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Episode 7. Publicis Sapient CEO Nigel Vaz: Redesign Your Operating Model Before AI Redesigns You
254 Plays1 month ago
Redesign Your Operating Model — Before AI Redesigns You
with Nigel Vaz, CEO of Publicis Sapient and author of Digital Business Transformation
"What you don't want is faster caterpillars; you want real butterflies." — Nigel Vaz
What You'll Hear in 35 Minutes
- Why AI is a chain of "sequential watershed moments," not a single leap
- The S-P-E-E-D framework (Strategy, Product, Experience, Engineering, Data & AI) behind Publicis Sapient's transformations
- Tackling the $1.5 – $2 trillion technical-debt mountain and flipping the 80/20 "run vs. change" budget
- How Slingshot and Bodhi bring agentic AI + industry patterns into the SDLC to kill "spaghetti code"
- Moving from "tools" to a digital-workforce mindset (Iron-Man-in-the-suit analogy)
- Culture shift: learn → unlearn → relearn as an executive super-skill
Guest Snapshot
Nigel Vaz has spent 25 years at Publicis Sapient and became global CEO in 2019. His best-selling book, Digital Business Transformation: How Established Companies Sustain Competitive Advantage, introduces the SPEED model that Fortune 200 leaders still use to frame end-to-end digital change. Vaz now spearheads the firm's agentic-AI platforms Bodhi and Slingshot, aimed at collapsing delivery cycles and slashing tech debt for Global 2000 clients.
Timestamps
00:00 — Origins: from early internet banking to CEO
03:30 — "Sequential watershed moments" & the post-Turing era
06:11 — Technical debt: why $2 T blocks innovation
11:00 — Fear vs. action: only 15% of firms truly embracing AI
14:45 — Inside Slingshot: combine-harvester for the SDLC
20:45 — Services-as-software: blending people, products, outcomes
24:55 — Operating-model redesign & the Iron-Man analogy
29:15 — Governance moves from review boards to real-time guardrails
34:30 — Closing thoughts: learning > knowing in an agentic world
Resources & Links
Book – Digital Business Transformation → https://www.publicissapient.com/insights/dbt-book-preview
Sapient Slingshot overview → https://www.publicissapient.com/solutions/sapient-ai/sapient-slingshot
Bodhi agentic platform → https://www.publicissapient.com/solutions/bodhi
Follow Nigel on LinkedIn → https://uk.linkedin.com/in/nvaz
Follow Phil on LinkedIn → https://www.linkedin.com/in/pfersht/
Enjoyed the episode? Follow, rate ★★★★★ & review From the Horse's Mouth so we can keep the bold, practical AI-transformation talk coming to your feed.
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Transcript
Introduction and Podcast Overview
00:00:12
Speaker
You're listening to From the Horse's Mouth, intrepid conversations with Phil First. Ready to meet the disruptors who are guiding us to the new great utopia by reshaping our world and pushing past corporate spin for honest conversations about the future impact of current and emerging technologies?
00:00:30
Speaker
Tune in now.
Guest Introduction: Nigel Vaz, CEO of Publicis Sapient
00:00:36
Speaker
I'm Phil Fersht, I'm the host of the Horse's Mouth podcast. With me today, I'm very excited to welcome back an old friend and a very respected voice in the industry, Nigel Vaz, who's the CEO of Publicis Sapient, which is a major digital business transformation company Nigel's also authored a great book that a lot of us have read, which is Digital Business Transformation, How Established Companies Sustained Competitive Advantage from Now to Next.
Nigel's Career and Digital Transformation Journey
00:01:08
Speaker
So without further ado, I'd love to welcome Nigel to the pod. Hey, everyone, and thanks for having me, Phil. It's great to be on. Your company's been making quite a bit of waves, particularly in the last few years in the industry, particularly around ah CX impact and digital transformation.
00:01:24
Speaker
But maybe you could give us a little background of yourself, the business that you joined and what the business is looking like today. I started my career very early in with the advent of how the internet was going to transform business, which is very much, I think, sapience genesis. How is the internet going to transform business was the question we were asking. And transform, I think, was the operative word there because a lot of businesses did things with the internet. They built websites, they built internet.
00:01:50
Speaker
e-commerce businesses as was
AI Disruption and Business Strategy
00:01:52
Speaker
in the in in the retail space. But really the transformative power of what the internet could bring came from launching some of the first online banks and the first online retail businesses.
00:02:02
Speaker
The first time you could pick a seat on an airplane, the first time you could buy equities. And you started to kind of realize the magnitude of that kind of transformation across sector. And so fast forward to today,
00:02:13
Speaker
I've been with with Sapien for almost 25 years, and the journey has essentially come from how is the internet going to transform business to essentially businesses are inherently digital and now AI enables slash disrupted. And we're at a very similar moment in time to what we were back in the 90s. And if I think about where we are today,
00:02:35
Speaker
That moment in time is essentially creating yet another leap. But before we get to that, our core business over the last decade or so has it really been about around this premise that in order for most businesses to not just survive in the digital context, but really thrive,
00:02:50
Speaker
they needed to operate very differently. And we summarized this in an acronym I wrote about in a book called How Do Established Companies Sustain Competitive Advantage? So the title of the book is Digital Business Transformation, How to Establish Companies Sustain
Sustaining Competitive Advantage Through Transformation
00:03:07
Speaker
Competitive Advantage. And the reason for that ah orientation is because it was aimed at our primary clients, a big fortune 50, 100, 200, who are really leaders in their space, but needed to really meaningfully transform in order to sustain competitive advantage. And we summarize this in an acronym called SPEED, and it stands for Strategy, Product, Experience, Engineering, Data, and
Is AI a Watershed Moment?
00:03:32
Speaker
AI. So
00:03:33
Speaker
And our belief was that these, that acronym sort of like fingers in a hand have got to kind of work together those capabilities in order to really help companies lead. And so that's been sort of my journey and a little bit of our journey over over that period of time.
00:03:47
Speaker
Are we generally at a watershed moment with the advancements of AI, particularly in the last two to three years? Is this a watershed moment in your opinion, or is this just a gradual evolution of technology as it matures?
00:04:00
Speaker
I think it's anything but gradual, right? Because you're starting to see both the rate of change and the scale of change start to really pick up. The thing about a watershed moment is I'm not sure if it's a watershed moment or a series of watershed moments that will each exponentially move us significantly further beyond what
The Need for Business Reimagination
00:04:20
Speaker
we've imagined. Like as an example, very simply, right? We just passed the Turing test moment.
00:04:25
Speaker
very recently, right? And like almost little noise has been made about this, as you can imagine. And when you think about that for a second, I'd say 10 years ago when we talked about artificial intelligence and we were building machine learning models and using predictive AI to drive insights,
00:04:42
Speaker
The Turing test moment was almost like this mythical thing that would one day happen in the future, right? And we just passed that ever so simply in the last couple of days without it even being kind of a huge topic of conversation. And the reason for that is because of the expectations that I think AI has built in the minds of all of us as people now, where these kinds of watershed moments don't even seem like watershed moments. They just seem like a series of sequential watersheds, each propelling us exponentially further.
True Transformation vs. Superficial Changes
00:05:16
Speaker
So for me, I feel like we're on that continuum where the rate of change and the scale of change is really growing exponentially. And in that respect, it's going to really force companies and us as people to reimagine ourselves, as opposed to simply think about incremental progress. So yeah I often use this word in the context of transformation is what you don't want is faster caterpillars, right? You want real butterflies, which was a George Westerman quote out of MIT, which is where Sapient was founded right outside the MIT campuses. And that, I think, is today where we find ourselves.
Technical Debt Challenges and Strategies
00:05:51
Speaker
Yeah. When we look at the challenge facing enterprises, you were at our summit last year, and particular, we talked a lot about technical debt. There's such a frustration in the industry of companies who don't want to keep spending 10% more each year on their licenses, on their providers. It's, well, how do we get more from the same? How do we actually change the model and start to look at phasing out areas of technical debt? I mean, what are you seeing that maybe is working and what isn't working with your network and your your clients?
00:06:24
Speaker
I think the first thing that we should acknowledge is what you just said, right? This is probably the single biggest barrier to innovation, agility, and growth. We're talking about 1.5 to 2 trillion worth of technical debt across the global 2000, right? And that's definitely not something to sneeze at, particularly when you think about this massive IT services industry that was largely built up around maintaining and managing most IT budgets in the context of
00:06:56
Speaker
operations and outsourcing as opposed to real innovation. So a lot of the conversations I'm in with CEOs, businesses is how do we go from spending the amount of money we spend where 80% of it is going toward maintenance and operations and 20% of it might go toward innovation? How do we invert that ratio?
00:07:15
Speaker
And the biggest challenge in doing that is essentially the amount of technical debt that you spend. are dealing with as most institutions, right? And for years, I think historically, this has been sort of tried to be solved by, well, we'll outsource, we'll add staff, we'll move people offshore and maybe do some automation on the fringes, right? But these problems weren't necessarily solved by them. They almost institutionalized it. We normalized this idea that companies essentially promise modernization, but are delivered bodies, cloud bills, legacy systems that just won't die, right? And that entire journey is essentially, if you are a non-technological leader, and you're kind of looking at this, you're saying, we really do need a fundamentally different approach.
00:08:02
Speaker
And I feel like both where we find ourselves in in in the context of AI and where we find ourselves in the context of the size of problem this has become for enterprises, both together provide potentially a very different approach to how we think about this very differently, right?
AI Tools and Their Impact on Business
00:08:23
Speaker
Our belief is that this is essentially not something that you just add on and, you know, incrementally continue to do, right? But you really fundamentally can transform in a very meaningful way, right? You almost blow up the old model and you can start to really transform.
00:08:43
Speaker
reimagine how companies have thought about legacy applications, legacy code, huge areas like integration and testing, and do things that was going to take a decade in a couple of years. And I think we're seeing that kind of impact with our clients.
00:08:58
Speaker
Because again, Just from a positioning perspective, right? Sapien always operated on the transformational end of the spectrum. So we were never the guys that essentially you called in to simply outsource large amounts of your legacy and do it at a lower cost.
00:09:12
Speaker
That wasn't the business we were in. And so to us, it was a huge amount of frustration also that so much of our clients' investment and time was caught up in essentially just maintaining this status quo. The spaghetti code and the leaning tower of Pisa, the more you spend, the harder it gets to change and the more expensive it gets to change. Right. And you're waiting.
00:09:34
Speaker
But actually, the reality is that the tools and the platforms to really take a fundamentally different look at this weren't there
Industry Reactions to AI
00:09:45
Speaker
for the longest time. And I think now we're at a very different point.
00:09:49
Speaker
so Other tools there. I mean, this is the first thing. I mean, we see incredible advances in 506, quite professionally available AI tools. I find them tremendously valuable just for my own job.
00:10:02
Speaker
I have like my own research assistant now in ChatGPT. I get real value from it. As an analyst company dealing with information, we're going through a lot of positive transformation because it's actually helping us do our jobs better.
00:10:14
Speaker
But when we talk to... enterprise leaders across the global 2000 and 45% of them they're scared they're living in fear of this change and and only a small amount about 15% are I think really embracing this and making the cultural changes necessary to make the shift does this mirror what you're seeing in the industry right now where you've got some companies just struggling to move and others ah ah others are getting it I mean mean what needs to happen to sort of shift the needle here
00:10:46
Speaker
I think there's a couple of things, right? I think first, when you look at where the largest amount of oxygen in the conversation is today, right? It's very similar to the parallels I draw with the early days of the internet. I don't know if you remember what the most valuable company or one of the most valuable companies in 1999 was, right? It was Cisco.
00:11:06
Speaker
Yep. yeah you were essentially because they were connecting the backbone of essentially the internet and then from there we went into the browser wars all the conversation about netscape internet explorer and all of that but where did most of the value from the internet come from. It came from the application tier above that hardware and the platforms that you use to access those applications, i.e. the browsers.
00:11:33
Speaker
And that's where most of the value came from, right? And I feel like with AI right now, when you look at the oxygen space of a lot of the conversations, right? There's a lot of conversations about GPUs and TPUs and chips, and that's important.
Transforming Businesses with AI and Agentic Architecture
00:11:46
Speaker
But I feel like the advances that are going to be made there right are going to mean that we have an incredibly power hungry yet an incredibly fast continuum of evolution of how those chips are going to enable the future yeah the next layer up above that is are are all the models you know there's constant comparisons and conversations about the various different models All of us, like you mentioned, you use ChatGPT to drive research, and there's plenty of examples of Claude's new model.
00:12:17
Speaker
But the real value for the Global 2000 from AI is going to come from, okay, once you have the chips and you have a plethora of models that you can choose from for every task possibly humanly imaginable, how do you leverage both of those things to fundamentally transform your business?
00:12:34
Speaker
How do you actually create value from your data sets? How do you actually codify uniquely specific industry patterns for your organization in the context of agentic architectures that resemble a digital workforce, right? How does that evolve?
00:12:52
Speaker
And that is where I think we are barely scratching the surface of what you can loosely call tools, right? Because there are tools of all description, But I'm not necessarily sure we should imagine a world where these tools are going to get to a point where you can simply say, hey, I have this tool, therefore I am sorted, right?
00:13:15
Speaker
And i think that was a lesson many companies learned through the software evolution of the last 20 or 30 years, right? Just because you have the software platform, it didn't necessarily mean out of the box, as in like an actual literal out of the box.
00:13:32
Speaker
And I feel like the AI wave is at that very early stage when you start to think about the kinds of tools you need to use to solve very specific things. Yeah, yeah. I mean, agentic isn't is so exciting because it's all about where this could go, but it's ah not enough about where this is currently being utilized. And now you guys have got a tool called Slingshot, right, which goes beyond just the off the shelf, chat GPT, clawed stuff. Can you talk a bit about that and how you're introducing that into your client environments?
00:14:04
Speaker
Yeah. and And look, I think the first thing, like I said, right, we I often use an analogy that I'll use just to kind of frame this. Right. I think you have to think about AI in the context
Slingshot: Modernizing Enterprises
00:14:14
Speaker
of I'll use an analogy of like Iron Man.
00:14:17
Speaker
You need to invest in the suit. in order to essentially create real value, which is like a tool, if you will. But the suit has to function in conjunction with a person or people in order for you to get that true superhero effect.
00:14:33
Speaker
Just an incredibly well-built suit is only going to go so far. But when you kind of harness the two together, you get kind of real acceleration. And that's our orientation or our framing for Slingshot.
00:14:43
Speaker
Slingshot's powered by a David mindset. and not a Goliath mindset. And if you have a bunch of Davids and you have Slingshot, you look very different than a Goliath, which was built on ah on the model of hundreds of thousands of people, humongous scale, where your business model around people fundamentally gets in the way of clients essentially being able to transform because your primary objective is to get your people into them, which by definition is exactly diametrically opposed to them freeing themselves of people and moving faster. But I think it has to be done in conjunction. So if I were talk about Slingshot, the way I think about this is we started by essentially building an agentic kind of architecture on a platform called Bodhi, which was all about building the knowledge of our transformations over the course of numerous years, embedding in that industry patterns, if you will,
00:15:41
Speaker
thinking about value creation, scalability, essentially being a driver of transformation in this new world, right? And on top of that, we essentially built Slingshot, which is very simply an AI-powered delivery model to essentially play across the software development lifecycle, where you're not just speeding up development, but you're helping enterprise modernize deliberately and pay down tech debt at scale.
00:16:07
Speaker
So what makes it different from why it's not just a generic use of Gen.ai, right? Clearly it's powered by a model hub and inference models that are specific to us, right? Where we built prompt libraries built by industry specialists that allow us to encode hard-earned institutional knowledge. So we're not starting from scratch each time, right? That's how we reduce and rework quality.
00:16:31
Speaker
It's drawing from huge amounts of industry context, but also our clients context on very specific domain assets where we bring their enterprise knowledge into the mix. So the AI is grounded in reality, not hallucination. Right. So fewer blind spots, fewer do overs.
00:16:47
Speaker
Context binding, which ultimately keeps the thread across workflows, tools, and teams. So you're not resetting context across each of these handoffs or rediscovering requirements in every sprint.
00:16:58
Speaker
This is particularly important, right? Because you started this conversation by talking about tools, right? And it's a little bit like the difference between, I'm going to use a rudimentary thing, right?
00:17:09
Speaker
But, you know, a combine harvester for a farmer, right? Which does... many, many different actions across the process of farming together.
00:17:21
Speaker
Because what they found originally when they built a tool for each thing, that it was much faster for the farmer to use his hand than have one tool to do this, and then another tool to do this, and another tool to do this. And they put them together in a combine harvester of sorts, right? And this is what we've noticed. This is the best tool for coding. And that's the best tool for testing. And And of course, across that, and this is the best one for user journeys. And then across that, you've got 19 tools that actually for a good developer and a smart designer working together will slow you down, not speed you up. So we explicitly built Slingshot to address this issue.
00:17:56
Speaker
And then the final couple of components really was, like I mentioned, an agentic architecture to ensure that decisions are not only being made in the right place at the right time with the right memory, but also in the context of long-term planning and real-time execution factored in.
00:18:12
Speaker
And then finally, intelligent workflows that are bringing it all together with pre-configured patterns for complex use cases, which ultimately are the thing that really accelerate you without you losing in control. So we're very thoughtful about where do you want the human in the loop and where do you want these things to essentially be exponentially moving forward, right? So you're architecting that. And we did that, by the way, by eating our own dog food. We did it for ou ourselves.
00:18:38
Speaker
We did it to make ourselves more efficient. And in doing that, we're now able to take that to our clients because we understand they have the exact same issue across the entirety of the life cycle of those journeys.
00:18:52
Speaker
So does this make you more of a software first services business? You've obviously heard about services and software is
AI's Role in Merging Services and Software
00:19:00
Speaker
the phrase that we'd coined, but this feels very much like a change in mindset on how clients engage with technology partners in general.
00:19:11
Speaker
Yeah, I mean, this is why I definitely think, right, you have to really think about this very much in the context of what is the physical workforce and what is the digital workforce, right? Because effectively, I don't think you are going to have to think about these things as human beings with tools.
00:19:26
Speaker
I think what you're going to have to think about is I've got a series of agents that are built on the context of what we've delivered before. And I've got a series of people who understand how to leverage these and work with them in order to deliver.
00:19:38
Speaker
So I think this idea of a services business and a software business also in the near future, right, will start to get appended because software businesses and services businesses, essentially the real separation was a tool versus a human.
00:19:54
Speaker
And I think what you're now going to start to see is a human who is augmented with tools. So it's a little bit like why I use this Iron Man and the suit analogy, because yes, we're not in the suits business.
00:20:04
Speaker
We're never going to be selling suits to people, but we're not also only in the people business anymore. We are in the superheroes business, which is that continuum from person through to all of the tools that make them that augmented person that they are.
00:20:19
Speaker
Right, so how do you shift the culture within company to get people excited about being iron iron men, iron women, whatever, right? How do you do that? Because I think this is the biggest challenge is, one, everybody knows how to use the basic tools at this point, but then how do you generally take the next step building out an ah agentic architecture and get people to take their day-to-day tasks and activities and start to create, we we call it like your synthetic self.
00:20:53
Speaker
How do you start to take your network, the way you operate, your work repository, your IP, this type of thing? It's incredibly valuable. I mean, you could even think about, you could build a company of people.
00:21:05
Speaker
And if someone leaves your organization, they have a synthetic version of what they were doing. So it actually ensures you as a business that you're not just losing a tremendous amount of IP because someone valuable left your business.
00:21:17
Speaker
But how do you break that cultural barrier that we're seeing and in so many companies right now? I think the first thing to breaking a cultural barrier here, right, is not to repeat the mistakes we made in the past. If you think about how technology and software and IT was introduced into the world, right, it was introduced in a very poor context with poorly designed tools, not fit for purpose, in many cases had people...
00:21:43
Speaker
be slowed down before they could be sped up as those things evolve. right And for me, first and foremost, this is a mindset idea. but This is not about thinking about AI in the context of tools. like I don't like that orientation at all. I think you need to think about this as a fundamental operating model shift, right?
00:22:01
Speaker
A legacy model based on labor-intensive processes, lots of approvals, very linear workflows, they're not designed for an intelligent operating model, right? Today, you have to essentially not simply graft these tools into an old operating model and an old structure. You have to fundamentally reimagine how this works, right? Which essentially says that Starting from first principles for how are services delivered? How's value measured?
00:22:28
Speaker
How do you actually let things be modular and outcome led? um And so very practically, there are some very foundational shifts, right? The first foundational shift here, I think, which is extremely important to start with, right?
00:22:42
Speaker
Is this notion that there very simply very simply and an approach that is going to work in the same way that the siloed divisions and systems of companies work today.
Rethinking Business Structures for AI Optimization
00:22:58
Speaker
right So if you think about the classic baton passing approach of a lot of organizations, right well, this is what marketing does and this is what sales does. And once you market, then we sell.
00:23:09
Speaker
And once we sell, this is what service does. right Those were ah linear approach business approach because every baton was passed from function to function, right? They weren't essentially operating in the same way that that company before it became big and set up all of these divisions operated where one human being could connect the dots across marketing, sales, and service and solve your problem, which is what that company probably began its life as when it was a startup.
00:23:39
Speaker
So I feel like you have to almost go back to that idea of basically saying, how do you start to reorient organizations in the context of delivering outcomes in the service of the customer's journey and starting to rethink the functional structures that you've historically operated in in service of those journeys, right? So what you're trying to enable is me to buy a house, not you to sell a mortgage.
00:24:07
Speaker
And that's a very different orientation in how you would structurally set up a business if you were trying to help me buy a house versus if you were helping me get a mortgage, right? And that starts, I think, very much in the reimagining of how the value chains, which are much more seamless, work, right? So think,
00:24:26
Speaker
kind of connected enterprise, not fragmented departments, right? Because ultimately, things like AI thrives on context, and context really dies in these silos, right? A future operating model for us starts with essentially saying, how do you deliver a set of agents that really connect what used to be called the front office, the middle office, the back office, so you can create this unified flow of data, decisions, and actions, right?
00:24:52
Speaker
But of course, it starts with the people, right? We always joke that said, if you took the people out of transformations, would be easy, right? Because we as people have to essentially say, well, what does that mean for us as human beings? And I come back to something else I talk about in my book, which is this idea of like learning, unlearning and relearning.
00:25:08
Speaker
So we've all been taught like the last couple years of the AI tools. I certainly can tell you that from what I'm seeing just over the last couple years, the rate of change is only going to increase, which means that everything that you could do with some of these tools today, you're going to have to unlearn how you do them tomorrow because they're going to progress in leaps and bounds.
00:25:30
Speaker
And you're going to have to relearn a fundamentally different way of using them, right? So it's not like essentially saying, hey, this is like a bike, which is you learn to ride a bike and you get better at it and you keep getting better at riding the bike.
00:25:42
Speaker
right But imagine if you were taught to ride a bike and the bike functioned one way today and tomorrow it functioned a different way and a third day it functioned a different way. The most important skill in that instance is to unlearn everything you did yesterday and then relearn it today and then unlearn it again the next day and relearn it the next day. And this is a cultural shift.
00:26:01
Speaker
You will start to see organizations value people who wire themselves towards learning rather than knowing. The other thing I would say is governance, right? We've got to basically say, how do we move from governance bottlenecks to these kind of embedded guardrails, right? Where governance is definitely slowing lots of things down, particularly AI.
00:26:21
Speaker
Monthly steering committees are not going to keep up with autonomous agents making real-time decisions. Yet the risks are real. So rather than thinking about oversight, which is an after the fact idea, how do you actually build governance into the system from the start?
00:26:35
Speaker
Whether you start about automated controls or policy based enforcement or real time monitoring so that you can actually think about these risks in the context of how they are being delivered in the moment, not somebody writing a report and telling you about it kind of weeks later. Right.
00:26:53
Speaker
So think about governance from a review function to governance in a real-time code-driven function.
Managing a Blended Workforce of Humans and AI
00:27:01
Speaker
And I think that's, again, another one of those big shifts.
00:27:05
Speaker
and Another one to maybe talk about is this idea of managing people to managing a physical workforce and a digital workforce. So how do you actually start to manage people and systems in this model so your employees aren't just doing tasks, but they're accountable for outcomes?
00:27:24
Speaker
I do think what you are going to start to see is a world where management as a skill alone isn't going to be good enough. You're going to have to be a player coach. You're going to have to be somebody that can actually steward automation, calibrate agents, improve workflows,
00:27:40
Speaker
so that you can enable better functioning humans alongside the suit, if you will, right? So you're constantly refining both of these. So you're not doing things like coordination and tracking insight, but you're really moving forward that This is the true coming together of the C-suite, non-technical and technical people. I've seen HR heads getting really into this. I've seen CFOs really trying to understand how do we leverage this to get better data.
00:28:11
Speaker
You can really feel the pressure coming on to business leaders now from the board, from the CEO to really start to shift the shift the conversation.
Rapid Technological Change and Evolution of Business Models
00:28:22
Speaker
What's your prediction on the pace of change? There's obviously some uncertainty in markets. I think this actually has driven some activity from some enterprises to say, hey, like globally, we're in a challenging market. So let's fix our data. Let's get ahead of this. Let's use a bit of this crisis to to get ahead of the game a bit.
00:28:41
Speaker
Others, I think are a bit more frozen stiff waiting to see what happens. What do you think is going kind of spin out over the next 12, 18 months in in the market that we're in. I think there's a lot of change, right? i mean, I think we have to eat our own dog food as we're talking to companies about the amount of transformation that they're going to see, right?
00:28:59
Speaker
I think you have to start with the technology space and basically say these traditional models that we've essentially operated on, like if I start with the software space, right? where you can continually sell people software and whether or not they get value out of it, there's going to be another group of people, largely people driven and services focused to try and help them get value out of that.
00:29:19
Speaker
And that's going to be the ecosystem, right? I think that's a flawed idea in both in terms of the rate of change and the expectation that organizations have. For us, we've, I think, been really focused on this idea of how we actually deliver client outcomes. And I think that's more critical now than ever. As we shift away from this traditional services, software sales approach, right, to where, like you were saying, the services as a software and the SaaS worlds blending together, right?
00:29:50
Speaker
You really have to think about people, products in the context of a value-driven model as how you're going to move the needle there. For us, this is definitely not just about software, if you will, in an AI context or tools.
00:30:04
Speaker
This is essentially about embedding intelligence into the core of how work gets done. We made significant investments and in almost three areas the business that we typically focus on, right? First, our platform, Bodhi.
00:30:16
Speaker
which is essentially an agentic platform we talked about before. Slingshot built on top of both the focused on the software development lifecycle. And then CoreAI, which is essentially our AI platform leveraging identity and data to really transform how marketing gets done.
00:30:32
Speaker
Each of these three are designed to radically accelerate enterprise AI software development lifecycles and marketing transformation, right? Because this idea at the very heart of it is this notion that While there's a lot of conversation about agents and agentic AI, right?
00:30:48
Speaker
Our belief is these agents have to operate autonomously within the software development lifecycle and marketing workflows. They're not tools, but they're essentially a digital workforce that works alongside your people to continually learn, evolve, evolve,
00:31:02
Speaker
ultimately enabling them to enable your clients to adopt this AI-driven way of transforming themselves, right? So constantly faster, smarter, self-optimizing.
00:31:14
Speaker
And so this people plus products model, which I kind of talked about from an Ironman perspective, is essentially where creativity and intelligence and technology come together to where the two are not quite distinguishable, right?
Redesigning Business Models with AI Integration
00:31:28
Speaker
In the same way that I'm sure for prior generations, it would be entirely impractical to basically say, where did your IQ as measured ended?
00:31:39
Speaker
And where did the tools that enhance your ability to perform significantly cognitive tasks begin, right? Right. Those are now just a kind of continuum, if you will.
00:31:51
Speaker
In other words, redesign your operating model before ai redesigns you. or redesign your operating model on the basis of the fact that AI is going to redesign you and the operating model.
00:32:02
Speaker
Yes, indeed. Well, Nigel, this has been a fantastic conversation. I think we spoke about a year ago, so it's great to see the different nuance that changes. It also reminds me, the speed of change in our industry is phenomenal.
00:32:15
Speaker
Just even over the last 12 months, I think every three months, we seem to have a big step change in development and the capabilities of these tools and systems. So really enjoyed it. I look forward to sharing this with our audience.
Conclusion and Engagement Details
00:32:28
Speaker
And it's great to chat with you again.
00:32:30
Speaker
Thank you, Phil. It's great talking you.
00:32:36
Speaker
Thanks for tuning in to From the Horse's Mouth, intrepid conversations with Phil First. Remember to follow Phil on LinkedIn and subscribe and like on YouTube, Apple Podcasts, Spotify, or your favorite platform for no-nonsense takes on the intricate dance between technology, business, and ideological systems.
00:32:56
Speaker
Got something to add to the discussion? Let's have it. Drop us a line at fromthehorsesmouth at hfsresearch.com or connect with Phil on LinkedIn.