AI is Losing Ground: Futurist Brian Solis on Why AI Adoption is Failing

Are businesses falling behind in the AI revolution? While AI is transforming everything from workflows to decision-making, many companies are facing a surprising reality: they’re becoming less prepared for AI, not more. In this episode, we sit down with Brian Solis, a globally recognized futurist and thought leader, to explore how disruptive technology is reshaping business, society, and the future of work. As Head of Global Innovation at ServiceNow, Brian shares expert insights on business innovation, AI adoption, and what it truly takes to succeed in this rapidly evolving landscape. We also talk about the growing gap between AI-native companies and traditional enterprises, the rise of the agentic enterprise, and why true AI-driven reinvention requires far more than simple automation. Like and follow for weekly episodes. In this episode: 00:00 Intro 00:55 Are businesses falling behind in AI? 01:30 What “AI disruption” really means for business 03:30 The hidden dangers of AI: Bias, sycophancy & atrophy 05:20 Why most companies are underusing AI (capability overhang) 07:00 The AI index explained: Why readiness is declining 08:30 AI maturity scores are dropping and here’s why 10:50 Will AI-native startups disrupt enterprise giants? 13:00 How AI is reshaping jobs, roles, and workflows 15:30 The biggest myth: “AI transformation is easy” 16:30 What is the agentic enterprise? (future of AI work) 18:30 Automation vs innovation: Where AI creates real value 20:30 Why AI needs vision, not just it execution 22:30 IKEA’s $1B AI Pivot: A real business case study 25:00 AI business reinvention vs digital transformation 27:00 AI agents explained: How they actually work in business 30:00 Who manages AI? The Rise of HR and IT collaboration 33:30 The Chief Workflow Officer: A new c-suite role? 37:30 Innovation culture vs reality: Why most companies fail 45:00 Can you succeed in AI without an innovation culture? 53:00 Biggest AI myth debunked and final takeaways Connect with Brian: LinkedIn: https://www.linkedin.com/in/briansolis/ X: https://x.com/briansolis Instagram: https://www.instagram.com/briansolis/ Our links: Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Geoff Nielson?

  Hey everyone. I'm super excited to be sitting down with Brian Solis. Brian is a globally recognized futurist and thought leader in business innovation, currently serving as the head of global innovation at ServiceNow. What I love about Brian is that from innovation to digital transformation to AI business reinvention, he's been the leading authority on how disruptive technology is impacting society and work for a generation. What really sets him apart, though, is that he gets beyond the ivory tower thinking that some futurists fall into and has actually written and executed the playbooks to reinvent the way companies do business. I want to ask him how big the risk is that AI-native companies torpedo today's leading businesses. What does the enterprise of the future actually look like?

• 0:45Geoff Nielson?

  And what do we need to do and avoid to build it? Let's find out.

• 0:52Geoff Nielson?

  Brian, thanks so much for being here today. Super excited to have you. One of the things I wanted to talk about right off the bat is, you know, AI is obviously disrupting, you know, consumer patterns. It's disrupting businesses, disrupting the markets. And one of the things that I've seen in my experience with the clients that I'm advising and that we're advising is that businesses, by and large, seem to be losing ground in this adoption of AI. And I wanted to get your perspective in terms of what's going right, what's going wrong, and what's kind of the state of the nation when it comes to how businesses are attempting to adopt AI and better use it in their business practices.

• 1:31Speaker 01

  Well, Jeff, let's just kick it off with a big, huge question.

• 1:37Speaker 01

  Where, I don't want to save the big ones for the end. You got to get into it, right? Where do you want to start? I mean, look, the key word you used was disruption. You talked about consumer, then you talked about business. That is the right word to talk about this. So let's, let's have some fun. So disruption, the way I talk about disruption, I like to give it sort of a tangible meaning so that it frames the rest of the conversation. The way that I define disruption is doing new things that make the old things obsolete. Another way to think about disruption is doing things, whether consciously or subconsciously, in ways that change behavior.

• 2:20Speaker 01

  So whether you realize it or not, change patterns, change thinking.

• 2:26Speaker 01

  Because of that adoption. So the reason I give that additional sort of context is because on a personal level, AI is absolutely disrupting how people think or not think. And it is certainly stoking, or even in some cases sparking new biases, meaning like, you know, AI sycophancy, which is something that a lot of people are experiencing where, for those who aren't following that term, it's where AI is constantly giving you accolades and compliments. And it starts to create, subconsciously in many cases, sort of this

• 3:11Speaker 01

  false sense of competence and validation that can lead into all kinds of crazy cases that the news media has covered. And then also, just like what I call cognitive Darwinism, but is referred to as AI atrophy, where the more you, for example, high school students having to do their homework for them to save time, what they're doing is giving the thinking to AI and therefore sort of reducing their capacity for critical thinking, creativity, et cetera. And then you carry that all the way into business and you have what OpenAI

• 3:48Speaker 01

  calls capability overhang, which is described as the capacity for AI to do X, yet most people only use it for Y. And in their research, they found on their platform, for example, that they experience power users who use seven X more capabilities of OpenAI than the rest of the pack. So that's a pretty large delta. And if you look at Kevin Roos, who's a famous New York Times tech writer, he describes that in detail of what he sees

• 4:30Speaker 01

  firsthand in San Francisco with all of these AI native entrepreneurs, the agents that They surround themselves with, or we could look at the news and everybody who's using Claude Bot at Mac Minis and all the agents that they have doing their work for them. So anyway, it's a long way of saying that the real disruption is one that I wouldn't say is is is is named or realized yet. That businesses do not know what they do not know. And that disruption is is is to borrow OpenAI's term, the overhang. That at some point, competition and disruption is coming for them in ways that they're not seeing because they're focused on

• 5:11Speaker 01

  skills, upskilling, fluency literacy, but not necessarily against that vision of what do we want to become because of AI versus how should we use it?

• 5:22Geoff Nielson?

  So so all of that makes sense to me and it, you know, it frames it up really nicely in terms of the use cases right now, the art of the possible, maybe not even with future tech, but with what's available right now. Something caught my attention while I was, you know, doing some research on you, Brian, which is this AI index that that you and ServiceNow put out recently. And that in the past year, there's been a regression, it sounds like, if I'm reading it correctly, in the business AI index, which means that businesses feel less able or ready to capitalize on AI than they did a year ago. That is, you know, startling and maybe a little bit surprising. What what do you make of that? First of all, do I have that right?

• 6:06Geoff Nielson?

  And and what do you make about that? And then maybe maybe more importantly, what do we do about it?

• 6:11Speaker 01

  Well, first of all, thank you for doing your homework. And also, thanks for for plug in ServiceNow. Yes, I'm I'm very proud of our AI index research. And one of the reasons why is because it's the analyst in me where for those who don't know, I used to be a principal analyst at a firm called Ultimeter Group. And we studied emerging disruptive technology and made sense of it at a time where

• 6:40Speaker 01

  Most analyst firms were just studying the base, you know, like the stuff they have to cover. And for example, generative AI would have been something we were ahead of and and discussing at a high level. And so it's like right up our alley. And so that when I say the analyst in me, when generative AI hit, the natural first thing that came to my mind was to do what I had done with digital transformation to see if I could start to document stages of how organizations might adopt it and then how that adoption starts to transform the organization internally. And so what we had come up with was a maturity model of five notable stages of progress for generative AI between

• 7:25Speaker 01

  the most advanced and the those like everybody else, because it's it's changes hard. So anyway, that maturity model became the foundation for what later became the AI index, where we were able to survey against it around the world since we had these these models to understand where people were in their journey. So with that setup, what we had found was that in two thousand twenty five, the average score for AI maturity with a hundred being the most mature was thirty five out of a hundred.

• 8:04Speaker 01

  In two thousand twenty four, the average score was forty four out of a hundred. So it was a it was a drop of nine points. And what we really sought out to understand was, well, what what happened in that year? Where companies might regress. And in that one year alone, we saw rapid evolutions of AI models or, you know, frontier models. And then we also saw

• 8:32Speaker 01

  AI agents start to become a thing.

• 8:36Speaker 01

  And also the concept then of an agentic enterprise. So it was just so much, so fast that companies had to take a step back and say, wow, AI natives all over it because that's the foundation, that's their DNA. But for other organizations where things like governance becomes a huge factor, trust, security, risk, these things required organizations to better understand at a foundational level, how do we need to reorganize for this stuff so that our organization isn't caught off guard as we go further down this path?

• 9:19Speaker 01

  So it was, it was a regression, but for the right reasons.

• 9:25Geoff Nielson?

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• 9:52Geoff Nielson?

  It's notable to me as well that you said the score in 2025 was 35 out of 100, right? Like this wasn't a regression from like 95 to, you know, 86. This is like, we're deep in the red, right? Like we're talking about like an F on like a grade point scale, right? Right? I mean.

• 10:11Speaker 01

  One way to put it.

• 10:13Geoff Nielson?

  I mean, I'm struggling to, and I, look, I'm familiar with, you know, the five point scales and, you know, it's very typically the way they're constructed is it's pretty tough to get like a five out of five on them. But it, we're seeing, we're seeing a playing field where there's just not a lot of organizations, you know, except for the AI native ones that are, you know, really excelling here. And so maybe to just back up for a second before we, you know, talk about the agentic organization is.

• 10:41Geoff Nielson?

  You know, how big is the concern level? How big is the risk that AI native firms are going to swoop in and eat the lunch of, you know, a lot of these, you know, if I can call them more legacy or established firms that are not implementing these technologies in a material way?

• 10:59Speaker 01

  I mean, there's certainly, in the absence of understanding how things actually work and function and why, there's certainly a narrative out there that says, here come AI natives, they're coming for all of the legacy players. But in reality, there are, just like a maturity model, there are layers. And so if we, if, let's just take a step back to kind of

• 11:24Speaker 01

  set, set the conversation for everybody. If we look at a model and, and, you know, you had used the, the, the, the grade F for thirty five out of a hundred. The way, the way that I would want to think about it is

• 11:38Speaker 01

  if you're learning how to ride a bike, or if you use the, the traditional analogy of crawl, walk, run, you know, you're grading, you, you know that ultimately someone is, that running is, is the, the ultimate achievement. So that's the hundred. And so you're grading sort of someone's progress. And it becomes an issue if that progress becomes slower than the rest of your peers. And that's how we look at it. But the fact that there's progress and so, so quick in terms of, of adoption. So just as a reminder, generative AI hit in 2022. So with that context set, if we look at why that regression happened in terms of the score, it was because companies have to protect themselves, whether it's a matter

• 12:23Speaker 01

  of regulatory compliance, whether it's compliance in general, whether it's reporting, whether it's security, like these things matter at enterprise grade. If you're an AI native startup, you're, you're not thinking about those things, you know? If you're, if you're worried about auditing, if you're a publicly traded company, I mean, these are things that I think we, we just take for granted because we don't know what we don't know. So with all of that said, enterprise software gets an A in those things for a reason because it has to. You can't run your business on this stuff if, if those things weren't covered. Now, where, where the conversation gets interesting is now the nuance of what are we going to do with AI?

• 13:09Speaker 01

  It is one thing at an individual level. It is another thing at an agentic level because now what you're talking about is not just automating how work flows, we're actually empowering software to take on tasks that might normally be done by a human employee. And so this brings up much bigger conversations than just the capacity of software. Now we're looking at human resources and IT working together to better understand now how software collaborates with people. And it's not just a matter of, okay, this, this, the, this company is doing really cool things, let's put it in there.

• 13:51Speaker 01

  It is now a bigger conversation of breaking roles down into tasks, understanding where those tasks are actually holding people back from their own professional progress. And then not only dividing and conquering, but starting to understand what can we do with that freed up time and those freed up resources to achieve what we didn't know we could do or what was impossible yesterday? And then also, how do we do it in a secure way, in a, in a governed way that does not expose the company to unnecessary risk or compliance issues? So these are, these are really big conversations and I don't know that they're sexy headlines, but they're reality.

• 14:31Geoff Nielson?

  Well, and I completely agree with that. And certainly for a lot of our audience who, you know, is business leader and technology leaders, it's a really critical conversation to have and, and maybe not one that's being sufficiently understood or is, is taking a little bit longer to understand. And, you know, one, one of the things that's been on my mind and it's, it feels like we're starting to have like a come to Jesus moment around it is in 2023 and 2024, you know, what I had heard is at the CEO and board level. There was sort of this wishful thinking around AI that it would be easy and you could just sprinkle AI into your business and suddenly it would be transformed, which, you know, I have to laugh at because I have a background working with, you know, IT and

• 15:13Geoff Nielson?

  CIOs and I've never, I've never met an enterprise-grade tech project that was, you know, easy or, you know, took substantially less time and less cost and less than people expected. And it feels like we're finally starting to acknowledge at that enterprise level that, as you said, oh, we need all these enterprise-grade capabilities around risk, around governance, around integration. So before we talk about the how and what exactly that looks like, one of the challenges here is, you know, when you compare this to riding a bicycle or, you know, some of the technology implementations of the past, one of the things that strikes me as being

• 15:58Geoff Nielson?

  unique about AI is there isn't necessarily a defined target state because the technology is changing. And in some ways, the technology is, you know, it's a means to an end versus you're doing it for this specific reason. And you talk about the agentic enterprise. And so, you know, at least in 2026, what end state or what capabilities should organizations be building toward? And what's sort of the right way or the wrong way to pick your north star here?

• 16:32Speaker 01

  I love these questions because essentially what you're getting to, at least the theme that I'm picking up on throughout your questions is this idea of what Bill, our CEO, would say, Bill McDermott, for those who don't know, is what he would call AI business reinvention. That's essentially what we're talking about here.

• 16:55Speaker 01

  Or it's what we could be talking about here. And I say that because as someone who, for those who don't know, I wrote some of the original research around digital transformation. With all credit due to Capgemini, they were the ones who popularized the term in the early 2000s. My research was some of the first to look at not the IT implications of digital transformation, but the business opportunities for it. So for example, a working hypothesis would be like if we believe mobile and digital and social media will become prominent mainstream, human level transformative platforms, then

• 17:36Speaker 01

  how might a business reimagine parts of itself or a whole of it, you know, as a whole, in order to do business natively for a digital customer or a digital employee? And so it framed the conversation under the assumption that digital was going to transform the outside, therefore need to transform the inside. And I would work with the same assumption that AI is going to do the same thing, hence the maturity model that was originally created. So I say that because one of the things that I had studied in digital transformation was, I think I remember a stat from one report, that 86% of organizations around the world

• 18:19Speaker 01

  reported that they were actively investing in digital transformation, but only 25% of them could tell you why. And the reality is, is that like AI and like digital, back in digital transformation, I used to say, we weren't transforming with digital, we were digitizing the existing business. So modernizing, whatever terms you want to use, things that might even date back to analog processes and systems. So. With AI, you could say that some of the same patterns are already starting to exhibit or are exhibiting. So for example, the famous MIT report last year that found that 95% of companies

• 18:59Speaker 01

  weren't realizing ROI, it is because like the digitization, we are automating what was digitized. So it's hard to take ROI out of that if you're not reducing costs, like for example, whether that's headcount, whether that's software, whatever it is, you have to, you have to realize something back from it. So one of the, one of the interesting conversations that our team has is we're looking at

• 19:33Speaker 01

  how can AI save costs and resources by automating existing stuff? And then because it is, it is a frontier technology, how can we use it to do what wasn't possible yesterday to create new value? So it's this automation augmentation, this iteration, innovation conversation. And it's one, I believe that you could, you could make the argument that with digital transformation, it wasn't as profound, but with AI it is. And so now the conversation is a matter of vision. It's a long way of saying that this is vision and leadership, not just traditional IT,

• 20:16Speaker 01

  looking at existing infrastructure to take out costs and to increase efficiencies. It's part of it for sure, but I think that this is a bigger opportunity for technology leaders within the organization to say, hey, we're not just here working in the backend and we're not just here to take out costs. We are a growth engine opportunity now and we need to work closer to business leaders in order to define what we can become with AI, not just use it as a tool or a cost takeout mechanism.

• 20:48Geoff Nielson?

  That I completely buy that and the vision piece is really interesting to me, especially through the lens, Brian, that you just set up of digital transformation because, you know, looking at digital transformation and I imagine your experience was similar to mine. There were a lot of organizations that were, you know, deep in digital transformation, but shallow on the vision around digital transformation. Right. It's a lot easier to say you're doing it than to actually have that compelling business behind it and be, you know, reinventing the business in, you know, a really big and valuable way.

• 21:22Geoff Nielson?

  From your time in that space, what are the lessons learned that organizations should be thinking about if they're really serious about, you know, what you and Bill, you know, what Bill was calling AI business reinvention? Where does that vision come from and what do you have to get right? If you're going to move beyond, you know, kind of pot shots and small fixes to something, you know, actually truly transformational.

• 21:49Speaker 01

  I love this question and we, as we were building out the initial model for, for the maturity assessment. Vision and leadership was there from the beginning and it was not there because I had seen it in AI implementations at the time. It was there because I had, I had not seen it in the years of digital transformation. And so I knew that that would be a pillar at some point. So I'll give you, I'll give you an example. It's, it's a couple of years old, but it's still, it's, it's, I guess it's a great example to show you, even though it's a couple of years old, it is how rare vision is right now.

• 22:30Speaker 01

  So IKEA famously deployed an AI chatbot. It named Billy after its most popular bookcase. And like everybody, an AI chatbot is meant to.

• 22:44Speaker 01

  Take on level one customer service engagements and try to to solve every every instance as best as possible. And minimize elevation towards a human agent. And it was so successful, and forgive me if I get this statistic wrong, but it was it was something like this compelling like fifty seven percent effective in level one engagement. So it it it resolved those cases without in human human escalation.

• 23:19Speaker 01

  And

• 23:21Speaker 01

  most companies would then say, all right, wow, fifty seven percent. That's a whole lot of human agents. We're just not going to need anymore. And the ROI in that implementation would come from reducing those heads. And that is a popular narrative and fear with AI today. But this is where technology leadership comes in in partnering with the business by saying, I don't know if this was the conversation that was happening, but I'll I'll I'll act it as if it were. Well, what were the forty three percent that couldn't be resolved by Billy? That's that's a pretty staggering number of of cases it couldn't resolve. Let's study what those were. And what they had realized in that research was that

• 24:03Speaker 01

  those in many cases, not all of the cases, but a notable amount of cases were inquiries about interior design in commercial and and residential applications. And the long story short is that they spun up an interior design consultancy within IKEA, reskilled those agents to now become interior designers and applied a service fee for that and ended up in the first year, I think that it was generating one billion euro net new revenue. And so that is an example of leadership.

• 24:48Speaker 01

  I don't know that it was vision because it was more of a reactive thing, but it was it was a leadership opportunity to grow the business. On the vision side, you have someone like Jamie Dimon at JP Morgan.

• 25:01Speaker 01

  And he famously and his executives famously put out a vision like a lighthouse last year that says, we are going to become the AI mega bank by 2030 or whatever, whatever it was that they said. And they detailed how they see themselves getting there. Now that's a vision. Now, you know, someone will say, well, it comes down to execution. Of course it does. But we don't see a lot of vision as to where we're going to transform or what we're going to become differently as a result of AI. And so when you take the IKEA, the JP Morgan examples, what we're looking at now is this synergy, maybe the wrong word, sorry to use a buzz term,

• 25:41Speaker 01

  but this relationship between technology and now business leadership. Because together, we're going to be able to now rethink our approach to technology.

• 25:55Geoff Nielson?

  That's, that's, that's really interesting to me. And it's exactly where I want to focus, especially because it's an, it's an area that traditionally has been fraught with tension, with distrust, with, you know, issues with execution. And, and so, you know, you, you made sort of a, you know, a throwaway comment, Brian, earlier about, if organizations are going to reinvent themselves in this space, we need IT and HR much more fully involved than they've been in the past. What does that look like to you? Like just sort of broadly? What, what's the, what's the process here? And, and what are the roles for, you know, IT versus HR versus,

• 26:39Geoff Nielson?

  you know, the CEO or executive leadership versus any other, you know, group that needs to come to the table here?

• 26:47Speaker 01

  You're, you're, you're not giving me softballs, are you? This, we're, all right, now we're getting into the construct of business reinvention and actually what that looks like. So let's, let's bring it back to leadership first.

• 27:00Speaker 01

  The reason why leadership is such a vision and leadership are such important pillars in all of this is because we're essentially navigating uncharted territory. And, and I say that literally, I don't take it lightly that there is no playbook for this. Though, if you Google AI playbook, there are countless playbooks. I just mean that there isn't a blueprint for what the business of the future can become with AI, even if it's a legacy business or an incumbent. So that means that every business, depending on leadership vision and culture of how that organization makes decisions,

• 27:41Speaker 01

  takes risks, executes, et cetera, balances iteration, innovation, balances the known with unknown. Everybody's going to attack this differently. So, and there's nothing wrong with that, as long as we're making progress with this. But I'll, I'll give you an example. My, uh, my boss, his name is Dave Wright. He's the Chief Innovation Officer at ServiceNow. And together, we wrote some research around

• 28:09Speaker 01

  the concept of when Jensen Wang at CES in 2025. So this is, this is already old in the world of AI, but it was still provocative and still meaningful today. Jensen said something along the lines of IT will become the HR of AI agents. And a statement like that, from someone like that, is going to be scrutinized. And it was, it made headlines all around the world. But what I had, what we had noticed was that

• 28:41Speaker 01

  there was no real dissection of that statement, no real critical thinking around it. Like, well, what does he mean? What does that look like? Why would he say that?

• 28:54Speaker 01

  And what we had found in the, in the paper that we were, we were, and this is publicly available, by the way. So if you, if you want it, you can, you could just email Brian at Brian Solis and I'll, I'll send it to you.

• 29:06Speaker 01

  What we had found was that it requires for the first time, let's just take it from an IT perspective. And then we'll look at it at the broader collaboration around your question.

• 29:16Speaker 01

  An AI agent is, let's pretend it's not, let's, let's pretend it's, let's take its term AI agent, because that has human implications in its name. Intelligent software that can accomplish tasks on its own and theoretically learn from that execution in order to optimize itself every time it runs those tasks. If you put agents together, then they're handing off tasks, tasks to one another to then together drive towards an outcome. Now, they don't just magically appear, even though you can download them from your place or buy them from your place of choice.

• 29:57Speaker 01

  They have to be tuned to the specific way your organization works, the way where your data is, is archived and stored. All the things that a human being, for example, would need to understand before it's allowed to go off and start doing things. So there's training, with HR, there's onboarding. Even before that, there's identification that this is a resource we need. So in HR, we might hire for it. We might then skill and train for it. We might then deploy, manage and assess, et cetera. So in the, in, in the AI agent model, someone's got to do that.

• 30:41Speaker 01

  And so that's, that's what we, we believe Jensen meant by that. But that just, that doesn't necessarily just happen because IT realizes that there are tasks that can be automated. The bigger idea was that we explored is then how does IT work with HR to then assess what those tasks are within someone's role? And then build out the framework from there, the model from there, the management from there. What we learned after we published that, or what we had, what we, what we realized as

• 31:19Speaker 01

  we were continuing this research was that essentially, like in the HR world, how we manage people, how they're in an org chart, et cetera, how we have performance reviews and those are documented.

• 31:35Speaker 01

  AI agents are essentially software and software is an asset. And there is software asset management in the IT world. And so agents also then become managed as assets. So this Venn diagram really starts to take shape for these forward looking companies that are thinking about it beyond just the simple automation route. So then, last but not least, you you have now some real world examples of where this is starting to take shape. So Moderna quite famously moved IT under the CHRO. And now that's a one of one.

• 32:16Speaker 01

  And she's highly, she's a highly technical CHRO. Let's let's make that clear. But it is an example of what is possible. So as a futurist, that is a signal. I want to understand the signal. What could this look like over time? You have in Nike and Puma's case, technology rolling up to the COO now because they see AI as a business, technology as a business enabler. So my 2026 prediction was that in reality, regardless of how this stuff plays out individually at an organization, what will be consistent is this collaboration between HR and IT,

• 32:58Speaker 01

  especially as agents start to become more sophisticated in their ability to do more than one task.

• 33:06Geoff Nielson?

  It's it's an interesting prediction and it makes sense to me that they would be working together. And I I love the model of IT thinking of agents as assets and running that. And the two groups collaborating together in a big way. It seems like it could be fraught with risk without the appropriate sort of front end to that entire process, right? Like, someone needs to be answering the question about how do we do the things that we do here? Right? Because like you have to, you have to decide, does this require an agent or intelligent software? Or does this require a human? And, you know, I like, how do you trio? Like, now I'm thinking about business architecture.

• 33:51Geoff Nielson?

  Like, how do you triage that? And who who answers the how do we do the things that we do here?

• 33:57Speaker 01

  That's so what I love about your question is that.

• 34:04Speaker 01

  It is exactly the reason why there is no true playbook. Because that is one of many questions that need to be answered or even thought of, right? What we're seeing right now, one of the reasons why maturity isn't just accelerating through the roof is because one, we have to be cautious, but number two, we don't know what we don't know. And when, as human beings, when we don't know what we don't know, we lean on what we do know, which is years of proven expertise, experience against failures, successes, et cetera. And so this is why we see early adoption going against the things we do know. Your question begs, what do we not know? And what should we be thinking about? And so we call this an AI mindset. We published a paper on this too.

• 34:49Speaker 01

  It's asking the right sets of questions in the right context. So in one way, it's how do we save money? How do we scale? How do we make this more efficient, et cetera? And the other one is why do we do it this way in the first place? How might we reimagine it for a world with AI when this workflow was designed at a time where that didn't exist? And so when you balance both of those mindsets, you now start to unlock new opportunities. You now start to create the blueprint for whatever your playbook is going to be as you start to think about and solve for these things. So one of the things that Dave and I have been thinking about in depth is was inspired by Quantum Black, which is a McKinsey entity.

• 35:33Speaker 01

  They published a paper last year called The State of AI. And there was one line that really struck me because I'm in the workflow business, which is of all, they had come up with 25 attributes that studied where businesses were realizing any kind of returns on AI investments. And they said the number one attribute was when a business was able to reimagine a workflow and the end with AI. So essentially forcing all the tough questions, forcing all of the new things, but in a contained environment. And so what we realized, and this comes back to your question.

• 36:16Speaker 01

  Sorry, these answers are so long because your questions are so deep.

• 36:21Speaker 01

  Who's going to figure that out? Or who's going to think about that? So right now, it's depended on the company. If anyone is asking those questions or thinking about it. But what we had realized is if we believe then that the number one attribute for ROI is going to be end to end workflow reimagination, then someone's got to own that. And that role doesn't exist. So we playfully came up with the term, the chief workflow officer. That is someone's job now, who is going to audit and assess and let's say theorize before we architect, then what that architecture could look like. And then bring the right people in, whether it's IT, HR, et cetera, to then reimagine now what that workflow could look like.

• 37:06Speaker 01

  That is the extent, at least initially, to which we can now start to reimagine or reinvent a business.

• 37:14Geoff Nielson?

  I've never heard a chief workflow officer before, and I like it. And I'm chuckling to myself because you're in the workflow business, obviously. So of course, of course, there's a chief workflow officer. But aside from that, I do like the idea and I do see merit to it. But I wanted to, you know, I wanted to tease out something there and get your take on it. And again, you may, you may have an inclination based on the business that you're in. But there's, there's sort of this implication that the way that this is designed is top down or it's centrally managed. You have, you know, an office of business workflows or a vision coming from the CEO. To what degree is, should it also be bottom up or emergent from different parts of the

• 37:58Geoff Nielson?

  organization where people put up their hand and say, I think we can make this workflow better, whether they're in the workflow, whether they're managing the workflow? Or does this really, truly need to be top down to succeed?

• 38:11Speaker 01

  I'm going to answer that with the answer that no one likes, which is it depends. It really does. So I'm someone who's studied also innovation. So my whole career, I've worked with startups. I've worked with, I've helped establish some of the world's first actual, not R and D, but actual innovation centers. I wrote research on how those innovation centers were and weren't successful. And what was consistent across that? Was when bottom up was a factor in order for gaining success, not just in bottom up within the organization, but also from the outside in. So this is where you see things

• 38:55Speaker 01

  like what Walmart has successfully scaled, which is incubation, acquisition, separation of acquisition between the mothership. And you know, a lot of these lessons were learned the hard way. So for example, in our research already, there, there is. What every company starts to do as they mature is they create a center of excellence, if you will. That goes by different names, but what, what we're, what we're looking at then is bringing together all of the key stakeholders now to ensure that they're doing the right things at every step, governance being one of them, enablement, training, et cetera,

• 39:38Speaker 01

  being another one, a place where questions can be asked and sorted and answered is another. But there is a company out of Australia called Orica. They're a mining company and Rachel Sandel is, is the person sort of leading that AI initiative over there. They have something beyond a COA. They have what they call an AI advisory committee, which is staffed by, of course, some internal stakeholders, but also external stakeholders. And it is for the reason you ask. It is to make sure that it is a place where the right ideas or questions

• 40:19Speaker 01

  can come through and be vetted and also explored without the usual politics or bureaucracy of just everyday business. And in that case, they are what we call an AI pace setter. They are so much further ahead than everybody else for the very reasons that you're looking at, because now they're exploring things that they might not have considered because those ideas are coming from new places. It is actually. Just to add an aside, it is how if, if, if anyone wants to geek out, it's how Amazon Prime came to life. It did not come from the C-suite. It came from, uh, organically from the organization.

• 40:59Geoff Nielson?

  Interesting. And, you know, I, I tend to be in general, a pretty big advocate of that. And, you know, like you, I've got a background in innovation and I've, uh, not just internally, I've done internal corporate innovation. I've done, you know, advisory with other firms and innovation. And, and one of the things that I'm a little bit skeptical of, but I'm, I'm curious in your perspective, because it seems like some of these, uh, these models are flirting with it, is having a monolithic innovation organization, uh, within the broader organization. And that, that may or may not be how you're structured right now. But one of the challenges I've found with those models is that you're sufficiently divorced from the actual workflows, from the business itself, that it can create, um,

• 41:44Geoff Nielson?

  either relationship friction with the people that are running it, or just feeling a sense of distance from the actual workflows that you're trying to, uh, ultimately influence. Has that been your experience? Or how, you know, how do you best, how do you best conceptualize of innovation that works versus that ends up in, you know, kind of a failed state that doesn't have the desired impact?

• 42:10Speaker 01

  I mean, it's all of the things. Um, you know better than anybody that sometimes this stuff works and sometimes this stuff doesn't work. And it, innovation is one of those loaded terms, uh, that I think you'll appreciate this. Everybody wants it. Everybody talks about it. Certainly, you know, since the nineties and early 2000s, innovation, Silicon Valley, I mean, this, all of these things become, uh,

• 42:37Speaker 01

  I don't know, this, everybody goes, I used to call it the Disneyland tour. Everybody goes to Silicon Valley to visit Google or visit Meta. Or we even host executives in our innovation center in Santa Clara, where they just want to touch Silicon Valiness. You know, I don't know if it's in the water or if there's, it's in the air. Because innovation is, is, is that, is that, I don't want to call it a North Star, but it is like that thing that should be a North Star. But what it really comes down to is leadership, vision and culture. So, culture was not something I set out to study,

• 43:21Speaker 01

  but it became something I had to study in order to understand how to make a culture ready for innovation. And the way I describe innovation is not just the allure of Silicon Valley, just, just really specific. Innovation is doing something new that creates new value. Whereas iteration is doing what we did yesterday better, faster, cheaper. And so you need a balance of both of those things. A culture of innovation is one that allows for, and you use the right words, failure, taking risks, counterintuitively investing in failure and the acceleration of failure.

• 44:00Speaker 01

  Because that term is so loaded and that term is so, it's, it's become like stigmatized that you can't take a risk for the fear of failure. So you do the right thing by, or you do what you think is the right thing by iterating on a proven model. And if that fails, you still have something to fall back on. But my favorite, one of my favorite thinkers of all time, his name is Sir Ken Robinson, and he had talked about He was a champion for continuing creativity in schools and continuing creativity outside of school, like in our work, for example, where things like creativity aren't as celebrated.

• 44:44Speaker 01

  Risk isn't celebrated as much as, say, when we were kids, we would just do whatever. We would think whatever, we would explore whatever, because curiosity was an essential skill for us. And what he has said was, if you are not prepared to be wrong, you will never come up with anything original. And if you can't come up with anything original, you will not create new value, was essentially what he was saying. So culture then becomes essentially what people would understand in organizational psychology as essentially safety. Is it safe for me to have this, to ask this question? Is it safe for me to propose

• 45:27Speaker 01

  this idea? And do I have a support system around me that allows for me to further that conversation? So some examples would be, I remember when, one of the earliest ones that I found was the Tata Group out of India. They culturally said, you have to spend 10 hours of your 40-hour week, if we believed that 40 hours was all they worked, or we worked, 10 hours either learning a new skill or thinking about how to improve something. But then everything above that, managers, performance reviews, managerial reviews of themselves, et cetera, everything then had to be systematized to ensure that those ideas

• 46:12Speaker 01

  were explored, vetted, deployed, or cascaded, or for the next thing to come through. So I say all of that to say that culture and organizational or psychological safety are things that ensure that innovation becomes a thing. The last example I'll give you is Google, who is, I think we could both agree that is an innovative company.

• 46:40Speaker 01

  They studied why their high performers outperformed all the other high performers. And what they had found, they thought it was school, they thought it was leadership. And of course, those are probably factors, but what they had found was that those teams felt psychologically safer than the rest of the teams in order to do these things, to explore these things, to test and iterate and fail on these things. And so one of my favorite companies out there is called gaping void and they are dedicated to creating cultures of innovation and cultures of transformation. All vetted in what they call culture science, because it is a must in addition to all of these things that we're talking about.

• 47:23Geoff Nielson?

  So the conversation around innovation very quickly pivoted to innovation being much more of a cultural force than necessarily how you structurally design the organization. Which I really like and it makes a lot of sense to me. One of the challenges, and this is, I'll preface this by saying this is going to be a difficult question. One of the challenges a lot of organizations and a lot of organizational leaders face is they don't have that culture of innovation. It's not in their DNA and maybe, you know, their executives go to the Disney world of Silicon Valley. But then when they come back, they say, everybody needs to innovate. Oh, but by the way, that's subservient to the other hundred things you're doing for business as usual. And they functionally deprioritize it, right?

• 48:08Geoff Nielson?

  And so if you're, call it a technology leader or, you know, a non-executive business leader. In an organization like this, that suddenly has a mandate to bring in AI. Which we've already said has no playbook, right? There's no like, follow these three things and ta-da, you'll have AI and it'll, you know, reinvent your business.

• 48:32Geoff Nielson?

  Is it, is it, is it a fool's errand? Like, is, is a culture of innovation a necessary precondition to being successful with AI? And if you don't have it, should you give up or is there some other road you should take on that AI journey?

• 48:47Speaker 01

  Oh, you're right that it's not it's not an easy question. And I don't think it should be because if it were an easy question to answer, then everybody would be innovative. Right. So the way I would think about it is is it's this way when so even before AI, when I used to publish these studies on monitoring and answering the questions you're asking just in general. How can corporations be more innovative? Capgemini, I had partnered with Capgemini at the time. I think we wrote like three or four or five reports on this. They became the first reports that really started to answer this. And there was no one answer.

• 49:28Speaker 01

  What we had found was it was highly dependent on the culture of the organization. And in those cultures, though, there would be different models that would work. So think innovation center, think external innovation center, think incubation and ventures programs.

• 49:55Speaker 01

  There were, there were so many different models, but the successful ones always came down to leadership and then the culture that that leader set for. And so I want, I want to just give cultures also a loaded term. So what it isn't is a vision statement, a mission statement, value statements. That is not what a culture is. And I think a lot of organizations sort of mistake those as culture theater. The

• 50:25Speaker 01

  the culture is how someone might define in any part of the organization, not just what we do, but where we're going and why. And that everybody agrees that this is the right way to go. And that as a result, there has been sanctioned behaviors.

• 50:44Speaker 01

  And those behaviors become norms. And then those norms are what's measured, celebrated, etc. And so in a more innovative organization, asking questions, supporting those ideas, that's just a norm. And those norms have to be established. And that's, these are things we don't, we don't, we don't talk about. So for AI to do what, what we know is at least possible to do in terms of AI business reinvention.

• 51:13Speaker 01

  There has to be an articulation of this. And it doesn't have to be like, this is what it's going to do. This is what it's going to look like. It could even be like, I don't know. But what I do know is that these AI natives coming out of Silicon Valley are completely reinventing their business with AI to agent ratios already. We don't have that, nor are we close to that. So what I as a leader am committing to is giving you the resources and the safety nets. And, and whatever you need in order to start answering those questions of what do, what does good look like with AI? What does great look like with AI?

• 51:56Speaker 01

  And I don't know the answers, but we're going to create a space of which then we can explore what comes back with that and do something with it. And then the rest of the organization then has to now bring that to life. The norms, the values, the measures, et cetera. Like, that's big stuff. That's not easy. That's not overnight. This is why I'm sure if you talk to Jamie Dimon and you ask him, hey, so when you said you're going to be a 2030 AI mega bank, how are you doing that besides the AI investments? Like, what are you doing differently with your leadership? How are you, what are you doing differently with human resources? What are you doing differently about, uh, performance reviews? What are you doing differently about the word failure?

• 52:39Speaker 01

  How are you, how are you allowing people to explore and experiment without, without repercussions? How are you, how are you promoting or incentivizing around failure? And these are real questions. And so if you think about like the companies where culture was a brand, like Zappos, or for many years, Southwest Airlines, or one of my favorite examples, because I got to work on it. Well, I worked on Zappos too, which was a Virgin America while it existed. I mean, these are companies that had leadership that could answer all of those questions. I could even give you specific examples of like with Virgin America, how flight attendants were trained and how that came to life in, in, in the airplane environment. But most companies don't have these types of conversations.

• 53:23Speaker 01

  What is one narrative around AI that you're hearing a lot in the media these days? That you think is complete bullshit and people should completely Throw out the window. I, I, I think, I think. I would speak for the entire enterprise software industry in saying that one of those narratives is that AI natives are going to eat enterprise software. I think that is, I think that is not only an incorrect narrative, it is, it's doing it to service to executives who are really trying to navigate uncertainty and complexity.

• 54:04Speaker 01

  And so it would, it is, it is something that is, it is what it is. But at the end of the day, it, it only incentivizes us and me in my work personally to be the clarity, to be the voice, to be the lighthouse of thinking through these tough questions and also thinking through the questions that aren't being asked to have more meaningful conversations at scale. And if I can, if I can find a, a PR platform for that to counter those narratives, at least in, in the public spotlight, that would be even more helpful. But if it's a message that I want to send to everybody is that you have people actually thinking deeply about this and what it means to you so that you can safely, securely,

• 54:50Speaker 01

  with all the right reasons, no matter how slow or fast it is, transform in the right way.

• 54:56Geoff Nielson?

  I love that. And, you know, I, I'm inclined to agree with you as well. And another time we'll have to have a much more fulsome discussion on that. But for now, Ryan, I wanted to say a big thanks for coming on the program. I really appreciate your insights.

• 55:07Speaker 01

  Oh, Jeff, thank you. I mean, obviously we could keep going, but hopefully this isn't the last time. So thank you for this opportunity.

• 55:15Geoff Nielson?

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