimes it's organizations of performance and thinking about how we optimize the business for value creation.

Then there's an element of what we do around mergers and acquisitions as well, and really taking that industry knowledge and helping our private equity clients and financial sponsors navigate those decisions as well. An early memory of AI. I wrote this down, and Kyle, it's not too far off from yours, but it's also at IBM Watson.

As an avid Jeopardy fan, seeing him beat Ken Jennings or it beat Ken Jennings, I think it would have been around 2010, 2011, somewhere in that timeframe. Because I think the first time I saw what really to me in my mind, artificial intelligence really was. But now we know it's so many more things than just natural language processing, and there's so many more applications than just that. But I think as a broadband moment, that rose to the top for me.

I love it. Well, thanks, Dan. Dan, I should probably ask John this question too, but what percentage of people at LEK would you say know who the L, the E, and the K are? I've always wondered this.

It should be 100 percent. If you interview at LEK., it's a question in almost every interview. So you should check beforehand. I'm kidding, of course.

John, what would you say for KPMG? How many people know who the K, the P, the M, and the G are?

I know personally that I'd have, I'd probably hatchet the German names in that conversation. But of course, it grew out of the US as Pete Marwick, and then combined in the 90s to become the global behemoth that we are today.

I love it. It's a brand on its own, so we don't need to know the genesis, but it's just kind of always a funny idea. Well, we're talking about the future, so I'm going to kick off into some of the core questions that we want to hear your perspective on today.

The first one is one that I'd love for each of you to answer. What's the common question around AI that clients are asking, and how is your firm helping to answer that question? I'll let you just jump in as you have an answer to the question.

Sure, I can go first, keep the alphabetical order coming for now. We do have to be ordered.

I think the most pressing question we're really getting from clients about AI is, how can we really operationalize this to drive transformative business outcomes? And I think over the past 12 to 16 months especially, this question is really reflecting a desire to move beyond experimentation and really start realizing tangible value from AI initiatives.

And how are we helping our client to answer these questions? We're doing a lot of work around AI strategy and transformation, to try to help people identify the proper use cases and really put strong, thoughtful roadmaps in place about how to really build and roll out those solutions. And so I think thinking through this is really kind of through four, I would say key areas of work that we've really been focusing on.

One, really strategic alignment with our clients. So ensuring that the initiatives that they're thinking about, are really closely aligned with their overarching business strategies. That's super important.

Two, really data ecosystem development. So making sure that the clients understand the critical role of data in AI and make sure they have a robust kind of data ecosystem that can support the applications they're considering. I would say three, really thinking about talent and culture.

I think all successful kind of AI transformations, implementations require a skilled workforce and a really supportive organizational structure from the top down. And then lastly, just value capture and measurement. Working closely with clients to develop metrics and frameworks, really measure the value being generated by these initiatives, which enables them to track progress and optimize performance and really demonstrate a clear ROI for their investments.

So we think kind of adopting this approach, which is multifaceted and really interdisciplinary, can really help clients leverage AI not only for efficiency gains, but for real growth and kind of competitive advantage.

I love it. Kyle, do they come to you knowing what they need just out of curiosity?

Oftentimes, no. I think given how much attention and hype there is around AI, I think a lot of people are kind of still looking at it as a shiny object and they know they want it, but they don't quite know how or where or why. I think it's really helping them answer those questions to make sure that they're doing this in a way that's thoughtful and makes sense for their business and their larger strategy.

From the LEK perspective, it's not too dissimilar to what Kyle laid out, probably not a surprise that we all kind of think about what are the needs that exist amongst our clients in a similar fashion and really how do we serve against those. So perhaps rather than I had to reiterating that, I'll speak to where do we see the most interest in kind of airtime given to with our clients today. Given what we're primarily engaging with the C-suite, a lot of it is helping them come through the noise at this stage.

It's thinking about, well, what does it mean for me? Chat GPT is great, but what is going to be different in my industrial business or about my brand? Where am I going to see that leverage? Is it my cost? Is it my customer acquisition? How do I think about this more broadly?

And how do I put structure to that problem so I could communicate effectively to my board, to communicate effectively to my SVPs and L2s about what their priorities need to be and how they need to be thinking about this as an opportunity. And then the second area of most discussion of late is really about then, well, how do I set up the organization? We do a lot and speak a lot about digital maturity and helping organizations move along that journey.

This is just another chapter of that journey and we're at the early pages of it where there's real appetite to invest and for dollars to actually be outlayed against AI in quotes. So we kind of help to work through those types of investment decisions and just try and paint a clearer picture for them, which right now can be a bit complex.

Fantastic. Go ahead, Alfredo.

Yeah. Jumping from a Kearney perspective and I completely agree, right? It's in the mind of every corporate leader, not just the CEO, but everybody around that person. Okay. You start with this question and it's an evolving conversation. The first one is, how should we think about AI? Which use cases should we prioritize? But the trend that we've seen, especially where the past recent months is, is stop being about, what do we do? But it's, okay, how can we get started?

How can we bring this initiative to life? And there's a huge component. You have most of the technology to actually get them operating under four or five key partners or key companies, right?

So another question is, which large company should we partner with to make AI happen? But now there's a separate trend that I particularly find very interesting, which is when the cases are not about AI, but we're having a conversation, for example, if a Chief Supply Chain Officer of a Fortune 5 company, and then we're at a steering committee and then they ask the question, how can we infuse this deliverable with AI? So before it was thinking about AI on itself or how can we implement it, but now for every other type of project, what is the AI flavor that we're bringing it as a next step?

So that is forcing us also to re-evaluate the things that we have done in the past to make sure that they're consistently relevant in the future.

If it's okay with you. I'll piggyback on that. When we then get to have conversations with our clients, there is the good news in the latest wave of technology is being able to ask the question about value. Better? Faster? Cheaper?

Where do the benefits show up? When do they show up? And is it worth it to actually make the investments in the new sets of technologies and the GenAI that we've been seeing?

When we think about it from a transactional perspective, actually doing business with our clients, two conversations. The good news is let's have a conversation about value. Where is the value?

And quite frankly, should we be getting paid based on the value that's being produced? Or if you think about it from a more fundamental perspective, many of us work with procurement departments, and the procurement department is saying, I think you guys are getting a lot of efficiency with what you're bringing to bear in AI. And I think from a procurement perspective, that you should be sharing some of that benefit with us.

And so it brings about a very interesting set of conversations when we think about the way that we're charging for the work that we're doing. So, very interesting in that we're able to have the conversation or shift the conversation more toward value, because I think we're going to have to as the business model advances.

I love it. John, this may be a question for you, although I would invite others just as a follow up. Are there times when you are specifically advising clients not to utilize AI?

They're all thinking about it, but I know that some of the greatest value that we can sometimes offer them is telling them what not to do. Can you give an example of something like that?

Well, given that I'm not in client service, I'm going to have to hand it to the other guys. I do know that we are in business to serve our clients' needs and the values of their corporations. Sometimes if we're measuring that based on shareholder value, whether it be increasing revenue, reducing costs, increasing asset terms, or managing the expectations of an investing market, that question has to be asked, which is, is this ultimately going to make an impact?

One of the things that we try to infuse into the conversation has to do with quality and risk. We always talk about value, but there's a quality and risk aspect associated with that, especially when you're thinking about managing the expectations of an investing public. So, are there recommendations against?

You bet there are. We wouldn't be responsible consultants as an industry if we weren't making those kinds of recommendations. But the notion of quality and risk, I think refreshingly, now more a part of the conversation than they previously have been.

I'll pause on that.

Anybody else want to weigh in on that too? Even if you could give a specific example of a time when a client was like, this is what we think, or we should do this, but you advise them against it, or advise them to hold on something that would be really compelling.

Yeah. I think oftentimes, like certainly back to my kind of data ecosystem point, I think a lot of times it's not about saying, you can't and should never do this, but kind of going back maybe to Dan's comment on the digital maturity topic, are you really ready for this today? And maybe are there a bunch of other things you need to put in place, whether that's from a data governance perspective or a data quality perspective, or just really an organizational governance perspective to make sure the proper guardrails and foundational elements are in place to really empower you to implement and think about AI properly.

And I think John brings up the risk point. Although there haven't been kind of really strong AI regulations in the United States yet, there are still conversations going on around that. And I think certain industries are moving closer to kind of regulatory guidance such that there are certain high-risk use cases, or maybe companies do want to reconsider kind of their positions on AI, or just really make sure that the compliance and regulatory aspect is properly thought through and considered before kind of going down that path.

So, you know, I think it's a cautious approach, and you need to make sure that the governance is in place kind of no matter what you're doing.

Love it. Well, we can move on. We'll come back to this if anybody wants to weigh in as we go.

But one of the things that John brought up was this efficiency, the efficiency gains that AI can provide in delivering the actual work internally. So my second question is just that we do expect that AI will alleviate some of the groundwork that consultants do in the coming years, right? ChatGBT might help us start the language that we use, or run an analysis, or source data that we haven't been able to source before.

I'm curious what specific examples you're seeing internally of how AI is equipping you to more efficiently deliver client work. Alfredo, you want to go first on this one?

Of course. So especially for the audience, when you're starting off as a consultant, there are some activities that are the most annoying, but that are necessary to deliver great value to clients. And those are changing, right?

So and then you can imagine most of the manual tasks, such as building training materials, processing or consolidating data, building questionnaires to interview SMEs. So yes, we are seeing it. I mean, and it is not where we're seeing it.

We're expecting it from our teams, right? From at Kearney, we have developed with our Center of Excellence, a couple of tools that actually are specifically designed for that purpose. So right now, the expectation from a consultant that is just starting is, you're going to leverage AI, but the expectation is higher because now we know that you can tailor these materials in a more effective way to communicate with the clients.

So in terms of gruntwork, yes, repetitive tasks that don't necessarily add a lot of value, those are getting reduced. But now, the expectation from a consultant, especially one that is joining as an analyst or as an associate, is that they're thinking through all of the different implications and how to make this a better deliverable for the clients. Now, that is on one end.

The other is, when we get feedback from a senior stakeholder about a change or a what-if scenario, we had this exercise with a CEO of a transportation company a couple of months ago. We went out of the steering committee and they wanted us to test something. It is a lot easier for us to experiment and come up with an answer to a client than it was before.

So yes, again, we're thinking more and hammering less. That's how we will describe it.

John, what about you?

Yes, my expectation is that industry-wide, the notion of using GENAI for content generation is largely permeated the industry. The expectation is that that is going to continue. The interesting thing, and I will let those who actually lead the innovation parts of our practice announce that in more public realms when they're ready.

There's a variety of innovations that are coming up that are going to be changing the way that we do a large portion of the work that we're doing right now. And so I referred a little bit earlier to this notion of the jagged frontier. So yes, my expectation is anybody that is looking for a career in management consulting should look forward to having an assistant, if you will, a go-to, well, not person, but thing that's going to make them that much more efficient than what they're doing.

While at the same time, we should be looking out for significant innovations that are going to be coming about in changing parts of our client's business and in doing so changing the way that we're doing our business in terms of both strategizing and implementing some of those solutions.

John, in particular, what do you think the impact will be on some of the thought leadership, I would say? A lot of times we've had thought leadership from firms like KPMG that have taken years to develop a perspective on something. And it's been a big part of that tip of the spear in terms of building client relationships and expertise in this space.

Do you see any disruption potential there?

Well, yeah. And disruption in terms of cycle time and speed, general speed, and being able to produce more of that thought leadership. And so there's great value, as all organizations are seeing right now, in terms of being able to generate text or image or video on a more rapid basis to make it easier to ingest by anybody in an audience that we're trying to reach.

Love it. I'll move on to the next question, and I'll give this one to FTI and LEK. Y'all can answer in whatever order.

I want to move on to a question just around our audience, around skilling up. So what skills would you like to see your current and future consultants learning to set themselves up for a successful consulting career?

I'm happy to go and reverse alphabetical order this time. So your question is what skill do we want to see develop? Obviously, as it relates to things like ChatGPT, how do you effectively take this and implement it into your daily workflow?

It can organize your notes for you, it can build out on your list of hypotheses. There's habit there that you can build in terms of how you utilize this type of technology to make you more efficient, to make you spend more time thinking versus hammering nails to use Alfredo's analogy there. That's absolutely something.

But whenever someone asks me what's the key to success in consulting more broadly outside the universe of AI, I always say develop a nose for the nuance. We're always hired for the toughest questions on the shortest timelines. The answer doesn't need to be complicated, but it needs to be grounded in true context of our client, their market, their situation, where their business has been, where leadership wants to take them.

All those things need to come into play. And if you're able to find that nuance and communicate around that nuance, you'll spend 80 percent of your time on the 20 percent that's going to create the real impact, to use the cliche almost there. Where people struggle in a career of management consulting, as they come in, they take this problem, it's drinking from the fire hose, they don't focus to the nuance, and then they try to do everything.

And that leads to many longer hours, more disappointed clients. So I think as you learn this practice, and you build this practice for yourself, really understanding that you have to find that thing to go deep on and then go, you can't try to tackle it all.

Love it. Kyle, what about you?

Yeah, I think building off what Dan said, I think for me, what's really critical for current and future consultants, really understanding, I think, how to be what I'll call a tech translator. It's really having the ability to effectively communicate super complex technical concepts to non-technical stakeholders. And I think as AI and digital technologies become more critical to what we do and just to what our clients do and to how the world functions on a day-to-day basis.

I think bridging that gap between technical expertise and business leaders is going to be increasingly important to the consultant toolkit. And I think being this kind of tech translator can allow new consultants to create value in a couple of different ways. I think providing valuable insights in a new and interesting way, helping facilitate decision making, maybe identifying new opportunities other people weren't aware of or haven't been thinking through, helping mitigate risk, because you can help really understand how these technologies function and then helping drive innovation.

And if I was giving advice to people looking to think through how to be a tech translator, I think it's one, try to build technical expertise. I think all consultants would agree being a lifelong learner is super critical to being a successful consultant. I think that's especially true when thinking about burgeoning technologies.

Two, really working to enhance your communication skills. I think, akin to what Dan said, like, can you work, can you think through nuance? Can you take really complex, large ideas and concepts and boil them down to what's critical?

And then I think really working to cultivate relationships, fostering connections with technical experts, whether you're in school now or just out in the field to make sure you're staying informed about industry trends. So I think that's really where I encourage people to kind of think through and focus their energy.

I love it. Well, I'll move back to the full group now. And John, I'll ask you to kick this one off, because I bet you think about this one at least every other day, if not every day.

And this is like, show me the money, right? From a consulting perspective, how does this going to impact how we price? And you mentioned already, you're getting some pushback from procurement officers that are saying, hey, y'all are getting efficient.

We should share those efficiencies. I'm guessing this really should be a tale of the art of the pushback because you know and I know that our talent isn't coming any cheaper than it used to, that our overheads are not cheaper, that nothing for us from an actual functional input cost is coming cheaper. So efficiency gains from a value perspective are probably shared.

I would just love to know how you're thinking about this. And I'll open up the floor to everyone to weigh in on this as well.

Okay. I'll start with this. You can't charge for an hour that doesn't exist.

And so, most of our entire industry charges by the hour for the resource. Well, if we consider that 90, 95% of all the work that is performed right now is done by resources, and in the future, that number is going, that percentage is going to be far less, and most of the value will be provided by something else, perhaps GenAI, then we have to rethink the way that we're charging. Because if you charge for an hour that really is a very small part of the overall value being provided, then how do you actually set a price?

And does that mean that the price pressure is going to be increasing and coming down? Or perhaps if we think about it in terms of value, how much value is being delivered in what we're actually providing to our clients, then there is an easier anchor by which we should judge the work that we're doing. So is it going to be a game of returning ourselves into software organizations, or is it going to be as it traditionally has been, which is it's all about the people in the relationships that make it work and the value of the people in those relationships that change organizations in which we're going to set price?

Very interesting conversations. Do I think about it every day? No, I don't. I think about it every hour.

Well said. Who else wants to weigh in on this important pressing question in the industry right now.

So I'll add a point. There's a point around our efficiency as consultants, but there's some other expectations that are changing in the client that influence our pricing model. One is, with AI, a lot of the expectations are also on tangible results. By tangible results, you mean you have to have either an AI tool or an AI solution that arises as a lead behind for a project.

And ownership, maintenance, those factors definitely influence on your price. And there's a third component, which is who do you come with to the table? If the client is already working with a large hyperscaler, and you just want to be a part of that engine to help the solution at the right value, then how do you incorporate that into the contract and the pricing decision?

Now, functionally, even though the delivery model changes and the efficiency has changed, and for the audience, the expectation changes because if you're charged now by value that you create or by anticipated savings, there might be additional stress in the project for delivery. The highest impacts on how projects are priced for a new consultant is mostly related with who are the stakeholders you're going to be interacting with for project delivery. But nothing more would change from their perspective.

Dan, go for it.

Yeah, I was just going to say, we don't really price to the hour, directly at least. We price to the value that we're creating for our clients, and at least that's the aspiration. Now, I've worked in multiple forms of consulting, and usually you do that by saying, well, it's going to take us a month to create that value, and therefore that's four weeks of team time, and that's X amount of dollars.

I think AI may shift timelines, and they shift the composition of our teams. I think the knock-on effect of that is going to mean that we, as an industry, have to price to value a lot more closely than we price to it today, and not use time as a proxy to value. That may mean risk sharing with our clients, realizing true outcomes both in terms of profitability and efficiencies and in sharing in that upside, but also puts more burden on us to communicate value as part of our sales process and get management buy-in to what that value is and how it should be appreciated.

So I think it's going to raise the stakes a bit in terms of what we ultimately use for a revenue model in the industry.

Awesome. Kyle, you have anything you want to add to that?

No. I think everyone really hit the nail on the head there. I think at the end of the day, it's a people business and it's about delivering value to clients. I think while we may define that value in a somewhat different fashion over time, I think that's really what's driving how we're pricing our services and what we're driving for clients. So I really agree with Dan and echo his sentiments there.

So there's a question in the chat that I think really articulates a very clear version of this. We're going to move on to audience questions now, so I'm just going to jump over to that one because I really like it. The question is basically, AI is expected to eclipse PhD level intelligence in a few years.

So at what point are consultants wiped out? When are they gone? What I want to share just as a genesis of this is something that I've articulated as I've watched a few waves of this happen, and I want you to agree, disagree, or clarify.

But basically what I've said is that AI is another version of noise that organizations don't know what to do with, and they need help navigating the noise. And that was the same thing when we saw cloud computing and it was the same thing when we saw machine learning. And every advancement in technology has not reduced noise, but rather added noise into decision making processes, competitive landscapes, and prioritization.

I do not know if you have a perspective that you think AI is different, the same, or you would like to clarify that. So jump in, jump in on the conversation. When do consultants go away?

Maybe I'm blind to it, but I don't see that happening. And I guess I agree with you. I think there's one qualification, though.

I think there's a question of, does AI add more noise as a topic that our clients need to deal with? Absolutely. Does it add more noise to their own workflow and their ability to kind of do what we do to help support their businesses?

I think so as well, right? I think AI is a tool. It's great at bringing information and distilling information. But the way we add value isn't by communicating information. It's about communicating insight. What are you going to do?

And that takes instinct. That takes understanding of complex markets. It takes an understanding of markets very far away, perhaps as analogs, to the very question that we're being asked to answer at this point in time. So I see it as an enabler to our business. It might mean team structures change. It might mean team skills need to change.

But I'm hard-pressed to believe that our clients are going to be able to ask the AI machine to do the work that we're doing. Because again, it's always about the most complicated of things, where they're resource constrained, where they don't have the bandwidth, where they don't have the insight beyond kind of the four walls of their business. And they might not know the prompt or the question to really be asking.

And that's really, I think, where our value has always been hiding.

Yeah, and I'll add to that from an implementation perspective. When we think about bringing change to organizations, it's people that are changing. You know, we're not wiping out consulting because we're not wiping out businesses either.

Ultimately, it is people who are going to have to operate differently and work differently and have different kinds of skill sets. And it's people who affect people. And so I don't see the human factor going away because ultimately at its consultants are and always have been providing advice and showing the what good looks like and providing that kind of transformation.

So I don't see it going away. I see this certainly as a as a hip check toward changing some of our business models, but I don't see it as a destroyer of an industry. It was interesting that they said, talked about PhD level knowledge.

That's great. A room full of PhDs is not going to be changing a Fortune 500 company. It's going to be a group of people. Not that PhDs aren't people and not that I don't want them.

John, what are you saying? Awesome. Everybody doesn't have to weigh in on this. If you have something additive, though, feel free to jump in.

And I have a few other just kind of popcorn questions that we'll go through.

Just a quick note, and the reason why clients trust us and they hire a consultant is based on our relationship of advisory and trust. They're looking for an external perspective, right? And AI, I mean, you just don't hire a consultant because you need someone that is smart.

So our values are a lot more nuanced, and then that is also going to evolve, but that doesn't mean it disappears.

I love it. Kyle, do you think consultants are going away?

I do not think they're going away. I mean, I think we're kind of all aligned here. I mean, it's not just about kind of bringing in the smartest people possible. It's much more nuanced, right? It's very people-driven, experienced, driven, as helpful as these tools may be. I think they're really augmenting what we do and supporting what we do.

They're not replacing the true kind of value add up consultants, right? And they're so much more beyond just kind of the intelligence and expertise that we're hopefully bringing, right? There's the relationship building and the kind of deep kind of understanding of client needs and kind of that EQ perspective, right?

And the fact of collaborating and building teams and all these things that are totally intangible and in no way can be replaced by technological tools. So even though I think it will help us work better, it definitely isn't a replacement for the whole kind of spectrum of things that a consultant provides to a client.

And maybe to summarize, it sounds like if business is still hire people to staff them, consultants will still be required, right? Once the computers take over 100 percent of it, then we won't be necessary. But up until that point, we're probably an important part of the ecosystem.

Let me move on to a few audience questions. For these ones, I just need one or two answers. Please, everyone doesn't need to weigh in.

And just one minute answers for each of them, but I'll do them popcorn style. And I love these, because I think this is exactly where our folks are. Number one is just, what is the top AI use case for a consultant beyond basic brainstorming applications? Go ahead, Kyle.

I was going to say, I think there are some really good, strong use cases around things like project management, knowledge management, collaboration, right? There are a lot of great tools in the market that integrate GenAI and AI to do those types of things, where it's not just about ideation, but kind of helping you organize and helping you sit through information. So I think those are a couple of really easy use cases that are quite widespread, that are pretty value creating.

Dan, you want to weigh in too?

“ame thing. It's all about my process flow at this point. How do I get more efficient?

Before every meeting, I'm writing in the five or 10 bullets into it and asking it to build out some points there. And it's not things I don't know already, but it's taking what I do know and just helping me pause, break, move to the next meeting in a structured fashion. And that's just kind of building the habit of bringing it in the same way you use Teams, the same way you use Outlook using ChatGPT just to bring more efficiency to your deck.

Love this one. Next one, what professional development plan does your firm have for consultants using AI? If any.

It's not something that we're moving slowly on. I'll say that we've built out internal tools to kind of, if you think about our assets, they're our team and they're our intellectual property. And that's kind of the two things that really help us win and help us do good work.

So we're building the tools to organize that IP to create more accessibility and curation to our teams to help them accelerate. And then we have to train our teams against using the tools that we're building, using the open source tools to help with their own efficiencies. And it's been instilled alongside all of our other professional development programs just as modeling bootcamp happens for all of our associate consultants.

It's right alongside that curriculum.

I would say three on our end is quick. We have trained the partners for how to talk with clients, trained the technical teams of how to roll out and develop tools. And then there's a sweet spot for the associates and the management consulting teams that is aligning those two fronts.

So I'll link to those trainings next week and we're excited about that.

Awesome. So you're not sleeping on it. This is great.

Let me let me ask another one. Can you provide one example of how AI helped a client in a specific industry with a specific challenge? Can you give me just like a very high level one minute case study of, this is the question the client came with, this is something that they did. But this is how it affected their business.

Yeah, I can go first. I can give a quick one. We had a large financial institution who had a very kind of manual, high touchpoint process for onboarding new clients, whether that was businesses or individuals.

So we worked with them to build out an AI driven know your customer automation tool to automate a lot of that processes and to allow basically their compliance associates who were doing those onboarding reviews, to spend their time digging in to thorn your issues and really spending time doing risk reviews that really made a difference to them. So that was a really interesting project combining automation and AI and a bunch of different kind of technologies with kind of a user interface. So kind of a cool, interesting problem that we had a specific solution for.

I have an interesting one. We have a giant retailer. They have a super complex shipping operations. And basically, they struggle to train their teams on how to gather data from all the different sources and then prioritize those sources to come up with their perspective. So we built an AI engine that categorized all the insights that came from the different PDFs and all of that information, matched it with their data and then simulated their decision-making process to offer alternatives. That was super exciting.

Love it. Anyone else? I think this is worth it for another minute or two. Dan or KPMG, if you all want to share anything.

Yeah, we, you know, recently we had a, it was in B2B Information Services, and they were looking at kind of subscription-based offering and revenue retention kind of risks that existed there. And ultimately what we ended up doing is kind of adjusting all of their customer data and looking at all the signals that could lead to early identification of customers lapsing. And, you know, there's a process there.

We did our regression-based testing, of course, looking at kind of some of the upsell and customer churn drivers, but ultimately kind of assess 12 or so different AI ML models and landed on the right solution for them. And now it's an actual tool that sits along all of their other enterprise platforms that their sales team uses day in and day out to kind of track against, you know, what's happening in their and within their sales book and giving them the information they need to go out more proactively and touch customers when that risk exists.

All of you have mentioned some form of sales enablement, both for your clients and also internally, with this kind of advancement of AI. Last question is just, how do you foresee striking the right balance between utilizing AI and maintaining human touch? Are there any risks there?

Well, the acronym we like to use is PQRST. Price, quality…

That is such a KPMG acronym. Thank you. Go for it.

Price, quality, risk, scope, and timing. So, as mentioned previously, that really is the challenge that we have, which is quality and risk, and how that gets balanced. Clients…

And I saw, actually, there was a chat question that was in there, too, that said, do you think there's a future, if I read it correctly, do you think there's a future where resources, human resources are going to be coming as a premium? Well, we're actually living with that right now. I think we all are in the industry, which is a named resource actually can demand rates or prices or compensation compared to somebody that is otherwise considered fungible by the client.

And so as we think about getting into and shifting more toward value and selling based on values, some of that value comes with brands, some of that value comes with the resources that you're bringing to bear, and potentially some of that value is going to be coming with the tools, especially when those tools are providing such efficiencies that they're part of the overall value story to be told to a client.

Fantastic. Well, thank you all for this really dynamic conversation. I could personally go on, but I know you have schedules and so does our audience. I want to just wrap up with a round robin and we'll go in reverse alphabetical order this time if we can do this. I think we can. Dan, we'll have you go first.

But what I'd just like to hear is one concluding hot take about how AI would affect the consulting industry and any advice that you have for the folks that are here today. Go ahead, Dan.

I get to go first. I get to take the easy one. I think it's going to increase the need for consulting more than it hurts it.

Boom. Well done. That's it. Mic drop. Everybody else has to think of a different one. I love it. John, what about you?

Okay. I'm going to repeat. You can't charge for an hour that no longer exists.

So as we continue to gain efficiencies by using any of our AI tools, we must be shifting toward selling based on value. More value, more that we can tie value to our price, the better off we're going to be as an industry.

Love it. Alfredo, what about you?

Yes, I had to change mine. Apparently, mine wasn't as hot as I thought it was going to be. So I'm going to change it into… In five years, many fewer things are going to change that people are expecting now. Everybody thinks that we're going to change the world and the entire industry is going to… No, we don't change that fast.

Technology does, but people and WebRice Consulting relationship doesn't change that fast.

I love it. Kyle, what about you?

Hard to follow all these hot takes. This may not be that hot of a take, but I think AI is really going to be a cornerstone of the modern consultants toolkit. And I think looking across all firms, all levels, I think using these tools, understanding how they function, really integrating them to building practices effectively is going to be table stakes.

And so encourage people to experiment, to use them until they understand how they work.

Thank you so much, everyone, for joining today. Thank you for our entire audience. I just want to give a shout out.

I think you all were very spicy, very opinionated. Also, I felt like I was thinking about new ways that I could integrate AI into my workflow. And so, thank you for sharing some really tactical ideas for how we could think about that.

I also think that we are in an interesting moment, and I can't wait to look back on this call and see how right or potentially how wrong we are. And it'll be fun to be a part of shaping the future together. So thank you all for your perspectives, for the work that you're doing.

We champion you. We're grateful for you. And thank you, everyone, for joining today.

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