The year of giving back and sharing expertise

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.

PRESS RELEASE

Stockholm, May 5, 2025

STOCKHOLM, SWEDEN — BTS Group AB (publ), a leading global consultancy specializing in strategy execution, change, and people development, has agreed to acquire Nexo Pesquisa e Consultoria Ltda. (Nexo), a boutique consulting firm headquartered in São Paulo, Brazil.

Nexo has been growing continuously since it was founded in 2017. With revenues of approximately 12 million Brazilian Reales (about 2.1 million USD) in 2024, and a highly capable team of 21 members, Nexo has built a strong reputation for delivering transformative projects in strategy, innovation, leadership, and culture.

Nexo collaborates with a diverse portfolio of clients across sectors such as financial services, consumer goods, and technology, assisting both local and global companies in navigating uncertainty, unlocking creativity, and activating strategy through people. Their work encompasses culture transformation, leadership development, employer value proposition, innovation culture, and vision alignment—supported by proprietary methodologies and frameworks.

BTS currently operates in Brazil, servicing both local and multinational clients with a team of 13 employees. By acquiring Nexo, BTS not only increases the Group’s footprint in Brazil but also adds significant capabilities in culture and transformation services. Nexo’s client base has limited overlap with BTS, creating strong growth potential and synergy opportunities.

“Nexo is known for helping leaders and organizations tackle some of the most complex, human-centered challenges with creativity, empathy, and strategic clarity, and the Nexo team is loved by their clients,” says Philios Andreou, Deputy CEO of BTS Group and President of the Other Markets Unit. “Their products and services complement and elevate our existing offerings, especially in culture transformation, and we are thrilled to welcome the Nexo team to BTS.”

“We’re excited to join BTS. We’ve long admired BTS’s approach and unique portfolio to support large organizations and leaders in connecting strategy with culture across the organization,” says Andreas Auerbach, co-founder of Nexo. “Becoming part of BTS allows us to scale our impact and bring more value to our clients while staying true to our values and culture,” adds Mariana Lage Andrade, co-founder of Nexo.

Upon completion of the transaction, Nexo’s business and organization will merge with BTS Brazil. Nexo’s founders will assume senior management roles in the joint operation.

The acquisition includes a limited initial cash consideration. Additional purchase-price considerations will be paid between 2026 and 2028, provided Nexo meets specific performance targets. A limited portion of any such additional considerations will be paid in newly issued BTS shares. The transaction is effective immediately.

BTS’s acquisition strategy continues to focus on broadening its service portfolio, expanding geographic reach, and enhancing capabilities to support future organic growth in a fragmented market.

For more information, please contact:

Philios Andreou
Deputy CEO
BTS Group AB
philios.andreou@bts.com

Michael Wallin
Head of Investor Relations
BTS Group AB
michael.wallin@bts.com
+46-8-587 070 02
+46-708-78 80 19

STOCKHOLM, SWEDEN and SAN FRANCISCO, CALIFORNIA, June 2023 – BTS has signed the Human Rights Campaign and GLAAD’s “Count Us In” Pledge, which affirms leading businesses and employers’ support for LGBTQIA+ inclusion and equality in the workplace and beyond.

BTS is committed to creating a professional environment that is inclusive, safe, and supportive of people of all gender identities and sexual orientations.

“We stand with the LGBTQIA+ community in the fight for equality,”

says Kathryn Clubb, CEO of BTS North America.

“We loudly celebrate LGBTQIA+ diversity and resilience. As an organization and brand, we are committed to demonstrating this support in publicly visible ways. PRIDE month has given us the opportunity to celebrate, learn, appreciate, and understand the LGBTQIA+ community. We are emboldened to take action, speak up, and be better allies.”

In signing this pledge, BTS commits to taking a stand for its LGBTQIA+ employees and clients. Through advocacy, in partnership with lawmakers on the front lines, BTS is committed to supporting broader social change that will shape the world for the better. In tandem with this pledge, BTS has formed an internal taskforce to lead its ongoing discussion and commitment by identifying opportunities for additional advocacy efforts.

“I’m so proud of BTS and the ways in which we are taking a stand to create a better world for our clients, our communities, and our employees,”

said Kathryn Clubb.

“In the words of P. T. Barnum, ‘Comfort is the enemy of progress.’ May we never get too comfortable.”

BTS stands alongside more than 75 other leading businesses, including many clients, in taking this pledge. To learn more about the Pledge and what it stands for, click here.

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There’s a specific kind of strategy meeting getting scheduled right now, in nice hotels with bad coffee: the AI reset off-site.

And for good reason. In a 2026 WRITER survey, 48% of leaders described their AI rollout as, in their own words, a "massive disappointment." That's nearly half the room.

What that number really measures is the distance between what these tools can do and what people are doing with them. In our experience, that distance is almost entirely human.

Which is why the off-site is the right instinct. Making the most of that time is the harder part.

What separates an AI reset that actually changes the game from an expensive two-day conversation? In our experience, it comes down to avoiding four common design mistakes.

Mistake 1

Blaming the bots

The gap between AI investment and real adoption is almost always about people, not technology. And when adoption stalls, we usually find it's one of four things.

1. They don't think it will help them
2. Nobody around them is using it
3. They don't feel capable
4. Or they don't have real access to the tools they were promised

Four different problems, and four completely different fixes.

That's why diagnosis comes first. If you don't know which barrier you're dealing with, every intervention becomes an educated guess. And you cannot tell which one you have by staring at a dashboard. A belief gap and a skill gap look identical in a status report and need opposite interventions. Show up guessing, and you'll spend real money teaching people to use a tool they simply don't trust yet. Congratulations - you've just catered the wrong conversation.

Mistake 2

Letting leaders off the hook

One of the biggest predictors of whether change sticks is also one of the most overlooked: leadership.

If your executives show up as observers, nodding along and quietly answering email under the table, your people clock it in about four minutes.

That doesn't mean your CEO has to emcee the thing. It means they use the tools in front of everyone, participate in the conversation, and make it clear this isn't someone else's initiative.

Recently we’ve been working with a Fortune 200 global professional services firm who’s top 120 leaders were at very different points with AI. Some were redesigning entire processes. Others were using it to summarize emails, or not at all. Rather than focus on the technology, the four-hour session focused on what leaders could do with AI, applying it to a live strategic challenge and ending with a personal commitment to lead differently. The response was strong enough that the organization is now cascading the experience globally.

The lesson is simple: when leaders experience AI as a strategic capability, they're better equipped to model the behavior that makes adoption stick. Nothing you build during those two days survives without that entire chain of leadership doing its part.

Mistake 3

Chasing the wrong outcome

Without a behavioral baseline, you have no way to prove anything actually moved. No baseline, no ROI. You're just hoping the energy in the room was good, which is a wonderful feeling and a terrible metric to bring to your CFO.

But the baseline isn't just about proving the off-site worked. It's about understanding where you're starting in the first place. And you'll want that clarity, because the quiet resistance is real. In that same 2026 research, nearly a third of employees admitted to actively working around their company's AI strategy. If you don't win their belief in the room, some of them will keep politely ignoring the whole thing from their desks. You can't measure your way out of that. You have to earn your way out of it.

Which brings us to the biggest reframe of all.

Mistake 4

Leaving follow-through to chance

We've been working with a Fortune 100 medical device company on their AI strategy for three years. It started with their leadership team, a three-hour session built around what those leaders would do differently, and it landed. What became clear afterward was that the same experience needed to happen everywhere else. So, it expanded: 90-minute activations for 15,000 people, and this year intact teams redesigning their own workflows.

Three years in, that first session is the smallest part of the story.

Your event is where momentum gets created. What happens at 30, 60, and 90 days is where results get made.

If you're planning one of these and want to change what happens on Monday, not just how everyone feels on Friday, that the work we do.

‍We'd be glad to help you design it.

Candidates now arrive at interviews pre-coached by AI, with their resumes optimized to pass every checkpoint. Polish has stopped being a signal. The traditional hiring process was built to read exactly the cues that AI is now best at producing, and the signals hiring managers once relied on have weakened as a result. And for roles where the wrong hire carries real business consequences, losing the ability to tell who will actually perform is not a minor inconvenience. It is a material risk, and it exposes the business to unnecessary turnover, reduced performance, and heavier investment for talent growth and development.

So how do you observe the behaviors that matter most, before someone is in the role?

Not by asking better questions, but rather by putting candidates in situations designed to elicit that behavior.

The limits of predicting from paper

Credentials tell you what someone has done. Structured interviews tell you what someone says they would do. Neither lets you observe what they actually do in the moments that count.

This distinction matters most in client-facing, relationship-driven roles, where the performance gap between a strong hire and a weak one plays out in real business outcomes (revenue, retention, client growth). Organizations that hire at scale in these roles carry that gap across hundreds of decisions at a time.

The better approach is to watch candidates do the work before you hire them. Put them in simulated, role-relevant scenarios, and pair the simulation with a second, different kind of measure so no single method carries the whole decision. That combination is what lets you evaluate real performance before anyone is in the role. Organization-specific simulations provide a clear read on who is ready and capable of performing on day one. In a world of AI-supported candidate signals, the use of simulations makes the process harder to prep for. It is harder to fake. And, when designed well, it is substantially more predictive than other hiring methods.  

What counts as evidence

Claims about predictive power are easy to make. Evidence for them is rarer than you would expect.

A predictive validity study, the kind that links pre-hire assessment scores to how someone actually performs once hired, is some of the hardest evidence to produce and the rarest to see. Many assessments are validated against proxies: another test, or a theoretical model of the role, rather than real results on the job. Connecting scores to concrete business outcomes and doing the statistical work to show the link holds, takes years of shared data and a level of commitment from both the assessment provider and the client that most partnerships never reach. That is precisely why it is worth asking for. A provider who can show how assessment scores track to training completion, retention, and first-year output is offering something categorically different from one who can only show a correlation with another test.

Why simulation holds up where other methods do not

When a candidate sits across from a trained assessor (someone playing the client or prospect on the other side of the conversation) and has to work through a real situation, they cannot rely on a rehearsed answer. The scenario is specific. The stakes feel real. What you see is close to what you would get on the job.

That is the value of simulation-based assessment: it does not test what candidates know about the role.

It shows how they use what they know when a real person is on the other side of the conversation, before the stakes are real.

For roles that carry significant business responsibility, this distinction is the whole game. The cost of the wrong hire in a high-stakes client-facing role is not just a missed quota for a quarter - It plays out in relationships that do not develop, clients who leave, and productivity losses that compound over time. Getting those hiring decisions right, at scale, with consistency, requires methods that are built for predictive accuracy, not just candidate experience or hiring speed.

What this means for how organizations think about hiring

Most organizations are still optimizing the wrong things in their hiring process. They invest heavily in employer branding, application flow, and interview structure, all of which matter, but less in the core question: does our hiring process actually predict who will succeed in this role?

AI has sharpened the stakes here. If every candidate can present as polished and prepared, screening based on presentation becomes less useful. What holds up is direct observation of the behaviors that the job requires.

A few principles worth building from:

• Measure what the job requires, not what is easy to measure. Cognitive tests and personality questionnaires have their place, but they do not look much like the job. The closer the assessment is to the actual work, the better it predicts performance in it.

• Ask what your assessment predicts. Training completion? Retention? First-year output? Most organizations cannot answer that question today, largely because providers have rarely been asked to prove it. It is a fair thing to ask for.

• Take the human element seriously. In a simulation, a candidate is having a real conversation, responding in real time, navigating a situation that requires judgment. Even with the help of AI, that is hard to game. And it remains one of the strongest predictors of on-the-job performance available.

The data exists to make hiring decisions more accurate, fairer, and more directly tied to business outcomes. For organizations operating in high-stakes roles at scale, there is too much on the line to rely on methods that cannot hold up to that standard.

You may be interested in BTS’ thought leadership in the five talent shifts AI is forcing now.  

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La IA ya forma parte del día a día de las ventas. Hoy cualquier asesor puede llegar a una reunión con datos, tendencias e insights generados en segundos. Sin embargo, disponer de más información no garantiza conversaciones de mayor valor.

A través de una experiencia real con un consultor comercial, este artículo explica por qué la inteligencia artificial funciona como un GPS: ayuda a interpretar el entorno, pero no conduce la conversación ni entiende las prioridades del cliente.

En este artículo descubrirás:

• Por qué el acceso a la información ya no supone una ventaja competitiva.
• La importancia del business acumen para interpretar los datos con criterio.
• Cómo hablar el lenguaje del cliente genera credibilidad y diferenciación.
• Por qué las relaciones B2B evolucionan hacia relaciones P2P basadas en la confianza.
• Qué capacidades consultivas seguirán siendo exclusivamente humanas incluso en la era de la IA.

La tecnología seguirá evolucionando, pero la ventaja competitiva estará en quienes sean capaces de combinar inteligencia artificial con conversaciones centradas en el cliente, pensamiento estratégico y relaciones de largo plazo.