By Dan Toma

Artificial intelligence has fundamentally changed the economics of product development. According to Cursor’s latest Developer Habits Report, developers are coding significantly faster than they were a year ago, while Nvidia recently reported that AI has enabled its engineering teams to produce roughly three times more code than before. Whether the exact productivity gain is twofold or threefold is almost beside the point. Building software has become dramatically cheaper and faster than it was only a few years ago.

Naturally, this raises an interesting question: what happens to the Innovation Accounting indicator, Cost of Failure, when the cost of building collapses?

Recently, I’ve heard arguments that Cost of Failure is becoming a less relevant Innovation Accounting KPI in the age of AI. If the cost of building continues to fall, then surely the cost of failing falls with it.

The opposite may be true.

AI hasn’t made Cost of Failure less relevant. It has simply changed where the cost comes from – and, as a result, what the metric tells us.

Cost of Failure was never just about building

The idea that Cost of Failure only measures the cost of building something is the root of the misconception.

Cost of Failure has never been solely about development costs. It is a compound indicator made up of three distinct costs that every organization incurs while bringing new products to market. The first is the Cost to Build the product or service. The second is the Cost to Learn whether customers actually value it by generating sufficient evidence. The third is the Cost to Decide what to do with that evidence – whether to stop, pivot, persevere or scale.

Cost of Failure = Cost to Build + Cost to Learn + Cost to Decide

AI hasn’t changed the equation. It has changed which part of the equation dominates.

Historically, the Cost to Build was by far the largest component of the equation. Software development was expensive, engineering teams were large and development cycles lasted months or even years. It was therefore natural to interpret a high Cost of Failure primarily as an engineering problem.

AI has changed what Cost of Failure measures

There is little debate that AI has dramatically reduced the Cost to Build. Code generation, automated testing, AI-assisted design and low-code platforms have compressed development timelines and reduced the effort required to create digital products. As organizations successfully adopt these capabilities, the Cost of Failure should logically decline.

The mistake is assuming that every component of the equation declines at the same rate.

Learning still requires customers. AI can summarize interviews, synthesize research and generate hypotheses, but it cannot tell you whether customers will actually buy your product. That still requires real-world evidence. While the Cost to Learn may be lower today because prototypes can be built and tested much faster, generating meaningful evidence and allowing experiments to run their course still takes time.

The same is true – perhaps even more so – for the Cost to Decide.

The Cost to Decide isn’t the cost of the meeting. It’s the cost of waiting for the meeting.

Once a team has generated sufficient evidence to justify a decision, every additional day before that decision is made continues to consume resources. Teams remain allocated, budgets remain committed and opportunities to redeploy people to higher-potential initiatives are delayed. In practice, the Cost to Decide is the fully loaded cost of keeping a team and its initiative alive while the organization decides what to do next.

A simple example illustrates the point. If a team costs €8,000 per day to run and the decision to stop or continue the initiative is delayed by 45 days while waiting for the next portfolio review, the organization incurs an additional €360,000 in Cost to Decide. That money isn’t spent building. It isn’t spent learning. It is simply the cost of waiting.

With or without AI, most organizations still review innovation portfolios quarterly, allocate funding annually and require multiple approval layers before teams receive permission to continue or stop an initiative. AI has compressed execution, but many organizations still govern innovation at the same pace they did before AI.

Ironically, AI may amplify this problem. As the Cost to Build falls, organizations can pursue far more ideas in parallel. Instead of reviewing ten initiatives, leadership may suddenly find itself reviewing fifty. The engineering bottleneck shrinks. The decision-making bottleneck grows. AI increases an organization’s capacity to build faster than its capacity to make decisions.

As the Cost to Build shrinks, the Cost to Learn and the Cost to Decide account for an increasingly larger share of the total Cost of Failure.

A high Cost of Failure no longer tells us primarily that engineering is expensive. Increasingly, it tells us that organizations are taking too long to learn – or taking too long to act on what they have already learned.

Twenty years ago, a high Cost of Failure often reflected the economics of software development. Today, it increasingly reflects the economics of organizational decision-making.

That is precisely why AI hasn’t made Cost of Failure less important. It has made it a far better diagnostic tool.

The new bottleneck is organizational

Most executives already know their organizations are slower than they would like. They know investment decisions take too long. They know projects remain alive long after the evidence suggests they should be stopped.

What they rarely know is what that bureaucracy actually costs.

Organizations that continue to govern innovation through quarterly portfolio reviews, annual funding cycles and rigid approval processes will simply build unsuccessful products faster than ever before. AI won’t eliminate waste – it will amplify the consequences of slow governance.

The difference has nothing to do with technology. It has everything to do with governance.

The greatest opportunity AI creates isn’t faster coding. It’s faster decision-making.

Otherwise, organizations simply replace one bottleneck with another. Instead of waiting for engineering teams to build products, they wait for leadership teams to make decisions about products that have already been built and validated.

The companies that benefit most from AI won’t necessarily be those with the best models or the fastest developers. They’ll be the ones that make better decisions, faster.

AI didn’t kill Cost of Failure. It made it a better diagnostic tool, putting a dollar value on slow and inefficient governance.

Dan Toma is CEO and Partner at OUTCOME and a leading voice on how established companies build sustainable top-line growth. His work focuses on the systems that enable growth – from governance and funding to portfolio management and execution – helping organizations move beyond “innovation theatre” to measurable business results. He is the award-winning co-author of The Corporate Startup, Innovation Accounting, and Open Innovation Works, and has advised executive teams across the financial services, energy, pharmaceutical, healthcare, and engineering sectors.

Dan was named to the Thinkers50 Radar in 2020.

In this interview with Thinkers50 co-founder Des Dearlove, she explains why the structure of our networks – not simply the number of people we know – shapes innovation, resilience, collaboration, and trust. She also explores how leaders can intentionally design stronger connections within organisations, what AI means for the future of human interaction, and why bridging divides may be one of the defining leadership challenges of our time.

Marissa is Professor of Leadership and Management at IMD and author of Social Chemistry: Decoding the Elements of Human Connection.

Watch the full interview or read the transcript below.

This interview took place at IMD’s signature Orchestrating Winning Performance program in Lausanne, 2026.

Transcript

Des Dearlove:

Hello, I’m Des Dearlove, co-founder of Thinkers50. My guest today is Marissa King, professor of leadership and management at IMD. A sociologist and network scientist by training, Marissa’s work explores how the patterns of human connection shape performance, resilience, collaboration, and change. Her book, Social Chemistry: Decoding the Elements of Human Connection challenges the traditional idea of networking, showing that our relationships are not random, but follow patterns that can be understood, measured, and changed. Marissa, welcome.

Marissa King:

It’s a pleasure to be here with you.

Des Dearlove:

The book Social Chemistry argues that relationships are not random. What do leaders most often misunderstand about our network relationships?

Marissa King:

Oftentimes when people are thinking about networks, their mind immediately shifts to thinking about networking. And when that happens, they start to really focus on the number of the people that they know. But instead of the number of people that someone knows, it’s actually the architecture or the form that those relationships take that are at the key to understanding human thriving, how organisations work, and how to make society more cohesive.

Des Dearlove:

And you identified three kind of broad network styles or types. Can you explain what the three are?

Marissa King:

Absolutely. If you look at more than 50 years of research in the social sciences, we know that most relationships can be described as either expanding, brokering, or convening. So expanding networks are just large networks. They help with influence and visibility. Brokering networks, on the other hand, tend to straddle different social worlds. And in straddling those different domains, they tend to promote innovation. And then finally, we can think about convening networks where your contacts are closely related to everyone else within your network. That tends to promote trust and resilience and bandwidth. So across these three types, there are various different benefits, but each of those different structures have an important place in making organisations, social relationships, and even your personal relationships work together well.

Des Dearlove:

So I appreciate they all have their value, but is one more important for leaders and leadership now at this moment in history?

Marissa King:

I think that’s a really great question. So each of these have different benefits. They also have different drawbacks. And the key piece is that we’re constantly creating and recreating these relationships and they need to change in response to what’s changing in the environment. So if you think about what’s happening in this moment now where we’re facing increasing fragmentation, increasing polarisation, and immense uncertainty, it turns out that brokering type networks, which are really focused on adaptability, combined with these convening networks which provide resilience are sort of the magic ingredients for really thriving right now.

Des Dearlove:

Okay. So what does that sort of look like if you are in a leadership position? We’ll get onto how you cultivate those relationships, but looking in from the outside or from the inside looking outside indeed, what does that look like?

Marissa King:

If I were a leader today or being a leader today, as I’m thinking about how do I manage these competing priorities, if you think about the challenge with most existing organisations to restructure an organisation, it’s immensely costly. It’s really difficult and it comes with a lot of pain. But instead, if I start to think from a network perspective and think about how can I redesign these types of interactions, we can do this. We could go out this afternoon and think about how to do this. So there are a couple different levers to pull from an organisational design or team design perspective. So we can think about the way that we structure teams. I spend a lot of time working in emergency departments where teams are on a day-to-day basis being designed and redesigned. So if you create stable, repeated interactions, you’re going to get a convening network.

If you have more diversity in terms of rotating people in and out of a team, you’re going to get a brokering network. The same goes with physical space. So how we’re designing offices and layouts or thinking about how we construct virtual work, all of those work together and are levers that we can pull to think about how do we get both of these properties. And what’s amazing is that if you think about social life in general, we don’t get to choose who our neighbours are or who our kids are friends with. So there are many aspects of our lives that we don’t get to design. But what’s powerful about the workplace is the workplace is one of the only places that we can consciously design social interaction. So these design levers that we can pull in the workplace are incredibly important.

Des Dearlove:

Okay. I have to say though, I do know some parents who try to choose who their kids’ friends are.

Marissa King:

Does it work out?

Des Dearlove:

Yeah, it doesn’t usually work out.

Marissa King:

No, it doesn’t usually work out.

Des Dearlove:

But they think they can. No, coming back to, I mean, I’m always fascinated by we’ve all seen the organisational charts, which is the kind of the formal network for an organisation. But I think we all sense that really organisations run on informal networks. How does that play out and how is that changing the nature of work, particularly now that we’re not necessarily under the same roof? As you talked about, you mentioned hybrid work, people are scattered all over the world. How do the formal and the informal play together?

Marissa King:

I love that question. If we think about this question, how we think about how these play together, really a network perspective or network lens is mapping this informal architecture. And some of that does directly map onto formal positions. So who I put in a role, how I construct a team, those formal assignments impact and influence informal relationships. But there’s a whole world that’s operating behind that, as many of us know, and starting to surface that, and conscious that, is really critical because that’s where much of this work gets done. And it’s also a tool that we can play with and redesign in a much more rapid and adaptive way to meet these changing demands of uncertainty and the rapid speed at which things are changing now. This informal architecture is much easier to design and redesign both through formal positions, but that’s costly. We can think about other ways that we can play with time and space, which has a huge imprint on what these informal interactions look like.

Des Dearlove:

As you say, restructuring, when you kind of re-engineer, re-architect an organisation is very time-consuming, very expensive, particularly if you can do it in other ways and informal ways. But what should be… I mean, I’m imagining a leader who wants to make change in an organisation. How can you engineer these sorts of networks? You mentioned leaders, but is that a mindset thing where you think, “Actually, I’m not going to think about the organisation almost as a physical thing. I’m going to think about it as a system of networks or one big network or an ecosystem,” or is there a different way of thinking?

Marissa King:

I love that, thinking about it as a mindset shift. And in many ways when I’m thinking about this, I’m trying to do two things simultaneously. One, I’m trying to allow someone to visualize what this network structure looks like. So first is giving the vocabulary – or the mindset in your words. So when I walk around a room or an organisation, I just see these maps in my head. But without that visual ability to understand these are the fundamental elements or fundamental building blocks of social systems, without that architecture, we can’t play with the building blocks. So the first piece is giving this mindset shift to understanding what the architecture looks like. And from there you can start to understand each of these different architectures or types has behaviours underlying it. So if I want to create a larger network or a more expansive influence network, onboarding is key. So how I’m bringing someone into the organisation, or you can think about individual behaviours.

So both of these are in play, but the first piece is being able to see the system and then thinking about the behaviours, either individual behaviours that you’re trying to promote or encourage, or system or team level dynamics that can also promote these same benefits.

Des Dearlove:

I think even now, a lot of leaders, when you talk about networks, probably see it as a sort of soft side of management, but what does the science tell us in terms of the actual impact of networks on performance? Which, at the end of the day, is what CEOs are concerned with.

Marissa King:

Yeah. I think it boils down to this idea. We oftentimes think about relationships as being soft skills, but where we started, relationships aren’t random. They can be mapped and measured. And once you take that shift to thinking about relationships being mapped and measured, those maps have extraordinary implications that we can tie to performance. So the form a network takes impacts everything from an individual perspective, pay, promotion, performance within side organisations, innovation, creativity, resilience, even health and wellbeing. So how the form that your network takes has an impact on premature mortality or early death that increases or reduces, if you have a good network, by about 50%. So in every dimension of both human and organisational thriving, the form and the quality of our relationships has an extraordinary and measurable impact.

Des Dearlove:

Okay. No, that’s important. The mortality one is I think at any measure that’s an important performance measure. Is there a danger that we overthink this and we take the, dare I say it, the fun out of the sort of social side of work that we’re… I mean, we’ve all met people at networking occasions where you start talking to someone and you can see them looking over your shoulder and thinking, “My next mission is to talk to that person.” I mean, is there something to be said still for the spontaneity or are we moving away from that and being more deliberate?

Marissa King:

I love that. So certainly the most important thing I believe is just in the joy of human connection, the spontaneity. And the spontaneity is actually what makes networks work. So that calculated approach of, “If I just meet this person, then my life’s going to…” One, it doesn’t work. But two, you’re right that it can diminish that sense of joy. And there’s really important research that shows that this type of interaction typically is associated with one specific type of interaction, which is an instrumental professional interaction. So I’m going into a professional relationship with this idea I’m going to get something out of it. But we know that we can overcome that by thinking about entering that interaction with a sense of giving instead of, “What am I going to get out of it?” And then you overcome this instrumental component. And I would say that’s my biggest worry in this profession is that people think I study networking, not networks.

And the network piece is so key because if we don’t think intentionally about our relationships, our networks, which are one of our most valuable assets, end up being accidents. And we all have relationships. Our decision to sit down and have a conversation today is going to have an impact on our relationships or our network. But the problem is that most of the time that’s done unconsciously. But by thinking more consciously about those connections, it benefits not just you as an individual, but also organisations and everyone else around you. And as you mentioned and where we started, there’s just joy in that connection and keeping that alive is so, so critical.

Des Dearlove:

We emphasize this or I mean, I’ve witnessed it many times at Thinkers50 events, particularly our big event in November, is that people come into the room and there’s a serendipitous bumping into people. And it’s always so heartening afterwards to hear that a professor from Harvard is suddenly collaborating with someone that they hadn’t met and they met them at our event and they wouldn’t have spoken to each other. That’s the great joy of physical events in a world that we feel that we still get many benefits from the virtual connections, but actually sometimes the fact of being put into a space and bumping into people can still be very valuable. You see that as well?

Marissa King:

Absolutely. I mean, one, there’s spontaneity and joy and connection. That’s where new ideas and innovation comes from, this recombination. But there is a component of that that I believe, and I think most of the research suggests, has to happen in coming together face-to-face. So there are human needs that we absolutely have to have that really can’t be met without the physical component. So making eye contact, touch, and just simply the presence that exists when you’re face-to-face. And that’s not really repeatable if we think about other domains and formats. So there’s something just profoundly human about connecting through our human senses in particular.

Des Dearlove:

And we are more attuned. I mean, I think when there’s even a little bit of separation in time, it’s much harder to read body language… it’s a different experience. Adam Grant, who’s one of the people whose work we’ve promoted over the years, he wrote a book, Give and Take. And one of the very satisfying conclusions of that was he talked about givers and takers and matchers. And in the big scheme of things, I think he came out with saying that actually givers, people who give generously, come out on top. Not always because takers can sometimes obviously take advantage. But it was pleasing to hear that those people that give the most also tend to do well and even best in career terms.

Marissa King:

Yeah. And it makes perfect sense if you think about just how relationships work, that idea that the norm of reciprocity is critical to human functioning. And so the idea of thinking about what can I give, it opens up a whole different world. And I think what’s particularly interesting about Adam’s work and work that’s built on it is it’s not also just one-to-one giving that matters, but if we think about giving one to many. That is where I think the immense power comes. And networks are amazing in the sense that they really work on a collectivity. So everything we all collectively put in, it just amplifies far beyond anything that our one-to-one exchange could ever create. And that’s where I think this power of the collectivity coming together through generosity is really, really key.

Des Dearlove:

Sort of a network effect.

Marissa King:

A network effect.

Des Dearlove:

I have to ask you, we’ve talked and I’m delighted that we’ve talked so much about the human side. I have to ask you about AI and how that’s going to change how we network and how deliberate we are in terms of selecting and navigating our social connections. Where do you see the impact? And is it a good impact or not-so-good impact?

Marissa King:

I think it’s transformative, there’s no doubt about it. And there are a couple ways that I’m seeing this play out now. And what is different about AI than anything that’s come before I would say technology-wise is that it’s relational so that it is actually an agent interacting with you. And so what is… the question becomes, what happens when you put this agent that has real human-like tendencies within an ecosystem? I think one of the things that I’m noticing that first happens that I would say is more on the worrisome side is that people sort of forget the basics of human interaction. You put AI in a conversation with a team and everyone just starts defaulting to talking toward the agent. And I think the antidote to that is we need to think very, very carefully about how we’re designing these systems, how we’re designing these network architectures and thinking about what is AI’s role in it. So it’s an active agent. So where in this structure does it fit?

And what we know from early research is that when this is being deployed in organisations, it’s actually creating more of this convening-like structure. So everyone is interacting with everyone else, which kind of goes contrary to what you would expect. So I think people often are worried about, “Oh, there’s going to be an increased sense of alienation,” but actually it seems like that when you introduce AI, it’s creating a greater sense of this convening network. Which you could be like, “Okay, that’s great. That could promote trust, that could promote more communication.” But the downside is if that’s happening on a single platform. So the AI has been trained with one mental model in mind, then everyone is actually… the downside to that network type is that it promotes group think. So everyone’s actually converging on a dominant model of thinking so that all these side conversations we’re having with AI before we go into the meeting means that the discussion we have in the room is lacking that diversity, lacking that innovation, and also maybe lacking in just the basics of human communication that we still fundamentally need.

Des Dearlove:

I can see how it could be detrimental to the spontaneity, in particular. I mean, I guess we’re training AI agents to… as you say, we’re uploading a mindset before we go in, which doesn’t allow us then to, or potentially could narrow the lens that we’re looking at. “This person is irrelevant to what I’m here for according to what I’ve been programmed for,” rather than that human thing when we just think, “That’s interesting.”

Marissa King:

Exactly.

Des Dearlove:

Yeah. Okay. So the Thinkers50 London Summit this year is all about leading in the fragmented world. How does networking impact on how leaders view their role and what they should be doing? I think we all are experiencing the fragmentation, but what does it mean in terms of social networks?

Marissa King:

So if you think about from a network perspective, what fragmentation looks like, it looks like that there are a lot of disjoined groups, oftentimes with polarised opinions and different viewpoints or different experiences that are disconnected. So in my world, this is right for what I would call brokering types of behaviours. So we need to create a sense of connection across these disjoined or fragmented groups. And I think many of the discussions now are focused on, all right, we need culture change or we need to have courageous conversations to address what’s underlying it. But that is very, very difficult. Changing culture arguably is one of the hardest things to do. And how do you facilitate these courageous conversations when you need them happening across multiple dimensions?

And the solution to that is really thinking about how can we create ties across these groups that are based on fundamental human experience? So we may have very different viewpoints or very different experiences, but at the end of the day, even through our own conversation thus far, family is likely deeply important. Most people love to laugh. How do we create these connections and start by seeing each other eye to eye, human to human, to start bridging across these groups? And so in this moment right now, this brokering type of network is really critical to starting to overcome fragmentation.

Des Dearlove:

Just imagine if you were organising an event and you had a bunch of really interesting people and the event organisers, in this case, are trying really hard to bring together business leaders and management thinkers in the same room and to really foster these courageous… I’m only asking this for a friend.

Marissa King:

Yeah.

Des Dearlove:

What would you advise that event organiser to do and how can we amplify some of those effects?

Marissa King:

I would start by not trying to encourage courageous conversation. I would start by trying to encourage deeply human conversation. So the conversation I would want to have is what is one of your moments of greatest joy? What matters to you most? And in those conversations, what we’re going to realise is people just by being humans share our most deepest values. And from that point of shared experience and shared values, then you start to just say, “Okay, we’re all human here. We all want to achieve the same thing.” And that’s starting to lay the foundation for this broader structural approach where we need to start connecting across points of difference.

Des Dearlove:

Okay. Fascinating subject.

Marissa King:

Yep.

Des Dearlove:

We’re running out of time. We’re going to have a bunch of business leaders in the room. What would be your advice, if you were speaking directly to them in terms of your research and what they can take away from our conversation, what would be the takeaway? What would you like them to remember from this conversation and how could they put that into action?

Marissa King:

That relationships aren’t random, they’re arguably the most valuable asset we have. Both as organisational leaders and as human leaders, we need to think about how we can promote relationship thriving and create leadership through connection.

Des Dearlove:

And what will distinguish the leaders that do best in the future in terms of some of these skills?

Marissa King:

In this day of age where there’s so much uncertainty and so much unpredictability, the only way that you’re going to get simultaneously adaptability and resilience is by thinking about human connection. So in this moment, human connection is more important than ever, and we deeply need to lean into it, and it’ll also bring more joy, I think, into the world as a whole.

Des Dearlove:

Marissa, thank you very much.

Marissa King:

It was a pleasure.

Drawing on insights from his Leaders Unplugged podcast, David argues that values – not formulas or playbooks – provide the compass leaders need when the future is impossible to predict. He discusses why business must become more comfortable with collaboration, how AI is reshaping management education, and why leaders should have the confidence to admit they don’t have all the answers. 

Watch the full interview or read the transcript below. 

This interview took place at IMD’s signature Orchestrating Winning Performance program in Lausanne, 2026.

Transcript

Des Dearlove:

Hello, I’m Des Dearlove. I’m co-founder of Thinkers50. My guest today is David Bach. David is the president of IMD and Nestle Professor of Strategy and Political Economy. A globally recognised innovator and expert on management education, he leads IMD at a time when executives face geopolitical turbulence, technological disruption, and profound questions about trust and purpose. Through his Leaders Unplugged podcast, David speaks candidly with CEOs, change makers, and thought leaders about what leadership really demands now.

David, welcome. It’s great to see you again.

David Bach:

Thank you for having me.

Des Dearlove:

Leaders Unplugged, the podcast, you really try to have deep conversations with leaders in the modern age. What have you learned from those conversations?

David Bach:

So you’re absolutely right. Leaders from across the spectrum in the corporate world, in government, in academia, and not necessarily people at the very top of organisations. We very much believe at IMD that leadership happens across organisations. I think what I’ve learned is yes, there are techniques, there are certain things that good leaders tend to do, but at the end of the day, there’s no substitute for values. I think if you have these deeper conversations, you’ll realise at the core when you have to make a decision, you fall back on your values. And that’s what struck me the most actually about this.

Des Dearlove:

And that sense of the North Star, as it were, pole star, that helps people navigate through especially the sort of turbulent times that we’re seeing at the moment.

David Bach:

I think so, because there are often no answers. There is no playbook that you can fall back on. The uncertainty, the volatility is built in. And so what is it that you rely on in the end? It’s the values of your organisations, the values of your profession, and at the end of the day, your personal values.

Des Dearlove:

And they’re very much conversations. I mean, they’re not lectures.

David Bach:

Correct.

Des Dearlove:

They’re not seminars. And then obviously that’s deliberate and presumably you get a more kind of human response from people.

David Bach:

Yeah. And it’s something that I think I’ve experienced since taking over IMD. You can have all the credentials, you can be well-prepared, you can have your strategy document, but leadership is interpersonal. It’s the human connection, how you relate to individuals, how you relate to groups, how you motivate people, how you mobilize them. And so I find these conversations to be much more revealing about who somebody really is as a leader, what makes them tick than something that would be a little bit more canned and prepared.

Des Dearlove:

So who stands out among your guests? Who are the memorable ones or what are the memorable moments?

David Bach:

I mean, there’s so many. So I’ll give you three examples. So I had Gideon Rachman on from the Financial Times. And that was great because Gideon is one of the people I look up to, I think about when I think about the podcast. He has this great podcast with the Financial Times, The Rachman Review. And having him on the other side was really great because I really got a sense of how he feels about current affairs and how concerned he is about the challenges that democracy is facing, for example. So that was really great.

But also I’ve had the new president of the International Olympic Committee, a former gold medallist swimmer, Kirstie Coventry, former national security advisor to President Biden. So it’s a very eclectic group of people, of course, CEOs as well. So I’m enjoying all of these conversations.

Des Dearlove:

So apart from the laser focus on values, are there other commonalities? Because obviously they’re quite disparate backgrounds and different roles.

David Bach:

Yeah, I think you can’t escape it, everybody one way or another is talking about uncertainty and change. They all feel, whether they’re in government, in academia, in business, in civil society, they’re all grappling with a lot of change in the world, mistrust in institutions, rapid technological change, geopolitical conflicts that seemed like we had left behind. And they’re all sort of figuring out what it means for them, what it means for their organisation, what it means for their profession.

Des Dearlove:

And geopolitics is sort of your area of expertise. So what advice have you got for leaders trying to navigate their way through very confusing and difficult times? I mean, there was a time too when business leaders in particular tried to sidestep and really not get too involved in the political side of things.

David Bach:

Yeah. So there are three pieces of advice that I give, but before I do that, let me actually pick up on the last point that you mentioned. I think business education, and I’m generalizing, has contributed to the problem that we face right now, in that for decades we’ve basically said to leaders, look, focus on your customer, focus on your shareholder, forget about the rest. And businesses exist in society. They’re collections of people. You cannot disconnect them from society.

So I think we need to sort of relearn this. And so there are three things that I say. First of all, leaders have to understand the old era is gone. It’s not coming back. This is not a temporary departure from the mean. This is what we have right now. Number two, everybody is dealing with the same set of challenges. So there’s no point going into a foetal position and being sad and upset about how hard it is. Everybody’s dealing with the same thing.

And the third, you can learn this. You can get good at navigating this environment. In fact, the folks who led organisations in the ’50s, ’60s, and ’70s, people who have been growing up in emerging markets, they’re all very familiar with volatility, with weak institutions. And so it’s really this group of Western leaders who’ve had the good fortune of developing their careers in relative stability who are struggling with this.

So we’re not going back. Everybody is dealing with this and you can learn how to manage it and get better at it.

Des Dearlove:

When I first met you, which was at least a decade ago, let’s leave it at that…

David Bach:

We look the same, both of us.

Des Dearlove:

Yeah. As we did there, I’m sure. Completely untouched by time. But your kind of area of expertise and research at that time was very much non-market strategies, which seemed it was a coming topic, but I mean it’s very much sort of landed. I always think for business leaders, the hard bit is knowing when to engage and when to say that one actually doesn’t concern us too much, because you don’t want to get involved in every single issue that comes up. So how do you navigate that? How do businesses decide when they need to engage because it is core to the business and the people that work for them and the communities they’re in and all those things? And when do you say, well, that one’s for somebody else to…?

David Bach:

Yeah, I think it’s really important to distinguish between business leaders weighing in on important questions about trade policy or fiscal policy or investments in infrastructure or education, or just picking whatever the topic du jour is that some reporter might be asking them about or they might feel compelled to post about on social media. So I don’t think we want CEOs who weigh in on every particular issue, but businesses play really important roles in society.

Take the competitiveness of Europe, for example, right now. Europe needs to grow faster. It needs reforms. It needs capital market union. And I think business has a really, really important voice. You have the European round table that is basically organising a set of CEOs who are working with policymakers and are helping them think through how to accelerate reforms.

And I think this is really important that often this is not a sort of solitary CEO doing something on their own. It’s business leaders working together, working with governments. So one of the things that I try to emphasize is that competition is great. We love competition. It incentivizes innovation and risk-taking and all of that. But as a leader, you also have to know when you have to shift into collaboration mode. When you pick up the phone, you call a competitor and you say, look, let’s put that aside for a moment. We have a shared interest here in moving an agenda forward. Making sure that we deliver more value for society, for stakeholders. And so that ability to shift in and out of competition and collaboration I think is going to be really important.

Des Dearlove:

We have at the Thinkers50 London Summit this year, we have Paul Polman as one of the speakers, former CEO.

David Bach:

Who knows this very well, of course.

Des Dearlove:

Exactly. And in the book that he wrote with Andrew Winston, Net Positive, they talk about the fact that most organisations… you can’t solve the world’s problems in isolation. You really do need to collaborate. So collaboration is kind of in business terms after decades of being told compete, compete, compete. It’s a change of gear I think for a lot of organisations. And it’s difficult because it doesn’t come as naturally to people, dare I say it, people who are trained in MBA programs.

David Bach:

100%. I mean, that’s why I do think we have part of the responsibility as an industry for this. And again, I would say that people who build businesses in a previous era, people who work in emerging markets, they get this.

I remember I was in Nigeria a few years ago and I met a young entrepreneur at an event and he was describing the business that he was building. And I said to him, “So is that a traditional venture or is that more of a social entrepreneurship project?” And he looked at me and he said, “David, in Africa, all entrepreneurship is social entrepreneurship.” So some of these are Western categories that we have created. Leaders elsewhere understand that their job isn’t just to think about the customer, they’re part of society.

And so we’re rediscovering some of that. And I think Paul deserves a lot of credit for doing that at Unilever, but also of course he chaired the World Business Council for Sustainable Development, a group of 170 or 200 CEOs that recognise that when it comes to sustainability in the planet, there’s so much that we can and must do together.

Des Dearlove:

You’ve put your hand up and said that business schools and business education has to take some responsibility for some of the things that perhaps need to change. I mean, this feels like a time when business schools have a need to really demonstrate that they’re still relevant. Now we’re sitting here at IMD. IMD, I’ve known IMD for many years and the school has always had a reputation for being an innovator in business education. Your personal brand is kind of built around being an innovator in business education. So what are the kind of innovations that are needed and that you are putting in place at IMD?

David Bach:

Yeah, so I mean, we were very quick to embrace technology, particularly AI, using AI to make learning more personalized and more interactive. We’re building games and simulations in new ways. So these are pedagogical innovations.

But I think the biggest shift really is how do we show the impact of what we’re doing? How do we even show the return on investment that we are creating? And some of my colleagues are uncomfortable with this idea. Education shouldn’t really be about ROI. But particularly when you look at executive education, which is where so much of IMD’s work is, people are spending a week with us, senior leaders. It’s an enormous investment by their companies to send them here. We owe it to them to generate tangible impact from that time.

And so we’re working very hard on how do we measure impact? What are the business objectives that a company is pursuing when they’re sending their leaders to an IMD program? How can we show that there is a clear before and after as a result of that intervention? So I do think management education will need to be comfortable with the idea of being held accountable for the difference it actually makes.

Des Dearlove:

We are here in the week of one of your flagship program, Orchestrating Winning Performance. And I’ve sat in on a couple of sessions. I’m amazed by how international the participants are. I think there’s 60 different nationalities here this week?

David Bach:

Yeah.

Des Dearlove:

And clearly they’re still getting something from it, but you talk about measuring impact, what do the metrics look like? What’s that?

David Bach:

Well, I mean the metrics vary across participants. I mean, we’ll ask people on Friday afternoon and in the coming days what was most impactful about the program for themselves, for their organisation. But we’ll go back to them in four months time and we’ll ask them what’s still sticks? How is it transforming you? What challenges did you encounter? And we’ll ask them a year from now again, what the impact of the program has been. And so we use some of that information then to fine-tune. We get that information for every single session that people attended.

But increasingly with our corporate partners, we say, “All right, in order for this program to be successful, what is it that needs to happen in your organisation?” We essentially contract around that, design against it, go back to measuring it and try to be held accountable for it. And all of that against the backdrop of a faculty that is super entrepreneurial, that likes innovation. This week is like a festival for us. There’s only one rule at OWP, it’s got to be new. And so people design new sessions, they try things out, but it’s all about making a tangible difference for each learner and each organisation.

Des Dearlove:

What are the big innovations that you can point to in the last couple of years that people outside or people watching this would say, “Oh yeah, that does sound like progress…” rather than sort of tinkering.

David Bach:

Sure. For me… in management education you mean?

Des Dearlove:

Yeah.

David Bach:

I think for me, one of the really important areas, and we’re very much focused on this, is to perforate and perhaps over time eliminate the distinction between degree programs and executive education. Again, this is sort of a distinction in our head. I mean, at the end of the day, you have classrooms, physical or virtual, you have faculty, you have participants or students, you’re learning. So it’s just us who have designed…if it’s enough of it, we call it a degree. And if it isn’t, then well, it’s non-degree.

And so I think stackability is the easiest way in which you perceive this. How do you actually build a learning journey around your individual needs? How do you spread it out so you can accelerate when you want to slow down a little bit when it makes sense in your life?

Once you start talking about stackable certificates where the building blocks are non-degree programs, but they stack up into a degree, then you start thinking about, do they all have to come from the same school? You and I grew up in a world where we bought music on compact discs and we got 15 songs from the same artist, whether we wanted to or not. And maybe your playlist has five songs from one artist and three from another and two from a third.

And so I think perforating that boundary, enabling stackability, and then really thinking about assembling across the institution is a real innovation. We’re working in that direction. Others are too.

Des Dearlove:

Fascinating really. I mean, do you feel that the history of IMD, which is very different to some of the other business schools, which a lot of business schools sort of grew out of universities and have this very heavy academic weight on their shoulders; do you feel that you are freer here, that you’re more able to… I mean, because that’s sort of anathema to talk about degree and non-degree as though they could be interchangeable, almost modular.

David Bach:

Yeah, this is a very different institution. We were set up by business to do this. About 80% of what we do is executive education. The faculty we recruit are people who want to be here. The best way to think about this is if you think of a distribution of faculty, in every school in the tail, in one tail, there are a couple of people who are the innovators who like being with executives, who keep pushing themselves. Those are the people we try to recruit. Very often in their institutions they were the only person like this or they were the oddball out and they come here and they realise, “Man, everybody here is just like this.” And so we’ve created a platform where really impact-focused faculty can come together. They’re supported by an extraordinary community of staff to innovate, to push the boundary, to work with leaders.

But it’s a very unique place. It makes for a pretty volatile environment. Executive education is the most volatile part of management education. Not nearly as… I’m jealous sometimes when I look at my colleagues who have these steady undergraduate or master’s revenues, even though they’re a little bit concerned about those now, but it’s very steady. We are the most volatile part of management education, but in many ways also the most exciting and innovative part.

Des Dearlove:

Probably the closest to the coalface, to having that impact that you’re talking about, that global impact you’re talking about. Okay, so what does AI mean for business education, management education in particular? Is it good news or bad news?

David Bach:

I think it’s good news. I think overall, it is good news. So certainly it means what we teach has to change. So AI is changing work incredibly fast. This is the fastest diffusing technology. It took the telephone 75 years to reach 100 million people. It took ChatGPT two months. And at this point, you have almost a billion active users just on ChatGPT. And the models are getting faster at breathtaking speed. So this is transforming everything. And so because it’s transforming work, we need to prepare leaders for it. We’re working with board members and what that means for them and how they can guide AI investments. We’re working with senior executives where it’s not so much about how to use technology, but how do you create the environment for people to experiment and then to scale? And we’re working with organisations developing skills at scale.

So that’s the what. I’m really excited about the how. And if you think about it, the magic of a place like IMD is that in our fairly small physical settings, we can create interactive personalized learning, and that’s the most impactful learning. And when you scale up, you either lose the interactivity, you just get one-directional video, or you sort of lose the personalization and sometimes you lose both. What AI enables is to actually do interactive personalized learning at scale. So we’re sharing some videos with participants and you can use AI to actually then apply it to your setting, get feedback on it and so on. So we’re at the beginning of this, but we’re really excited about what it can do.

Des Dearlove:

So this personalization thing, business schools have been talking about, forgive me, but for a long time, but it seems like the technology might finally have caught up. It might actually be feasible. We’re big champions and promoters of the work of C.K. Prahalad, the management thinker. And of course he talked about co-creation and he talked about N equals one to the personalization to the individual. I mean, my question is to what extent is it still just talk and to what extent is it a realizable, touchable two years from now, five years from now?

David Bach:

No, right now. Right now already. So I’ll give you the example. We’re here at Orchestrating Winning Performance. About half of our sessions, we basically record the session that takes place. We generate a transcript, we strip out the personally identifiable information, and then we make it accessible via an AI tool to all of the participants. So if 15 minutes or an hour or two days after the session you’re like, “What was that framework again that this professor talked about? Or what was the example from the pharmaceutical industry that they used?” They can chat with the class.

Now here’s the cool thing. If the example that was used was about pharma but you’re working in telecoms, you could say, “How would that apply to me?” And it will tell you, give you some ideas and recommend some readings, some of them from IMD, some of them from others based on that. And if you want to do that in French or in Albanian or in Japanese, you can. So it’s a way of deepening, lengthening, personalizing the interaction with an in-person learning experience taking place here enabled by AI.

Des Dearlove:

Okay. Final question. In November, we are celebrating 25 years of Thinkers50. We’ve got our new Leaders50 list. So for the first time, what we’re trying to do with the London Summit and Awards Gala is bring together not just the world’s great management thinkers, but also the most inspiring business leaders. So there’s going to be 700 people in the room of which a large proportion will be practicing business leaders. What’s your kind of advice to those people? What should they be thinking about at this point in history? What are the big concerns and what can they do when they walk out of that room? Because we’re also all about impact. So our mantra now is thinkers plus doers equals impact.

David Bach:

Yeah, absolutely.

Des Dearlove:

And the doers haven’t always been in the room, but they’re very much going to be in the room this time. So what’s the advice to the doers?

David Bach:

I think leaders really have to role model behaviour and there’s a lot of pressure on them in a world of uncertainty and change. There’s a lot of pressure for them to say, look, this is how the world is going to be and that’s how we’re going to organise ourselves around it. And of course we don’t know what the world is going to look like. The UK is about to have its seventh prime minister in 10 years. Let’s hope this one lasts a little bit longer, but the volatility is built in at this point.

And so leaders who pretend they know all the answers are not sincere. And so we need leaders who say, look, I don’t have all the answers. We don’t have all the answers, but here’s what we’re going to do. Here’s what we can rely on. These are our values. These are our capabilities. These are the relationships that we have with our clients that are going to take us forward.

So how do you give sense and meaning and direction to folks in a volatile world? And I do think part of that is going to be to admit that there’s certain things that we just don’t know and it’s okay.

Des Dearlove:

David Bach, thank you very much.

David Bach:

Thank you.

By Jayshree Seth

Key Takeaways

1. Infinite AI-generated alternatives can erode commitment to directions that were sound when chosen, quietly replacing perseverance with risk of perpetual pivots and constant churn. 
2. The Ulysses myth offers a precise and practical frame: the mast is a commitment-protection tool – built before the Sirens sing, not reached for after.
3. Most organizations already have two-thirds of what they need – project charters and stage gates. A third new practice can serve to hold the other two together in the AI era: a “Siren Clause.”

This summer, Christopher Nolan brings Homer’s Odyssey to IMAX screens worldwide. Millions will watch Ulysses – bound to the mast, straining against the ropes, hearing the most beautiful and dangerous song ever written – and many of them will think it is a story about willpower.

But it is actually a story about preparation.

Ulysses didn’t tie himself to the mast because he lacked discipline. He tied himself because he understood something that most have not yet fully reckoned with: that the moment of maximum temptation is the worst possible moment to decide whether to change course. The time to make that decision – calmly, clearly, with full judgment intact – is before the singing starts.

A problem forming

The crisis hasn’t quite arrived yet, but it is certainly forming – and it behooves us to name it, and address it, before it becomes structural.

There is considerable energy being spent discussing two risks posed by AI: the acute cognitive fatigue researchers call ‘brain fry’ and the longer-term decline in reasoning capacity termed ‘cognitive debt.’ These concerns are real and worth taking seriously.

But there is a third risk that can be more consequential for innovation – that AI makes us think too much – specifically about roads not taken.

Before generative AI, commitment to a direction carried natural weight. Alternatives existed, but once a team chose a path, the alternatives receded. Exploring them required real resources – time, experiments, people. That friction was a feature, not a flaw. It gave good decisions the focus they needed to prove themselves.

But generative AI lowers that friction. Every alternative is simply a prompt away, with every pivot costless to imagine. For curious, rigorous minds – precisely the minds that drive breakthrough innovation – the imagination of a better path is almost always irresistible.

I can envision a phase gate review where the direction is sound, the data encouraging, the team making genuine progress – and the conversation quietly pivots to an AI-generated alternative that arrived in someone’s inbox that morning – it was free, and it seemed new. The decision hasn’t changed. The evidence hasn’t changed. It was a Siren’s song tempting a change in course.

I think of this as “commitment erosion” not the inability to choose, but the inability to stay chosen. 

As more teams move from AI experimentation into AI-embedded workflows, this dynamic may become structural. Project charters written with conviction will start bending, or never get written or gain alignment under the weight of what AI generated overnight. Stage gates designed for structured risk-analysis may be overwhelmed by informal, always-on AI conversations that make every moment feel like a gate. The discipline of staying chosen – of giving a good decision the time, the space, the runway it needs – will become harder with every improvement of AI tools. 

What Ulysses understood

The myth is more precise than most retellings allow.

Ulysses tied himself to the mast after already deciding to sail towards the Sirens and hear them. The mast in this case was not a decision-making tool – it was a tool for commitment-protection instead. He was not trying to avoid the song. Instead, he understood that in the moment of maximum seduction, his judgment would not fail him. The Siren song would convince him that a better path existed closer to them. The song was beautiful, intelligent, and specifically addressed to him – promising exactly what he most wanted to hear.

That, in many ways, is the AI infinite optionality problem precisely. The alternatives AI generates are tailored, plausible, and specifically addressed to the logic of your decisions. They are not obviously wrong. In fact, quite the opposite, they are often seductively adjacent. And unlike the Sirens, they do not stop when the ship has passed. They are always available through the course of a project.

A team that commits to a strong direction and then spends months asking AI whether they committed to the right one does not lack rigor. They lack a mast. And we need to build the mast before the voyage begins – not reach for it after the singing has already started.

There is also a mirror image worth mentioning that comes from the same source. For every team that loses direction in the flood of AI alternatives, there is another that hesitates to even begin with AI at all because of the infinite optionality. Tying down to the mast does not only protect those already at sea. It gives those still on the dock a way to begin – by choosing intentionally, making the most of what I call “artificial diligence” has to offer – with a clause that defines what success looks like and a gate that creates permission to revisit. A commitment with a built-in reflection point is a first step with a map.

Tie down — and why two-thirds of it already exists

The good news is that most organizations already have the infrastructure for this. It just needs to be revisited with commitment erosion in mind. Three elements are critical to this and two of them are already sitting in the project management process, waiting to be strengthened.

Chart the direction once. Apply the clause throughout. Open the gate at every milestone.

Tether your charted direction.

Project charters already exist. But most are often written to satisfy a governance requirement – defining scope, budget, deliverables – not to serve as what behavioral economists call a Ulysses contract: a precommitment made in a moment of clear judgement that speaks on behalf of your best self to your most pressured future self. The fix is one addition: a sentence, written at the moment of commitment, that captures not just what the team will do, and not do, but why this direction was the right choice at this moment with given information. Could your team read it at month four, when three AI-generated alternatives are on the table, and say – “yes, this is still what we decided, and here is why”? If not, the charter needs that sentence. That is the tether – a direction statement – a genuine anchor for the direction charted.

Identify your pivot standard — the Siren Clause. 

This is the element that does not yet exist in most organizations, and it may be the most important one in the AI era. When the moment comes and someone asks a team what would need to be true for them to genuinely change course – not what would make change tempting, but what would make it necessary – most will pause longer than expected. The standard exists somewhere, but it has never been written down. Which means in practice it gets negotiated under pressure, with the alternative already on the table and already looking attractive.

The “Siren Clause” is written at the moment of commitment, before the project begins, in the same clear-judgment moment as the Direction Statement. It answers one question explicitly: what would need to be true for us to genuinely change course? It is essentially a ‘conviction clause’ – what evidence would be needed to emerge for that conviction to be overturned. 

It travels with the project through every phase – consulted actively each time new data arrives, a stakeholder shifts, or AI generates a compelling alternative. A standard set before the singing starts is the only standard that can survive the singing. Without it, AI alternatives always have the structural advantage of newness, novelty and potential and the original commitment never gets a fair hearing. 

Establish your reflection waypoint. 

Stage gate processes already exist to take an idea and launch it in the market. But they can evolve into primarily financial checkpoints – on budget, on milestone – while the direction question gets answered informally, continuously, and increasingly with AI doing much of the persuading in the background. The reflection waypoint restores the original function: a scheduled moment at every milestone, not a continuous invitation, at which the team formally asks “is the course still right and is the reason for staying on it still strong.” It converts continuous temptation into periodic structured review.

This applies wherever the organization already creates structured decision points – design reviews, sponsor updates, team onboarding when new voices join mid-project. Each is a moment where the mast can be either reinforced or quietly abandoned. In the AI era, none of them can afford to be silent about commitment.

A transitional moment — and a new leadership imperative

We are in a transitional phase of sorts with AI – moving from one system of working to another, and transitions are always the most disorienting part of any crossing. The more teams practice intentional commitment, the more naturally it will come. Stakeholders will get better at distinguishing genuine pivots from seductive alternatives. Decision-making will evolve to absorb the reality of infinite optionality rather than being overwhelmed by it. What feels like discipline now will become fluency. And the tools themselves will evolve too – from systems optimized to generate infinite alternatives to ones designed to support commitment, judgement and sustained direction. The mast will eventually be built into the ship. It must.

But in this moment – before that fluency exists, while the tools are accelerating faster than the norms – the most valuable leadership skill is knowing when to commit. This means – hearing the alternatives, considering them seriously, through reflection, against the Siren Clause and then turning back to the tether, with conviction, and trusting the course set in the clearest moment.

This is not meant to be anti-AI. Just like Ulysses was not anti-Sirens. He wanted to hear them. He was right to want that. The song was worth hearing.

The question is simply whether you built the mast before you set sail.

Tie yourself to the mast because you trusted your judgment most before they started singing – and that judgment deserves a chance to be proven right.

by Janka Krings-Klebe and Jörg Schreiner

Most large organizations have reorganized more times than their leaders can comfortably count. Decades of restructuring show a familiar pattern: decentralize to unlock speed and innovation, then recentralize to tighten alignment and efficiency. Loosen, tighten, loosen, tighten. When performance falters, the instinct is to pull control back to the center. When growth returns, autonomy is restored. The pendulum keeps swinging because, despite decades of organizational research, the underlying downsides of centralization and decentralization have never been properly addressed. At the core lies a simple problem. The benefits of local competence and agency work best at small scale. Yet as the number of interdependent contributors grows, so does the need for tighter integration.

How can organizations preserve the local competence that makes each unit effective while achieving the integration that enables the whole enterprise to deliver value? Lawrence and Lorsch named the problem in 1967. Henry Mintzberg (Thinkers50 Lifetime Achievement Award 2015) mapped its structural consequences. Since then, each generation of management thinkers has offered a fresh answer: flatter hierarchies, cross-functional teams, agile frameworks, autonomous units. Yet the tension persists. The reason is straightforward. Most solutions try to solve the problem by standardizing operations. Organizations need something else: standardization at the interface.

That shift changes the logic of coordination. Teams no longer need to work in the same way to work well together. They need to be compatible in how they connect: how commitments are negotiated, how outputs are specified, and how information, goods, and resources move across boundaries. That is the architectural shift from hierarchy to ecosystem.

Why Culture Alone Cannot Scale

As organizations grow beyond a handful of teams, coordination costs rise sharply. In a small team, coordination feels effortless because the group quickly develops their own cultural code to facilitate communication, sharing and handover. Edgar Schein (inducted into the Thinkers50 Hall of Fame in 2009) observed that culture is essentially the accumulated learning of a group, the shared solutions to recurring problems, internalized over time as norms and assumptions. In a team of five or ten people, coordination patterns are triggered through their well-known cultural codes and communication protocols, almost subconsciously. The team operates under the same constraints, experiences are shared, feedback is immediate, and learning is collective. When a problem arises, everyone can see it. When a solution works, everyone learns about it. Culture emerges from this tight feedback loop. It works brilliantly, because coordination efforts and outcomes are tightly connected, visible and shared.

The moment a second group is added, this logic begins to fracture. Constraints diverge. Experiences diverge. Each group develops its own well-functioning cultural logic, and those logics become mutually opaque. The very success of culture at the team level becomes an obstacle to coordination between teams. This is less a management failure than a structural consequence of how learning works.

From the pyramids to moon rockets, as soon as more than one group is needed to create value, organizations require a mechanism that helps them organize contributions across group boundaries. History’s answer was hierarchy.

The Cost of the Hierarchical Solution

Hierarchy solved a specific problem efficiently, but its costs were long treated as unavoidable. It emerged as an answer to a specific constraint: how to move coordination signals across many groups when information is expensive to transmit. A hierarchy routes information upward to a point with visibility across units, a decision is made, and instructions travel back down. Although it worked, its costs were largely treated as unavoidable: latency, distortion of purpose, and the concentration of decision-making capacity at nodes increasingly remote from the actual work.

Hierarchies work best when they can create commonality at scale, so that is what they inevitably do. They reduce the variety of solutions to the coordination problem by standardizing processes, metrics, control systems and incentives. Over time, this bureaucratic effort to align diverse contributions becomes increasingly disconnected from value creation. Lawrence and Lorsch described the consequence clearly: the more an organization reduces differentiation to ease integration, the more it degrades the local competence that makes each unit’s contribution worth having. And conversely, the more it allows differentiation to build local excellence, the harder integration becomes. This is the tension they identified. It is structural. It cannot be optimized away.

Every major attempt to escape this bind has largely stayed within this same underlying logic. For example, cross-functional teams add integrative structures at the seams yet leave the hierarchical governing structures outside intact. Agile scaling frameworks try to coordinate autonomous teams, but without changing the basic standardized operation architecture. In practice, they just reintroduce coordination hierarchy by other means. Approaches that consciously avoid hierarchy, such as Buurtzorg (founder Jos de Blok was the recipient of the 2019 Thinkers50 Ideas Into Practice Award) and W.L. Gore, limit the number of teams in a value stream and therefore reduce the coordination burden. This works as long as the number of contributions that need to be aligned and integrated to create value can be limited. Yet it does not fully solve the scaling problem.

The limitations become visible when value creation requires fluid recalibration of coordination efforts at large scale. In today’s highly volatile business environment, that is the challenge that many large organizations now face. The very ground appears to be shifting, and the managerial instruments for alignment, integration and control increasingly lose their effectiveness.

Standardize Interfaces, Not Operations

Previous approaches sought coherence through common processes, metrics, roles, and management systems. The breakthrough alternative is to standardize the interfaces used for coordination, not the operations. This is a much more flexible approach, and one that has proven its worth in the domain of engineering over and over again. Consider what happened in software architecture when the industry moved from monolithic systems to micro-services. In a monolithic product, internal consistency has to be enforced and upheld through centralized controls. They ensure smooth operation, but they need to know all operations in detail in order to effectively control them. Changing the operations means redesigning the whole system. Contrast that with an API-based system. What matters there is only that the contract at the boundary of independent functions is respected. The independent functions implement their own controls, streamlined for consistency with interface protocols. Using interfaces, each function can contribute to a large number of very different operations at any given time.

This logic can easily be transferred to organizations. Teams organize into services around their special competence, which can then be invoked by other teams through standardized protocols that govern coordination across the whole organization. Teams can differ radically in their internal logic, tooling, and culture as long as they honor the coordination interface and the commitments made. Amazon Web Services was one of the first companies to operate and govern their operations in this way. Despite its large scale, it is still at the leading edge of innovation, and probably powering the most diverse portfolio of operations of any single company in history.

At a deeper level, the analogy of organizational interfaces is to TCP/IP, the communication standard underlying the internet since the 1980s. The internet did not require every computer to be built or operated in the same way. Different machines, operating systems, and local networks could remain radically different. What TCP/IP standardized was the interface logic of exchange: how data was addressed, transmitted, routed, and received. That made interoperability possible across highly diverse systems.

The same principle applies organizationally. Teams do not need to operate in the same way. They need to be dependable at the boundary. What this requires is surprisingly lean. A coordination architecture needs to define how teams connect, how commitments are made, how outputs are specified, how information flows, and how conflicts are handled. As long as these interface standards are respected, teams can differ internally in culture, process, and capability. Compatibility at the boundary enables freedom in the interior.

This does not eliminate the need for differentiation and integration. It changes their relationship. Integration no longer depends to the same extent on operational similarity. It can be achieved through standardized interfaces among highly differentiated units. The decades-old Lawrence and Lorsch trade-off can be laid to rest.

The Minimum Viable Governance Contract

The most important implication is that interface standards do not need to be elaborate to be effective. Over-specification is its own failure mode because it recreates the rigidity of process standardization under a different name. An interface standard needs to guarantee three non-negotiables:

• I can rely on your commitments enough to build on them.
• I can see enough of what is happening to detect problems early.
• When something breaks, there is a legitimate path to resolution.

Everything beyond these risks over-specification. The guarantees translate into a surprisingly lean governance architecture in which four practices carry most of the load.

An onboarding agreement establishes shared principles before collaboration begins. It is a clear statement of what participation requires: what is expected, what is offered, and under what conditions participants can exit. This is where the logic of the interface standard is made explicit and accepted.

Lightweight contracting specifies outputs and commitments. Traditional contracting becomes cumbersome because it tries to anticipate and specify everything in advance in response to opacity and distrust. When an interface standard exists and is respected, contracting can become more relational and adaptive. It defines what will be delivered and what happens if delivery fails, without prescribing how the work must be done.

Transparent performance figures make contributions visible without creating surveillance. Transparency supports coordination and builds trust over time without central enforcement. Teams that consistently deliver on their commitments build reputational capital. Underperformers become visible too, without anyone needing to monitor them, because they feel consequences when others are reluctant to collaborate with them.

Conflict mediation is the safety valve. When commitments fail or boundaries are disputed, there must be a trusted and accessible path to resolution that does not depend on escalation to authority. Without a clear, trusted mechanism for resolving conflicts and failed commitments, teams either escalate the issue, which reintroduces hierarchy, or avoid it, which erodes the standard over time. Mediation prevents small failures from becoming large ones.

These practices move some of the most underinvested areas of management to the center of the coordination architecture. In hierarchical organizations, they are often secondary because hierarchy carries most of the coordination load. In an interface-based coordination model, they become primary. Without them, interface-based coordination remains an idea. With them, it becomes operational.

Coordination through shared standards among autonomous contributors is not entirely new. Professional fields such as medicine, law, and academic science have long worked this way. What is new is the ability to apply this logic inside large business organizations at scale and in real time.

Technology as the Nervous System

For much of managerial history, the infrastructure needed to sustain this kind of architecture was simply unavailable. Maintaining a living, legible, and enforceable interface standard across many autonomous teams in real time required coordination overhead that consumed the gains. Today’s digital technology changes this calculus. Shared data layers, real-time performance visibility, automated workflow, and digital process management can carry much of the coordination load that previously sat on managers and meetings.

The transformation of Spanish bank BBVA illustrates how a shared digital backbone can reduce the managerial overhead of coordination by synchronizing strategies, priorities, and performance data across global operations. Critically, process users across the organization can propose improvements to the shared process architecture, and those improvements can be rapidly incorporated and made available to all operations. The interface standards themselves become more adaptive.

That is crucial. The greatest risk in any governance structure is ossification: when standards that once enabled coordination to become the bureaucracy standing in the way of flexibility. Giving participants a legitimate pathway to improve the operational system from within, “voice before exit” in Hirschman’s terms, keeps the standard connected to operational reality.

A Different Kind of Organization

What emerges is a kind of organization that is capable of complex and flexible value creation at large scale. The problem Lawrence and Lorsch identified has endured because most proposed solutions operated within the same architectural assumption: that integration requires enough operational commonality to keep differentiation under control. Standardizing coordination interfaces, but not the subjects of operation, opens a different path. It allows organizations to hold diversity and coherence together by shifting the basis of integration from shared operations to shared protocols of exchange.

What becomes possible is an organization that can scale adaptability without sacrificing coherence. It can combine deep local specialization with fluid coordination, respond to volatility without constant recentralization, and extend value creation beyond the firm into ecosystems of autonomous contributors. In that context, leadership must be reimagined. Its central task is no longer to align work through control, but to design and enable the conditions that make distributed, large-scale value creation possible.

by Atchara Juicharern, Ph.D., MCC

Over the past few years, AI has moved from the edges of organizational life to the center of it. It is no longer simply a tool for efficiency. It is shaping how organizations analyze, decide, and move.

At first glance, this sounds like progress in its clearest form: more speed, more insight, more support. And in many ways, it is.

But the more I work with leaders and organizations, the more I see a deeper reality. Even with better tools, more dashboards, and increasingly sophisticated AI-generated outputs, many organizations still struggle to make clear decisions, move in alignment, and think well under pressure.

So the question is no longer only, How well are we using AI? A more consequential question may be: Are we thinking well enough to use AI wisely?

That is why I believe this: AI does not make coaching less important. It makes coaching a core organizational capability.

Because what organizations need now is not simply more information. They need better thinking. And better thinking does not emerge by accident.

When Information Scales, Thinking Becomes the Constraint

Organizations now operate in a world where information is abundant, immediate, and increasingly AI-generated.

AI can analyze vast datasets, generate insights in seconds, and offer multiple pathways forward. Yet many organizations still struggle with slow execution, misaligned decisions, and what I would call superficial alignment, the appearance of agreement without real shared understanding.

That is the paradox. The constraint is no longer access to answers. It is the quality of thinking applied to those answers.

Daniel Kahneman’s work reminds us that under pressure, people tend to default to fast, automatic responses. AI may accelerate output, but it does not automatically deepen judgment.

Without the right conditions, speed can simply allow shallow thinking to happen faster.

The Real Gap Is Often Conversational

Despite all the progress in tools and technology, many organizations still live with familiar patterns:

• meetings rich in data, but poor in insight
• silence at the very moment challenge is needed
• decisions shaped more by hierarchy than by inquiry
• teams that appear aligned, but are not actually thinking together

This is why I believe the real gap in many organizations is not only technological. It is conversational.

Amy Edmondson’s research on psychological safety shows that performance improves when people feel safe enough to speak up, question assumptions, and admit uncertainty. But psychological safety is not created by good intentions alone.

It is created, moment by moment, through everyday conversation. Through how leaders ask.
Through how teams listen. Through what people feel safe enough to say.

That is where coaching becomes far more than a leadership style.

Coaching as Infrastructure™, Not Just Intervention

For many years, coaching has been positioned as one of three things:

• a leadership style
• a developmental tool
• a skill practiced by certain individuals

None of these are wrong. But in the age of AI, they are no longer sufficient.

If the quality of thinking inside an organization depends only on whether a few leaders happen to be good at coaching, that organization will not be able to scale trust, learning, or thoughtful decision-making.

This is why coaching must move from being seen as a skill to being designed as an infrastructure. It means coaching is no longer something extra. It is not something leaders do only when they have time. It is not reserved for developmental conversations once a quarter.

It becomes part of how the organization thinks.

The Coaching as Infrastructure™ Model

To make this practical, I use a simple three-layer model.

1. Thinking Space Infrastructure

From Reaction to Reflection

In fast-moving organizations, almost everything is designed for speed. But very little is designed for thinking.

That is why the first layer is about intentionally creating moments where reflection can happen.

This might include:

• reflection built into meetings
• strategic pauses before key decisions
• question prompts embedded into workflows

Without structured thinking space, AI can accelerate reactions rather than improve decisions. This layer helps people move from immediate response to more deliberate reflection.

2. Learning-in-the-Flow Infrastructure

From Activity to Learning

The second layer is about closing the gap between work and learning.

Too often, organizations treat learning as something separate from real work. Yet some of the most meaningful learning happens inside the work itself.

This might include:

• after-action reflection
• coaching check-ins during execution
• feedback conversations that invite thinking, not just correction

When learning is embedded into the flow of work, development becomes more natural, more relevant, and more sustainable.

3. Coaching Habit System

From Occasional Skill to Repeatable System

Many organizations train leaders in coaching, yet the behavior fades over time. Usually, this is not a motivation problem. It is a systems problem.

If coaching is not reinforced, practiced, and built into routines, it disappears under pressure.

That is why the third layer matters. This layer also resonates with the work of Michael Bungay Stanier, whose book The Coaching Habit helped many leaders see that coaching creates greater impact when it becomes an everyday practice rather than an occasional intervention.

This includes:

• reinforcement mechanisms
• peer coaching
• structured practice
• integration into performance routines
• AI-supported coaching simulations and feedback
• metrics that track conversation quality, not only outcomes

This layer helps coaching move beyond individual intention and become part of organizational habit.

From AI Adoption to Human-AI Intelligence

Many organizations are investing in AI adoption. Far fewer are investing in how people think with AI. And in my view, that is where the deeper opportunity lies.

The real question is not simply whether your people can use AI. It is whether they can think well with AI.

The greatest value in human–AI collaboration comes when people remain actively engaged, when they critically evaluate outputs, bring context and ethical judgment, and resist the temptation to outsource thinking entirely.

This is exactly where coaching infrastructure matters.

• Layer 1 creates space to question AI outputs
• Layer 2 embeds reflection into real decisions
• Layer 3 reinforces disciplined thinking at scale

I often summarize it this way: AI increases the speed of thinking. Coaching increases the depth and consistency of thinking.

Organizations need both.

Conclusion

AI does not diminish the importance of coaching. If anything, it elevates it.

Because in a world defined by information abundance, accelerated speed, and growing complexity, the organizations that thrive will not simply be the ones with the most intelligence.

They will be the ones that can think, learn, and adapt together. And that capability does not emerge on its own. It must be designed. That is why coaching is no longer just a skill. It is a core organizational capability.

And in the age of AI, it may be one of the most important capabilities an organization can build.

Transcript:

Des Dearlove: 

So the new book is the third you’ve written together, Detonate, Provoke, Hone. Did you plan it as a trilogy? 

Geoff Tuff: 

I would say anything but. Had you, if we could rewind the clock and look at Steve and me eight years ago, I think we were just hoping we might be able to make it through the first one. But the way things have played out, each time we finished a book, though we’ve taken a bit of a break afterwards, we have had reason to want to continue the story and to continue to engage some of our readers. And there’s a logical flow to it, I won’t tell you about all the books right now, but thankfully, we can now retrospectively call it a trilogy, but it was never the plan. I can definitely tell you that.

Des Dearlove: 

Well, it’s nice to hear you admit it. Steve, your earlier books, Detonate and Provoke, challenge leaders to break free from outdated playbooks and embrace bold action. How does Hone build on that, and to what extent does it diverge from that set of ideas? 

Steven Goldbach: 

Yeah, I think Detonate was all about a call to action, and Provoke was the start of a methodology towards dealing with exponential change. So, it was about anticipating, thinking about when trends become matters of when they’ll come to fruition rather than if. Hone is a further exploration of how you drive change in an exponential world, and it’s about focusing on behavior. It’s about behavior really being the subatomic element of everything that leadership has to drive. And it’s also about how you shape behavior through the changing of management systems, which are all the incentives that exist in organization to drive that behavior. 

Des Dearlove: 

I also think the subtitle is very powerful, How Purposeful Leaders Defy Drift, and what you’re saying is that purposeful leaders can defy drift. What does drift look like in organizations today and why is it such a pervasive challenge for leaders? 

Geoff Tuff: 

The way that Steve and I talked about it, when we were first conceiving of this idea, is that when you’re out on a boat, let’s say you’re sailing, usually, you have a set of coordinates that you’re sailing to or there’s a point in land that you can keep your eye on on the horizon, and you can keep on track. You can avoid drifting even though you’re being impacted by weather and wind and waves and current and tides and all those things. You have the ability through either steering or adjusting the sail or what have you to stay on track. In business, unfortunately, you don’t have set coordinates, you don’t have a set point on land. You have something in your head, in terms of an objective or a mission or a vision or what have you. But it’s really easy to be knocked off course bit by bit by competitive entries or regulatory shifts or new technologies arriving on the scene, where suddenly at some point you can pick up your head and say, after dealing with these day-to-day emergencies for some period of time, you can say, “Whoa, I’m way off course from where I intended to be at this point in time,” and that’s the point at which it gets really difficult to get back on track. 

Des Dearlove: 

Many leaders talk about purpose, but you frame it as a discipline to be honed. How are purposeful leaders different?

Steven Goldbach: 

So purpose in here does have intentional double meaning. So, we do think that business has a greater purpose. So, I think the notion that businesses that only care about shareholder returns is in itself its own fallacy, because when you only care about one stakeholder at the expense of others, you rarely get the shareholder returns that you want. So we do think that the role of purpose is important, but purpose also means, in this context, being purposeful about what I am moving towards. As Geoff said, what am I avoiding drift from? And that is by this constant honing that we describe. It’s constantly looking at that behavior that I want to drive and making sure that all the actors in the system that I’m responsible for are acting in a way that’s consistent with the objective of that purpose. So, it’s really being focused on that part, Des. 

Des Dearlove: 

From your perspective, how can regenerative business models, those that restore and renew rather than simply extract or even sustain it, I guess, reshape the way organizations think about growth and long-term value creation? And how does that link to the book? 

Geoff Tuff: 

Well, in some ways that really though it was not intended this way, that is the central thesis behind Hone, which is, and I think you probably know, we borrowed the idea from the title from a friend of Steve’s originally, Flannery, who we profile in the book as Chef. And Steve asked her at one point, “Why do you sharpen your knives before cooking every single meal?” And she said, “No, no, no, Steve, I’m not sharpening. I’m honing,” because when you sharpen a knife, you’re actually removing steel from a blade and you’re destroying it, you’re not being regenerative. With honing, you’re realigning them into an edge that actually is fit for purpose. And so, as we write about in Hone, the entire objective behind Hone is not to have to go through massive transformations episodically, but instead, take the action day in, day out, to make sure that you can stay on track and that you don’t have to go through some sort of great act of shift that may end up destroying some part of the company, whether it’s part of the culture or part of the purpose or even part of the organization itself because of the nature of change. In my mind, one aspect of being regenerative is to actually keep intact the good things that you have within the company to be able to continue on down your path. 

Des Dearlove:

There are some great stories in this book. I mean, not necessarily the usual suspects, these are stories from outside. The film director, Sam Pollard, for example; the rock band, Our Lady Peace. Where do you get these stories from? Where do you find them? 

Steven Goldbach: 

So, we’ve always wanted to bring in our network into our writing. We want to draw on lessons from our own personal lives. And oftentimes in Provoke and Detonate, that has been stories about Geoff and me. We profiled three provocateurs at the end and we thought, let’s look to the world of artisans for inspiration here, outside of the business arena. And so, Geoff knows Ana from his personal life, they are nearby neighbors in Rhode Island. Sam, we met through some work that we’re doing in the documentary filmmaking space. And Geoff as a longtime rock fanatic just happens to know the bass player of Our Lady Peace. And so we thought these are wonderful stories. There were other artisans that we were thinking about, and these are the four that made the cut. 

Geoff Tuff: 

But the thing I’d add to that, if I may, is that first of all, it’s no great secret that these types of stories are sometimes more entertaining than all the business stuff that Steve and I talk about. But as we got into exploring their stories and exploring how what they have done with their careers over time fit or didn’t fit with the analogy that we were trying to create in Hone, it’s amazing how many of the lessons from their lives actually transferred over into the business world into something that really is actually quite meaty. 

Des Dearlove: 

We used to, some people still do, talk about the VUCA world; volatile, uncertain, complex, and ambiguous, but I hear people now talking about a BANI world; brittle, anxious, non-linear, and incomprehensible. With geopolitical uncertainty, technological disruption, climate pressures, all of that going on, drift can almost feel inevitable. So, what practical steps can leaders take to stay on purpose without becoming overly rigid? 

Geoff Tuff: 

I think that’s all just a reaction to accelerating uncertainty. I don’t think the conditions of a VUCA world have changed all that much, it’s our reactions to that VUCA world that have. And so the very first thing that companies and people within companies need to do is just to have the humility that we’re no longer in a position where we can predict what’s going to happen in the future. We should stop pretending that we can use past data to try to understand the way the future is going to unfold. And instead, think like scenario planners think and actually accept that we don’t know what’s going to happen, but we can actually start to frame some stories about the future that will allow us to operate as we continue to move forward every single day and hone what we’re doing. We can still keep the big picture in mind, but we don’t have to pick which of those futures is the reality today. We need to have an understanding of the direction we’re going, but really, what we need to be focusing on is the here and now. 

Steven Goldbach: 

And if I might add, one thing that I think is a relevant story from… the three of us happened to be at the same dinner last night. And someone at some point was lamenting the fact that customers aren’t doing the thing that they really want them to do, they’re not. In this particular case, it was paying a premium for greener products. And I think the thing that you can do in a BANI world, is just get back, as Geoff says, focus on the future and what the future might bring. But also bring a mindset of… if I want that future, I need to create it and the thing I need to focus on is the behavior change that I want to be the driver of. And rather than lamenting that people aren’t doing the thing that you want them to do, start to ask yourself, well, how do I get them to behave and start to experiment and say, “What are the things that I can do that are in my control that will drive the behavior that I want to have in that uncertain world?” 

Des Dearlove: 

What are the key leadership takeaways from the book, and indeed, from the trilogy? 

Steven Goldbach: 

If there’s one thing, it’s focus on behavior. I think we often in leadership say we want to focus on changing people’s minds, and I think that really, it’s about changing the collective action of an organization and really, really focusing on that behavior. And then similarly, not judging people by perhaps what they think, but actually just what they do would be probably one, but let me let you add-

Geoff Tuff: 

Well, I think related to that, and this actually is a thread that carries through all the books, but as a leader, to be an effective leader, you have to be deeply curious about people. Not people in the organization, not dots on the org chart, but actually the people in the organization and outside the organization to understand what is it that motivates them that drives their behavior. And ultimately, you are trying to understand that in part so that you can affect that behavior. But the more curious you are about people, inevitably the more you actually have to engage with them. And the more human an operating environment, a business environment we end up creating. 

Steven Goldbach: 

And maybe that’s the draw, the connection between the artisans and the leadership that we want to draw. And I think artisans, by their nature, are designers. And our view of leadership is that you need to design the system that promotes the behavior. So remember the cheese last night, there was a table of 20 and they put two cheese plates in random spots and nobody was eating the cheese because people were confused about was the cheese for someone, was it for someone else? But the problem was that that was a poor design. Had they put four cheese plates because there were four sections of a table, people would’ve said, “Oh, that’s for sharing,” but instead it was in two random spots and people didn’t understand it. So, leaders have to design something that makes it clear. And so that was just an example of bad design in a very, very small and in an unimportant way.

Des Dearlove: 

Again, one of the things that I really like about the books is this emphasis on management systems, that management systems weren’t created, we create them. We can design them for a purpose, and different leaders with different priorities can influence behavior through the management systems. And I think that runs all the way through the three books. 

Geoff Tuff: 

Yeah. Well, and as we talk about in Hone, there are formal management systems, which we’ve known about for a long time and sometimes we use them well, sometimes we don’t. We hope some of the guidance in Hone will help them be used better. But it’s the informal management systems that we’ve been semi-obsessed about in all three books. The orthodoxies, the conventional wisdom, just the stuff in the ether that makes us act the way we do that we actually think may in the long run be more powerful in impacting the way people act and organizations unfold. 

Steven Goldbach: 

That’s why we are sick of hearing culture eats strategy for breakfast. And we know that that’s a business orthodoxy, it’s something that leaders love to say. And the problem with that is it puts culture as if this is something out of a leader’s control, right? Oh, we just can’t change the culture around here. And actually, the whole point is that management systems are something within the leader’s control. It is something that they design, and in management systems are all the tools that you use to change culture. It’s not about posters on the wall. So we would love to get rid of that phrase and introduce, it was like design the culture that you want to create the behaviors that you want. 

Des Dearlove: 

So last question. The trilogy is complete. What happens? What’s next for you two? 

Steven Goldbach: 

Maybe have a drink and enjoy life a little bit. 

Geoff Tuff: 

Yeah, sail off into the sunset. We will do, I would imagine what we always do, which is take a little break from thinking and writing and not really each other, we see each other almost every single day. But inevitably, there will be more ideas. Whether they manifest in a book form or in some other form, I think is still TBD. 

Des Dearlove: 

Well, we look forward to seeing the fruits of your continued collaboration. Steve. Geoff, thank you. 

Steven Goldbach: 

Thank you, guys.

Geoff Tuff: 

Thank you.

In conversation with Des Dearlove, he explores why successful transformation starts with clarity of purpose, how business design helps organisations adapt to disruption, and why human-centred leadership remains the ultimate differentiator in an increasingly AI-enabled world. 

Transcript:

Des Dearlove:

How do you define business design today and why is it becoming such a critical capability for organizations navigating disruption?

Francisco Salazar:

Well, I think business design is integral to dealing with disruption. This is about, at the end of the day, adapting your strategic choices to the capabilities you need and what type of organizational makeup you have to put together, particularly around the operating model. If you don’t do that right, you’re not going to be able to execute in your strategy.

Des Dearlove:

Now you’ve overseen some large-scale transformation programs across different industries. What patterns have you observed that separate successful transformations from ones that stall or even fail?

Francisco Salazar:

The first thing is clarity of objectives. Many times transformations become kind of a buzzword of just doing things differently instead of actually focusing on what is your objective function, what are you really trying to optimize? And by that, then we can actually apply the other lesson, which is really focusing on continuous business adoption, if you will, of the different things they are doing. Everybody will call it change management. We call it adoption, but it’s really about people changing their behaviors towards what we’re trying to optimize.

Des Dearlove:

I’m thinking of the AI transformations going on at the moment. Is it more of the same or is that fundamentally different?

Francisco Salazar:

I wouldn’t call it more of the same. You can never say more of the same with AI and generative AI, because we know where this started, we don’t know where it’s going to end. But it’s a disruption. It’s changing what we do. And certainly having clarity about what you’re using AI for and how you’re applying it in a way that actually sticks into the organization, is really important.

Des Dearlove:

Do you find that organizations have that clarity? It feels like… sprinting into the fog, was an expression that I heard. That suggests that perhaps we know we need to move fast, but we don’t really know where we’re going with it.

Francisco Salazar:

The question about AI is that we’ve seen a lot of people testing it and nibbling at it with the famous use cases, let me see what it can do for me. I think we’ve passed that. I think right now it’s really about understanding which pieces of your organization you want to enable with AI and what is it for, what is the final business result you want? And not just experiment, but really start to apply it at scale.

Des Dearlove:

Do you find organizations are able to do that or is there still some hesitation?

Francisco Salazar:

Not really yet. I think what we see is a lot of people are still very tentative about where they want to do it. Now, at the end of the day, this is a large capital decision you make, and with big capital decisions you have to actually go through and understand what you want to do, but it’s going to be a portfolio. We’re going to have to have different pieces around a portfolio of late mature things that you can actually apply, some more efficiency moves. At the same time there’s the opportunity of, I’m going to call them innovation moves, and moves in which you can speed certain things you can do before in a much better way.

Des Dearlove:

Is it possible to get an example of some of those?

Francisco Salazar:

For example, when you talk about efficiency, let’s talk about back office and let’s talk about finance. In that space there’s a series of opportunities of applying not only AI but agents themselves as a substitute labor for an agent. Now if you go to innovation, for example, in the pharma space, the ability to actually put AI towards research in a way that you didn’t before is going to speed the ability to get to solutions that you didn’t before. That for me, are the typical examples in which you see the extremes and efficiency move and an effectiveness move, if you will.

Des Dearlove:

How can regenerative business models, those that restore and renew rather than simply extract, reshape the way organizations think about growth and long-term value creation?

Francisco Salazar:

Regeneration for me is a broad word. I think it applies very well to the topics around sustainability and how we can create a regenerative space to continue to grow by actually not exhausting the resources we have. But I think more broadly, it’s also about how do we adapt to an ever-changing environment, ever-changing world in which clock speed today is so much faster than it was before. You have to build an organization that is able to continuously adapt to that. For me, regeneration is about that now, regeneration with a purpose. I think having an objective towards where you’re going is really important. If not, you’re just changing for the sake of changing, which is not really very effective.

Des Dearlove:

Regeneration applies not just to new business models, but also new forms of leadership. How do you see regenerative principles influencing the way leaders design organizations, mobilize talent, and balance performance with what you were just talking about – with purpose?

Francisco Salazar:

A layered question! There’s a lot there. I’m going to try to unpack it. First, I’m always of the belief that leaders have to be acting leaders. Leaders that actually are there, not sitting away putting some fancy vision and then expecting the organization to do it. For me, the principles of regeneration apply very much to leadership about how you are continuously engaging with the organization about where do you want the organization to go and why we’re going where we’re going. It goes back to the purpose thing. In terms of the organization itself you cannot build rigid organizations. You’re going to have to build organizations that allow for some wiggle room, if you will, of actually how to adapt to continuously changing environments.

Des Dearlove:

And the human side of this, obviously we’re all doubling down on the technology. How do you balance that? How do you keep the human bit? How do you manage the human?

Francisco Salazar:

The human is central to this. In our business at Deloitte, we have a lot of assets and a lot of different tools and methods, but it’s really about the human being at the center of what we do. Actually having a human that is enabled by AI in the right way is really going to be important. So the ability that us as humans have to really leverage the technology in the right way. AI is a new technology. It changes different things. It’s a big disruption, don’t get me wrong, but we’ve had other disruptions in the past and we have adapted to those disruptions, incorporating that clearly into what we do and how we do it.

Des Dearlove:

From your early career at World Bank to leadership roles at Monitor Group and now Deloitte, what leadership lessons have you seen, practiced, the ones that have stayed with you, what would you pull out?

Francisco Salazar:

I joke a little bit that a good leader for me is a student athlete. It’s like you have to study and you have to be there. I’m very much a believer of being a present leader. I think the leaders that are present, that are constantly there, that are reinforcing the message, that are there when things are bad, not only there when things are good, is really the difference in my whole career and what I’ve seen in the dozens of clients I’ve worked over my career. I think it’s really important now in this time to remind our leaders that they have to lean in. It’s not about letting things percolate and happen. It’s about the responsibility they have to provide the vision, to provide the guidance, and to provide the pause, if you will, to sometimes just breathe and kind of figure things out as they happen. Not trying to rush towards solutions that sometimes may not be the right ones.

Des Dearlove:

Applying that, sort of, in the mirror, let’s talk about the future of consulting, because obviously we are in this brave new world. How do you see the role of – particularly strategy consultants – evolving in an era of AI, digital transformation, and really a more complex mesh of stakeholder expectations?

Francisco Salazar:

You mentioned three things that I’m going to pick on in that phrase because they’re really interesting. First of all, one of my favorite authors, Aldous Huxley, you just mentioned there with Brave New World; the guy got it 100 years ago, and it’s a little crazy. The second thing, if I knew the answer to the question, I’d probably be sitting on a beach right now, on an island that would be mine. I don’t know the answer because we’re all trying to figure it out, but I think we do know certain things. What we do know is that we have an opportunity to reinvent ourselves as a practice, not only consulting, which is more broadly, and there’s a lot of things there, but certainly as a strategy consultant.

A strategy consultant, at the end of the day, it’s about someone that can bring the right level of dialogue with the C-suite, understand the portfolio implications of the choices you make, and is able to really architect enterprise transformations that actually drive what we need to do. That’s what we try to do at Monitor Deloitte. That’s what we push for. Being part of the Deloitte family allows us to do things that really can help speed up transformations and make them stick in a way that in other situations is harder. But I do think that we are first… and I say that to the practice every single day, we have to disrupt ourselves before somebody disrupts us.

Des Dearlove:

Do you think this is a game changer or a whole new game? Is it a disruptive technology or is it a paradigm change for business?

Francisco Salazar:

Wow. I am going to say, just because I’ve been through too many changes over my career, that I think it’s a disruptor, not a paradigm change. Because I do think that at the center of what we do, still is a human being. The human being is still going to have the opportunity to interact with others, to actually enable change in a nice way. Now the future, who knows? We may end up in a Terminator world where the machines dominate us. I hope it doesn’t go that way. I don’t believe in that. I’m a glass half full kind of guy.

I do think that we have a tremendous opportunity of using AI to really transform things that we did, either inefficiently or too similar to others in a differentiated way. Because the interesting thing about best practices and about AI now… I hear people go “oh, I can go online and do ChatGPT and I have a perfect strategy. For me, I don’t need a strategy… “ Well, you have a perfect, average, mediocre comparison of what other people are doing. As far as I know, that is not a differentiated strategy. That’s just a me-too strategy. Normally, me-too strategies fail.

Des Dearlove:

Now, I know Deloitte takes a lot of interest in the next generation of leadership as well. What advice would you have for emerging leaders? What capabilities do you believe will be most essential for this next generation of leaders if they’re going to thrive in the next 10 years?

Francisco Salazar:

The funny thing about it is it’s analog for me. The AI, the digitization, the speed is all there. Embrace it, learn it, understand how to use it. You don’t need to do it, but you understand how to use it. But there’s two things for me. One is embrace change, embrace, don’t run away from change. Change is going to chase you really, really damn quickly if you don’t embrace it. Second, the funny thing about our business, and I think executives in general, is be effective in the way you communicate. People are very ineffective in the way they communicate. It’s surprising to see that in scenarios and I think we under-invest in that, a little bit of the side of… what are the important things – clarity is critical to what you do. I tell that to our practitioners all the time.

Des Dearlove:

Surely by now we realize how important communication is; clarity, encouragement and all of those things. But what does that actually look like? 

Francisco Salazar:

The first thing is leaders sometimes do not communicate very clearly. It’s a very simple principle. Let’s go back to the classic pyramid principle of communication. First of all, what are you trying to portray and what are you asking your people to do? Sometimes it gets lost in translation. It’s like too many frameworks, too many ifs and buts, too many flowers. I just want to know what you really want me to do.

Des Dearlove:

Because I’ve encountered both, is the problem there the communication or the lack of clarity?

Francisco Salazar:

It’s both. Because the funny thing is I always try to keep our teams and our clients clear about what they’re trying to do. I’ll go back to something I mentioned a little earlier, which I’m going to call it in econometrics term, an objective function. What are you trying to optimize? What are you trying to move? What are your main goals or objectives that you want your organization to be focused on? And that applies to everything. Not only commercial organizations, it applies to governments, applies to NGOs, anything. What are we really trying…? Because if not the organization is going to go in circles. You’re going to create a lot of vapor, a lot of heat, but not a lot of motion, not a lot of energy. That is critical. And it’s surprising to me, by the way, in the biggest organizations, I’ve had the privilege to work in the biggest organizations on the planet, they still don’t do it very well. And there’s a lot of interpretation. Interpretation leads to inefficiency.

Des Dearlove:

Final question. As you say, you’ve seen a lot of organizations up close. What is the one message that you would want a young emerging leader to take away from this conversation? What is the one message you would like to pass down to the next generation?

Francisco Salazar:

There’s a world of opportunities. The future is about the opportunities that are there. Don’t get distracted with the barriers that exist because I think we can do a lot with what we have in front of us. We can solve a lot of the problems we haven’t been able to solve by actually applying some of the things we have in front of us right now.

Des Dearlove:

Francisco, thank you very much.

Francisco Salazar:

Well, thank you for having me, Des.