Yumi joins BTS: A new era of empowered, inclusive change
Yumi joins BTS: A new era of empowered, inclusive change
In this episode of Fearless Thinkers, Rick Cheatham, hosts Katy Young, Senior Vice President and Partner at BTS, and Emanuele Scotti, Co-founder and CEO of Yumi, a recent addition to the BTS family. Emanuele unveils the fascinating story behind Yumi's evolution into a powerhouse of HR innovation, drawing inspiration from the collaborative spirit of Waze. Discover how Yumi, their groundbreaking tool, harnesses collective intelligence to empower individuals within organizations, making change not just manageable, but thrilling. Katie shares insights on inclusive change and the thrilling challenge of scaling it across diverse organizations.
Most of us want to lead in a way that matters; to lift others up and build something people want to be part of.But too often, we’re socialized (explicitly or not) to lead a certain way: play it safe, stick to what’s proven, and avoid the questions that really need asking.
This podcast is about the people and ideas changing that story. We call them fearless thinkers.
Our guests are boundary-pushers, system challengers, and curious minds who look at today’s challenges and ask, “What if there is a better way?”If that’s the energy you’re looking for, you’ve come to the right place.
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Masami: Welcome to Fearless Thinkers, the BTS podcast. My name is Masami Cookson and our host is Rick Cheatham, Head of Marketing at BTS. On today's show, Rick sits down with Katie Young and Emanuele Scotti. Katie Young is a Senior Vice President and Partner at BTS. Throughout her career, she has partnered with leading organizations across industries to enable change, from shifts in strategy and business models, to evolution in culture, operating models, and ways of working. She is a published author and active thought leader on the BTS blog. Emanuele is the Co-founder and CEO of Yumi, which recently joined the BTS family. Emanuele is a senior advisor who helps organizations design and implement new digital frameworks. He frequently speaks and writes on the topic of digital innovation. Hey Rick, how's it going?
Rick: It's going really well, actually. Well, with the exception of my budding addiction to Duolingo.
Masami: Oh my.
Rick: Yeah, I've got a trip to Brazil, this summer and I was like, I should probably pick up some Portuguese. And, the whole concept of gamification in learning language has proven to be very effective, at least on me.
Masami: That's amazing. I'm a lover of Duolingo myself.
Rick: Oh, yeah. Well, and it's actually a great tie in to today's show because, Katie, who, per your intro has always been a great partner to our clients in implementing significant changes in their business with our partnership with Yumi, we now have the capability to put in the palm of any individual's hand, the power to make that change personal. And, it really does enable us to shift at scale. It's an exciting conversation.
Masami: Amazing. Can't wait to hear more.
Rick: So Katy, welcome back! And Emanuele, welcome to the show.
Katy: Thank you.
Emanuele: Thank you so much.
Rick: So Emanuele, I would love to start with you today. Could you maybe tell our listeners that aren't familiar with Yumi, a little bit of the story of how you guys came to be?
Emanuele: Sure. The story is, I was a fan of Waze, since the very beginning. The navigation app built collaboratively by the community of users is like Wikipedia or other social applications. It's a fantastic example of collective intelligence. By sharing experiences and personal data, the community can build something that makes their lives easier, decrease traffic jams, and reduce the need for outside management, such as traffic cops. Even for the city mayor, Waze can be a wonderful dashboard to see. How citizens use streets and places and design improvement accordingly. We at Yumi had the insight to build something similar to Waze in our work in HR and change management. Leveraging data, collective intelligence, and self-regulation seemed like a good idea at the time. In a certain way, organizations are like cities, and everyone wants to live their work better, autonomously. Driving the journey when possible. And the CEO is like, the city mayor and the mayor would like to see the city from above and understand where there is traffic and action needs to be taken and where things flow smoothly. Yumi is a tool to navigate better through the organization, leveraging data and suggestions to work better with others and providing to every node of the ecosystem, maps and nudges to avoid problems and to evolve better behavior. From our point of view, this is a paradigm shift from a system based on command and control where the feedback and growth are delegated to external agency, mainly the manager to an approach on collective intelligence, where the system learns and grows on its own. After that, we made different attempts to turn these insights into reality. Some of them evolved positively, others failed. We use mechanism and tone of voice very far from traditional corporate software or traditional HR software so that the user feels very, very positive. And when we met BTS, the global leader in change and cultural transformation, we understood that this was the play for us.
Rick: Wow, so that was a lot that you've given us to think about. I guess the first thing would be, I understand what the word collective means and what the word intelligence means, but when you use collective intelligence, what precisely do you mean?
Emanuele: I mean that the colleagues that I work with, know me very well. better for sure than the HR department or my boss. And this form of intelligence is often, it's difficult to capture, to collect and to drive. And to have a technology that can, select, and leverage the intelligence that is inside, every single person of the team of the organization. And if we could leverage this intelligence, we can make a big empowerment of the single employee and of the organization.
Katy: Mm hmm. This is why we were so excited at BTS to have Yumi join our family and be a part of our portfolio in terms of how we serve clients because we're extremely aligned on the idea that change has to be something that's inclusive in an organization. It can't be something that just happens to people or is passively received or is forced upon people. It has to be something that the organization is truly engaged with and people feel a part of, and they feel like they're contributing to it. In addition, the challenge with that, of course, is scale. How do you include thousands, tens of thousands, even hundreds of thousands of people in change in an organization? And that's really the power that we see in Yumi partnered with the rest of our capabilities at BTS to really drive that kind of scale and impact in an organization.
Rick: That's awesome actually, to think about the ability for people to go on that journey as a whole versus being surprised or worrying about what's coming next. Earlier, Emanuele, when you were talking about how the map sort of changes, if I'm paraphrasing correctly, based on that collective intelligence we were just talking about, what does that look like? Can you give us an example of how that might actually work?
Emanuele: It works in a very simple way. The app asks to every single user to track some interesting data on their work experience. For example, how went that meeting, how was that day, who gave important support during the last week, how was the evaluation of the other attendee at the same meeting, or how was the day for the people you are working with. So, you produce some value for the community and the community provides back to you some insights. So you are tracking the information because you have an interest in receiving some value from the community. And so with no more than two, three minutes a day, you, for the time frame of four or six weeks, in a scenario that we call a campaign, the Yumi campaign, you can, in this give and take dynamic, give and receive some value from the system.
Katy: I think that really aligns with again, Rick, how we think about change in an organization, because I think where we see often change going wrong and I could talk all day about how typically change efforts really over index on, focus on, organizational structures, processes, things like that, and really under index on the people side of change, which is really what the whole BTS, you know, business is based on. But specifically, when we are thinking about the people side of change, what's so critical is that we figure out a way to make it two-way in terms of how we engage with people in the organization. So what Emanuele is really talking about is the power to help individuals throughout an organization really supported with the mindset and behavior shifts on the job that are going to be required to make the organization successful with change. So they're receiving these positive nudges, reinforcement feedback from their peers, tips on how to do things fundamentally differently, but it's done in a really helpful way so it doesn't feel like change is being forced on people. And at the same time, it's asking people for their experience and their opinion, which makes it really exciting for people to feel like they're actually actively participating in the change. So people are able to share, here's what's working for me. Here's what's not working for me. Here's what more support that I need. Here's what I observe in my team. Here's what I observe in the organization. So that experience for people makes them feel really involved and engaged. And then of course, as Emanuele was saying about the power, then, of the data that the system is going to give us, is that then we have so much insight into what's going on in the organization. So, typically the people side of change is managed through essentially communication, which, sort of, one-way pushes information within the organization. The beauty of the sort of daily element of Yumi is that we can actually get into the daily work experiences of individuals and teams and actually see what's happening and what people are experiencing at every level and every part of the organization.
Rick: So Katy, let me just go a little bit deeper. Okay. In fact, into what you just said, and that is that daily connection with change, and including it in the flow of work. I realized that this is one of those things that probably for a lot of people, might feel like too much. So I guess I'm wondering, in your experience, how is it that the daily reminders don't potentially make things harder for people?
Katy: I think that's a really interesting question. And I think, the biggest thing we hear from our clients is that people are experiencing change fatigue. I don't think there's an organization that doesn't, at this point, experience change fatigue. Our point of view at BTS, of course, is that that is the the new normal and, part of our job in working with Yumi or any of the rest of our tools, is to help build change readiness in organizations while we do the work. But we also have to be very careful about how we engage with people so that it doesn't feel like something additional, something extra, something burdensome, or as you said, kind of a constant reminder that I'm supposed to be changing all the time. It helps people see these kind of big macro shifts that are being discussed actually at a day-to-day level aren't giant asks in terms of “me fundamentally doing everything differently,” it's small things, small behavior shifts, small mindset shifts that can add up to a lot.
Emanuele: The idea is that we could try to put the people more at the center of the organizations and, make the work, more, meaningful in a certain way, connecting more with others, especially when we work from home or from remote and sharing an important part of the work experience. Rick: I guess what I'm hearing you say is, it's not reminders of the big changes. It's not daily reminders that we've got to, really rethink our go to market strategy or whatever the shift is that we're talking about. It's actually getting people to realize that it's small shifts potentially every day that make the difference. Am I tracking?
Emanuele: What we discovered, reading a lot of scientific research about what drives engagement and behavioral change, is very interesting, and is an opportunity also to have a more broad and comprehensive approach to the human being inside the organization. Because when we see, in a lot of organizations, also with our clients, the traditional leadership approach, that is using, external motivators to drive, engagement, like, what we call stick or carrots. And, we know that, if for us, the work is meaningful is important, is a big source of energy. Sticks and carrots are at the end of the day are very demotivating. The engagement, leveraging behavioral economics or neuroscience, is more based on intrinsic motivators. I do what I do because it is absolutely exciting, interesting, meaningful for me, has a purpose for me. And so in this new framework where I don't need sticks or carrots to do something that is meaningful for me, but, I need other stuff. We need more empowerment. We need a new kind of leadership to boost autonomy. And the third part that we were mentioning before is the connecting with others.
Rick: Thanks for that. It really helps to clarify some of the differences between the way that things have been in the way that, they actually should be if we're going to be successful making these types of shifts. One thing you just said, Katy, that I'm curious about your perspective on, and that is this kind of concept that I have some level of autonomy on “what this means for me” and “how that works for me.” How do you kind of reconcile that with, what we would consider in the past, like a playbook or, a best practice for ways of working?
Katy: Anyone in an organization chooses what they're going to do at any given time of the day. They're not being forced to do anything. And so at the end of the day, execution of anything in an organization happens from the small choices that people are making thousands of times throughout their day in terms of how they spend their time, how they interact with other people, small choices that they make, large choices that they make. Embracing the fact that people have autonomy and are able to make all these choices that they're making on a daily basis, but supporting them so people are getting this sense of positive reinforcement on the things that are really working, and some tips and some suggestions on things that they could be doing to be even more successful with their teams and within the organization. And of course they can do with that information what they will.
Rick: Cool. That actually provides some great clarity for me. Thank you. So, then I'll just kind of throw this one out – this one pops out to me, Emanuele, in something that you just said, in the traditional leadership approach, I would think it would be difficult for, leaders to kind of, for lack of a better way of saying, pass the responsibility for the pace and the process over to the team versus, what you said all the way back in the beginning, that kind of command and control. By the beginning of Q2, this is going to be how it all works.
Katy: Another part of way we view change, Rick, is that change, particularly today, but to some extent always, has been and needs to be iterative. Change can't be some sort of a linear path from A to B. We need to actually understand how things are evolving in our organization, how things are evolving in our external climate, and be adaptive because that's the nature of how we need to be able to evolve organizations today. So, what this is really helpful for is that we actually are able to get data about what's happening in the organization and iterate and adapt our approach, instead of just sort of communicating things out and hoping for the best and seeing what happens. We're actually able to not only support people on the job and making small shifts every day, but then we actually understand, okay, what's actually happening in the organization? What are people doing? What are they struggling with? What are we successful with? Where are the pockets in the organization of success and pockets in the organization where we're seeing things lagging, for example, and then we're able to use that data to actually adapt our approach and continue to evolve and iterate over time. And I think that's another extremely powerful aspect of this.
Emanuele: My experience with Yumi is that, when you find leaders that recognize themselves, not as cops of the organization, but more the designer, the architect of the city that the people are using by themselves – it is a data driven and iterative process. Where, for other assets off the organization, you can see what is happening, as the results of your decision through data, and, this is quite interesting also to see how, this kind of leaders of every level are going to feel that the issue is not just, inside them is some issue that, arrives from, a bad, style of leader or a bad behavior interacting with other, but it's just a managerial task to try to change my behavior as a leader of this team and to verify, which are the results of this change. And this is, my experience, a new wave of change also for leaders.
Rick: And, I love what you both just pulled out for me in that, which is this concept of the data driven approach that we don't even have to always ask, but we can actually see based on real measurable activity – what, if anything, do we need to do different as leaders to actually enable these shifts to happen? Katy: Absolutely.
Rick: Well, I guess what would probably be helpful for our listeners now is if you could, tell us a little story, give us an example of what this potentially looks or feels like in action.
Emanuele: One case is about new value spread out within the organization where the company changed the company values after decades. This customer needs to embed new values inside the organization. And the project started through the customization of the new values inside the platform. This is one part of the project. Very important. Very useful. The platform as the opportunity to describe, in a certain way, the challenge that the company is looking for, in terms of, new behavior, respected the new habits, new key factors to observe. And so we made this work 46 weeks in advance, and then we launched The Yumi campaign. We made three different Yumi campaigns in an elapsed time of weeks, 12 months. In an absent time of one year, and, during the campaign, starting from this very simple feature we mentioned before, how was your day? At the end day, platform sent a notification to each user through the smartphone. How was your day? Why? And who was with you? And from this, every user can track the day, can share with other colleagues, so the user, each leader and the leadership or the HR department receive a more comprehensive, also more complex, dashboard, with all different insights, on the different data captured by the platform, organized for the organizational structure, but also for some demographic, families, from the tenure, for example, for the job families or for the generation. So every single actor in the organizational ecosystem can receive data, nudging, suggestion to modify and to track how different behaviors, as an effect, on the other part of the organization.
Katy: You know, Rick, what I think is so cool about this is you can imagine the power of this data that the organization is getting. I think it's very easy to understand why the organization wants this, why the leaders of the organization want this data to be able to understand and adapt their approach and be more effective. But the data is only available if people are actually using it – the app.
Rick: Incredibly exciting. I appreciate so much, you both giving us your time today and, can't wait to hear more great stories of how we're able to enable change through a real community effort on the client side. So, thanks!
Emanuele: Thank you so much, Rick.
Related Content
You can't predict the future. You can be disciplined about how you face it.
That's where Future Storming comes in. Future Storming is a process for looking at the trends and signals already visible in the market, understanding how those forces connect, and thinking more clearly about where they may lead.
Recently, we've been applying that lens to talent strategy, running Future Storming sessions with talent leaders across industries to understand which forces are already reshaping how organizations find, develop, and retain the people they need. When you look across those conversations, one thing is hard to miss: AI runs through almost all of the most significant trends, and not as a future scenario. It's already reworking the talent systems most organizations have leaned on for years, often quietly, and often faster than leadership teams have had time to respond.
From these sessions, five high-likelihood, high-impact shifts have emerged as the ones every talent leader needs to be watching right now. What follows is what each of them may mean for your organization.
1. The frameworks most organizations use to define great leadership were built for a different era
Skills and competency models describe work that no longer exists in many roles or that AI now performs alongside, or instead of, humans. The gap between what organizations say they're selecting and developing for, and what the work actually requires, is widening quietly.
This creates a real problem. Organizations that don't redefine what great looks like now will be developing the wrong people for the wrong future optimizing for capabilities that are becoming less predictive while under-investing in the ones that matter most.
- Rebuild leadership profiles from a future-back perspective, starting with where the business is heading, not where it has been.
- Focus on the distinctly human capabilities AI cannot replicate judgment in ambiguous conditions, relational intelligence, ethical reasoning, the ability to set direction when there is no precedent.
- Increase the use of behavioral observation in selection and development. It's the only methodology that shows how someone actually thinks and decides under real pressure.
The signal worth chasing isn't on a resume, it's in the room in how someone handles a real situation, under genuine pressure. It's the only place where someone can't prepare their way out of being themselves.
2. Human differentiators are the last mile AI cannot close
Judgment. Empathy. Creativity. The ability to navigate genuine ambiguity. These are increasingly what separates human contribution from AI output and they're precisely the things most talent systems have always found hardest to measure.
For a long time, organizations could afford to treat these as qualities that would emerge naturally with experience. That's no longer an option. The human differentiators are becoming the job. And most organizations still aren't measuring them well.
The methods exist behavioral assessment, simulation, structured observation. And AI is now making them accessible at scale in ways that simply weren't possible before. The question isn't whether to use them. It's how to deploy them thoughtfully, with the governance and transparency that -stakes talent decisions require.
- AI-powered behavioral observation that surfaces how people actually perform in the flow of work, (i.e. judgement, decision-making, adaptability) not self-report
- Assessment that evaluated how people work with AI, not just without it because that's increasingly what the role looks like
- Simulation-based approaches that reveal thinking in action - the kind of evidence no credential or output can provide
3. The talent pipeline is broken
AI is displacing the early-career work that has traditionally served as the on-ramp into organizational life. Those tasks once gave emerging employees something more valuable than work product. They gave them foundational experiences, relationships, and judgment. The kind of judgment that eventually grows into leadership.
The impact won't show up immediately. That's exactly what makes it worth paying attention to now. Within three to six years, benches will thin and succession pipelines will require far more intentional investment. Organizations will find themselves asking why their internal talent isn't developing the way it used to.
The organizations that get ahead of this have a real opportunity to build something more deliberate, more equitable, and better suited to the capabilities the future actually requires.
- Invest in real, simulation-based experiences, putting emerging leaders into the decisions and pressures that build genuine organizational judgment, not just task exposure.
- Redefine what early-career development is, building toward the capabilities the future requires, not the ones the old job description described.
- Build feedback into the flow of work. AI behavioral observation and practice AI role plays make continuous development possible at scale. The experience that used to happen informally has to be designed now.
4. People need to re-skill faster than any development model was built to support
People need to reskill faster than any development model was built to support. Most organizational development infrastructure was built around a longer, more stable arc of skill acquisition. AI is compressing that arc significantly.
The implication isn't just that training needs to be faster. It's that the whole architecture of how organizations identify, develop, and deploy talent needs to be built for continuous recalibration not periodic refresh.
- Prioritize adaptability and learning agility over static expertise. The ability to acquire new capabilities quickly matters more than the specific capabilities someone holds today.
- Treat reskilling as a continuous organizational process, not an episodic program.
5. AI is absorbing leadership work and culture is losing it's anchor
This is the shift that's easiest to underestimate, and hardest to recover from once it arrives.
Culture is what people see leaders do. The behaviors leaders model how they make decisions, how they show up in hard moments, what they choose to reward and what they let go are how organizational culture gets transmitted. It doesn't travel through stated values. It travels through visible human behavior.
AI is absorbing the work that used to make leaders visible as humans making choices. Performance reviews written by AI. Communications drafted by AI. Coaching conversations mediated by AI. When the distinctly human work disappears, so does the signal. People don't know what to watch anymore. And culture which depends on that watching starts to fray.
The organizations that navigate this well won't be the ones that use less AI, they'll be the ones most intentional about which leadership behaviors remain visibly human, and why.
The behaviors that held culture together need to be rebuilt around what humans uniquely contribute now and that starts with getting the success profile right. That's exactly what the Future Ready Profile is built for.
Strengthen empathy-centered leadership capabilities. The human dimensions of leadership matter more, not less, as AI takes on more of the technical work.
- Strengthen empathy-centered leadership capabilities. The human dimensions of leadership matter more, not less, as AI takes on more of the technical work.
- Reinforce organizational purpose and human-centered culture as anchors.
- Treat culture as something you design, not something you inherit.
What this means
The organizations that navigate this well won't be the ones that adopted AI fastest, they'll be the ones that invested just as deliberately in the human systems around it.
These five shifts aren't warnings. They're design problems, and design problems have answers. The talent systems that come out of this moment can be more intentional, more equitable, and more fit for purpose than anything we've built before.
At BTS, this is the work we're doing every day. If you'd like to think through what any of it means for your organization, we’d love to talk.
The thinking in this article was shapped by Future Storming sessions, including a SIOP 2026 workshop, and by ongoing conversations with talent leaders navigating these shifts in real time.
In Part 1, I told you about the three decisions we made two years ago and the simulation flywheel that produced our first Applied AI diamond.
Here’s the field-notes version.
Over 80% of our global business have now adopted a new Applied AI approach for doing simulations in the first eight weeks, across 24 countries and every practice.
The flywheel didn’t stop with simulations. It moved into finance, sales enablement, legal, operations, and client delivery. Teams started building agents and bringing them onto their own org charts. We didn’t plan for any of that. We built the conditions for people to find their own breakthroughs.
What it felt like inside the flywheel.
When the simulation team went live with their first clients on the new way of working, the lead person hit a wall. Their words:
“You’re asking too much. You’re making me be a full-stack developer. Up until this point I did a small part, and I sent it to the team, and they built off the back end, and they brought it back. And now I have to end-to-end soup to nuts, basically alone.”
There was graphic UI work nobody had been trained for, the fear of delivering quality below what BTS expects of itself, and the weight of not having a playbook. This was not the joyful adoption story most consultancies tell.
Then something shifted. Six members showed up for product testing, where the usual was two or three. The work created teamwork I hadn’t seen at BTS in years. The breakthrough was not an instantaneous change from skepticism to celebration. It was a breakdown in confidence, then rally, then bonding. If we didn’t make room for the breakdown, we would have lost the rally.
The other breakthrough was global teamwork; not yet a BTS core strength. Our culture is beautiful: high-freedom and entrepreneurial. But people’s first identities are to their countries. Almost every prior attempt we’ve made at a global initiative has failed. The one exception was Covid. So, when I say what happened next surprised me, I mean it.
I asked to join the simulation team’s Slack channel rather than pulling them into status meetings. What I got to watch in the mornings was someone in South Africa waking up, posting “I tried this and got stuck,” then London adding on, then San Francisco weighing in, then a surprise breakthrough overnight from Tokyo. We didn’t engineer that. Curious and determined BTS’ers did. The problem was interesting enough that the org chart didn’t matter. It was amazing to see and a glimpse into the next evolution of the BTS culture.
The pattern: Explore, expand, institutionalize, renew.
What we’ve now seen play out, both inside BTS and with clients, follows the same four-step pattern. Each step asks a specific decision of the leader.
Explore.
Stay stubborn on the aspiration and fluid on the path. Our breakthrough wasn’t the path we originally took. We changed tools and approaches. Nobody could have foreseen that. And if the team had taken the first six months of learnings from AI as their definitive “this is the detailed path we will follow,” we never would have gotten the disruption. Five different tool combinations were tried before we found the one that worked. Companies that lock into a single path or tool too early are betting against compounding capability that doubles roughly every seven months. That is not a bet I’d take.
Expand.
Run the old way and the new way side by side. When the simulation team’s breakthroughs got real, the instinct was to retreat into more internal testing. We did the opposite. They ran old way and new way in parallel on 6 or 8 live client projects across all three geographies. Every single one ended up going live the new way. The backup was always there. They didn’t need it.
Institutionalize.
Burn the boats. The simulation team committed that no new client work would be done the old way after January 1. The other practice leads then committed to dates within Q1, even though most of them had not yet experienced the new way themselves. They had to trust their colleagues. If you can do it for the most complex thing, you could probably do it for the less complex ones. By February 15, we had approaching 90% global adoption across 24 countries, across all practices. I was shocked and proud. We had spent years failing at exactly this kind of global rollout.
Renew.
Treat your agents as contractors. People on our diamond teams are now managing 30+ agents they built themselves. Our teams give agents performance feedback. We terminate their contracts when they don’t deliver. We expand the responsibility of agents when they outperform. The frontier question we’re wrestling with now is token budgeting. Two friends of mine running engineering-heavy companies believe that within 6 - 9 months, their token cost per engineer will exceed the cost of the engineer. Whether that’s the right framing is open. The question is real, and every CEO will be asked some version of it within the year.
What had to be true for this to scale.
Once we achieved this amazing global innovation, the leadership sat down to figure out what made it work. We named five things. None of them were about the technology.
Real pain points as the starting point. We had so many people frustrated from those ways of working, all the back and forth and all the wasted time, that this was gold for them. The old way was already painful. The new way wasn’t a forced disruption; it was relief. Find the workflow where the pain is loudest and start there.
The diamond unlocked creativity, it didn’t constrain it. This was the most differentiated insight, and the one most leaders miss. It wasn't "here's the new tasks and rules." It was, "once you learn how to do this, the sky's the limit. You can be even more creative." If your rollout feels like a new set of rules constraining your people, you’ve built the wrong thing.
Pair deep expertise with fresh eyes. The disproportionate share of our breakthroughs came from a tenured tinkerer with total command of the work, paired with someone new to the role who hadn’t yet built the muscle memory of how it had always been done. Without that pairing, you get incremental improvements to the work you already know how to do, instead of a reinvention.
Refuse the “people are too busy” reflex. When I brought the rollout to the global leadership team, the excuses came fast. “Our people are too busy. They’re burnt out. Q1 is going to be busy. No one’s going to have time.” My response: “This is a chance to eliminate the tasks you dread and expand what you love. I know it is a short push of extra work, and I think after the fact you and your team will feel joy and pride and say it was the best time we ever spent.” This is the moment most AI rollouts die.
Senior leaders must lead by example and do the work themselves. This is not middle manager’s job. This is not something you delegate. Even though you don’t build simulations anymore, you must know what this is. One of our partners proactively put time on senior leaders’ calendars and forced them to do the work. Once they started building, the excitement grew, and they could advocate for the rollout because they understood it. If your executives haven’t put their hands on the keyboard, you don’t have a rollout. You have a memo.
What we’re seeing across clients.
We’re now running this play with client organizations across industries and geographies. The companies whose flywheels are accelerating paired their A-players with their early-career talent, pulled IT and legal into the working sessions, refused the “too busy” reflex, and put their senior leaders’ hands on the keyboard. The companies whose flywheels are stuck almost always have a leadership pattern at the center of the stall. Not a tooling pattern. Not a governance pattern. A leadership pattern.
If this resonates, let’s talk.
If you read Part 1 and asked yourself whether your flywheel was turning, the question I’d add now is sharper: do you have the conditions in place for a diamond to appear? If yes, you’re already moving. If no, the technology will not save you.
Here's where we're starting with clients: a working session, half day to a full day, with a small group that owns one of your highest-friction processes. Together we map where your first diamond is most likely to land, how to set up the side-by-side trial, and what your version of "burn the boats" should look like.
The destination, if we do this right, is a self-reliant culture of applied AI inside your company. 5, 10, 15 diamonds compounding into a fundamentally different way of operating. From what I have experienced this is a once in a career opportunity for dramatic shareholder value creation if you get that muscle going. I say that because I'm watching it happen, in real time, inside our own company and across our client base.
If you want to get your flywheels spinning and map your first diamond, start here. Bring your hardest workflow. We'll bring the playbook.
At BTS, we’re constantly challenging ourselves to innovate at speed. And right now, it feels like we’re standing at the edge of something massive. The energy? Electric. The velocity? Unprecedented. For many of us, the current pace feels a lot like the early days of the pandemic: disorienting, high-stakes, and somehow exhilarating. And honestly—it should feel that way. Our teams have been tinkering with AI, specifically LLMs, for the past 2.5 years and it has really been in the last eight months that I can see the profound impact it is going to have for our clients, for our services and our operating model.
The opportunity isn’t about the technology. The world has it and it’s getting better by the minute. The issue is people and people’s readiness to adopt it and be re-tooled and re-skilled. It’s about leadership. AI is deeply personal, it’s surgical. In fact, that’s its genius. So, getting full scale adoption of AI, re-tooling everyone in the company by workflow, so that they can invent new services, unlock new customer value, unlock new levels of productivity, even use it for a better life, is the current race. The central question I’ve been wrestling with, alongside our clients and our own teams, is this:
What does AI actually mean for leadership and culture?
And the answer is clearer by the day: AI isn’t just a new toolset. It’s a new mindset. It demands that we rethink how we lead, how we learn, and how we build thriving organizations that can compete, adapt, and grow.
The productivity paradox revisited
Let’s start with the elephant in the boardroom. There’s been a lot of buzz around AI and its promises. But many leaders have quietly wondered: Will any of this actually move the needle? A year ago, we were asking the same thing. We had licenses. We had curiosity. We had early experiments. But the results were modest, a 1% productivity gain here or there. But by April, we were seeing:
- 30–80% productivity gains in software engineering
- 9–12% gains in consulting teams
- 5%-20% improvements in client success and operations
Just as importantly, the innovation unlock and creativity across our platforms due to vibe coding along with new simulation layers, is leading to new value streams for our clients. This isn’t theoretical. It’s not hype. It’s real. The difference? Adoption, ownership, and a shift in how we lead in order to energize the AI innovation within our teams. The challenge now isn’t whether AI creates value. It’s how to unlock and scale that value across teams, geographies, and business units—and do it fast.
Two Superpowers of the Agentic AI Era
In working with leaders across industries, I’ve come to believe in two superpowers (there are more as well) that will unlock the potential of this AI era: Jazz Leadership and a Simulation Culture.
1. Jazz Leadership
Forget the orchestra (although personally I am a big fan.) The successful team cultures that are innovating with AI feel more like jazz. In jazz, there’s no conductor. There’s no fixed sheet music. There are core bars and then musicians make up music on the spot based on each other’s creativity, building off of each other’s trials, riffs and mistakes, build something extraordinary together. This is how experimenting with AI today, in the flow of work, feels like.
For each activity across a workflow, how can new AI prompts, agents, and GPTs make it better, codify high performance, drive speed and quality simultaneously? How can we try something totally different and still get the job done? How might we re-invent how we work? That’s how high-performing teams operate in the AI era. The world is moving too fast for command-and-control leadership, a perfect sheet of music with one leader who is interpreting the sheet music and directing. What we need instead is improvisation, trust, shared authorship, courage and a playful spirit because there are just as many fails as breakthroughs.Jazz leadership is about creating the conditions where:
- Ideas can come from anywhere
- People see tinkering and testing as key to survival and AI failures mean your team is at the edge of what’s possible for your services and ways of working
- Leaders say, “I don’t have all the answers, but I’ll go first, with you”
- People feel “I’m behind relative to my peers in the company” and the company sees this as a good sign because the pace of learning with AI means higher chance of success in the new era
At BTS, we recently promoted five new partners who embody this mindset. They weren’t the most traditional leaders. But they were the most generative. They coached others. They experimented and are constantly re-tooling themselves and others. They inspired movement. They are keeping us ahead, keeping our clients ahead and driving our re-invention. Jazz leaders make teams better, not by directing every note—but by setting the stage for breakthroughs. It is similar to the agile movement, similar to how it felt in Covid as companies had to reinvent themselves. It’s entrepreneurial, chaotic and fun.
2. Simulation Culture
The ability to simulate is a super-power in this next agentic, AI era. Simulation has always been part of creating organizational agility, high performance and leadership excellence. But AI and high-performance computing have transformed it into something bigger, faster, and infinitely more powerful. It means that building a simulation culture is within all of our grasp, if we tap its power.Today, companies simulate:
- Strategic alternatives - from market impact all they way to detailed frontline execution
- New business, new markets and operating models
- Major capital deployment e.g. build a digital twin of a factory before breaking ground
- Initiative implementation
- Workflows current and future
- Jobs to assess for talent and critical role readiness
- Customer conversations and sales enablement motions
With a simulation culture, where you regularly engage in scenario planning and expect preparation and practice as a way of working, billions in capital is saved, cross-functional teams are strengthened, high performance gets institutionalized, win rates increase, earnings and cash flow improves.
Where to get started
Below are a few examples of what leading organizations are doing. Consider testing these in your own organization:
- Conversational AI bot platforms used to scale performance expectations and the company’s unique culture.
- Agentic simulations built into tools so people can prepare and practice with 100% perfect context and not a wasted moment.
- Digital twins of the job created so that certifications and hiring decisions are valid.
- Micro-simulations spun up in hours to align 50,000 people to a shift in the market or a new operational practice.
Final Thoughts
- Lead like a jazz musician. Embrace improvisation, courage and shared creativity.
- Build a simulation culture. Because in a world that’s moving this fast, practice isn’t optional—it’s how we win.
This is a brave new world. Not five years from now. Right now.Let’s shape it—together.
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How CEOs can win at applied AI by trusting teams to reinvent their work, setting AI flywheels in motion, and scaling breakthroughs from the frontlines.
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Brandon Hall Group, the leader in Empowering, Recognizing and Certifying Excellence in HCM, recently announced that BTS is certified as a Smartchoice® Preferred Solution Provider, confirming BTS's leadership in transforming strategy into measurable human performance.
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