BTS Resources
Empowering decision makers: Hands-on strategy training for tomorrow’s leaders
Three decisions that changed everything.
Two years ago, we made three deliberate decisions about how BTS would move with Applied AI.
We would become our own Customer Zero.
While others were building strategies, defining governance, and waiting for clarity, we made a different call: we decided not to wait. Not because the stakes were low, but because they were high. And because in a space evolving this quickly, clarity wouldn’t come from planning. It would come from movement.
So instead of starting with a roadmap, we started with three principles:
- No top-down mandate. The people closest to the work figure it out.
- IT must evolve from gatekeeper to enabler - leading AI trials and fast experimentation.
- Don’t wait for certainty.
We set the organization in motion, and once we did, things started to move quickly.
What if we started this company today?
Waiting for certainty is itself a choice, and it’s costing companies more than they realize.
We started where we knew the work best: our simulations. No perfect plan, just teams moving, trying, and iterating.
Simulations are core to who we are at BTS. Companies that simulate don’t just make better decisions; they execute faster and build more engaged cultures.
The team asked a simple question:
"What if we were to start our company today?”
That question started the flywheel.
They asked IT for a few licenses and started building - vibe-coding, writing agents, and testing tools - moving at a pace that would make any VC-backed start-up smile.
The messy middle.
At first, the team was underwhelmed.
The early reports were blunt:
“Not good with math.”
“Poor graph capabilities.”
The team wasn't discouraged. They kept tinkering - jumping between tools, staying on top of new releases, experimenting constantly.
This was a small team, across 24 countries, building off each other’s ideas. Laughing at crazy creations. Breaking things. Iterating in a sandbox alongside real clientwork.
Each cycle produced something:
- A sharper scenario
- A faster build
- A more powerful simulation
The flywheel was turning, and it was generating something real.
When the diamond appeared.
Then something shifted.
The team moved into client trials across five countries. They figured out ISO compliance and built the architecture to handle the complexity, the “spaghetti.”
And what emerged wasn’t incremental:
- What used to take weeks started happening in days.
- Limited creativity started to feel like unlimited innovation.
- Clients became self-serving.
- Agentic simulations were built directly into client systems for real-time updates and preparation.
This was our first AI diamond - a high-impact outcome created by many cycles of experimentation compounding into real value.
It only appeared because we kept the flywheel turning, each cycle increasing the odds that something would break through.
95% adoption in eight weeks.
Then it was time to take the AI diamond global.
BTS is decentralized and highly entrepreneurial. We operate across 24 countries and 38 offices, where local teams have real autonomy.
And historically? That’s meant a low appetite for adopting something built somewhere else and pushed from the center.
So we expected resistance.
Instead, something surprising happened.
In the first eight weeks, we saw 95% adoption across our global footprint.
It felt completely different from our own digital initiatives, ERP implementations, top-down rollouts of the past.
This moved on its own. Why?
We realized it didn’t start with a framework or a model, it started with a feeling.
The feeling of being at the leading edge of one’s craft and profession.
- Joy
- Excitement
- Pride
As we watched this play out across teams it stopped feeling like isolated wins.
There was a pattern to it. A repeatable, organic, innovation motion.
And the flywheel didn’t stop with simulations.
It spread across finance, sales enablement, legal, operations, and client delivery. Some cycles led to small improvements, and others revealed new diamonds.
Not becausewe planned for them, but because we built the conditions for people to find them.
The question I'd ask any CEO right now: Is your flywheel turning, or are you still waiting for the perfect plan?
In part 2, I’ll share the key success factors behind the breakthrough, and what we’re now seeing across more than 120 global clients.
Organizations have long wanted to scale coaching, but have been limited by cost and capacity. With AI, that's beginning to change as new platforms make coaching more accessible, flexible, and available on demand, extending support beyond a select group of leaders to entire populations.
For talent leaders, this shift creates both opportunity and complexity. With greater reach comes a new set of trade-offs: how to balance access with depth, flexibility with accountability, and efficiency with meaningful development.
The limits of unlimited (coaching).
Unlimited coaching sounds like the obvious answer. Remove the barriers, give everyone access, let people engage on their own terms. What's not to like?
In practice, quite a bit.
When coaching has no defined structure or cadence, engagement tends to become episodic - people show up when something feels urgent and step back when it doesn't. The coaching relationship never quite deepens. Conversations cover ground but don't build on it. And the development that was supposed to happen keeps getting pushed to the next session, and the next.
Three patterns emerge:
- Sporadic engagement over sustained development. Without a rhythm to anchor the work, coaching becomes reactive. Clients bring whatever is most pressing that week rather than working toward something larger. Progress happens in bursts, if at all.
- Insights that don't compound. Great coaching reveals patterns over time - things a client can't see in one session but can't unsee after several. Without continuity, and without a consistent coaching relationship to hold the thread, each conversation starts close to zero.
- Outcomes that are hard to measure. No milestones. No defined endpoint. No clear way for the organization, or the client, to know whether it's working. Activity fills the gap where impact should be.
The result is a model that's easy to scale and hard to defend. Which is exactly the problem talent leaders are navigating right now.
The relationship is the lever.
Decades of research into what makes coaching work keeps arriving at the same answer: it's the relationship. Not the platform, not the methodology. The relationship.
When a coach and client build trust over time, developing shared language, and returning to the same themes with increasing depth, something shifts. Conversations get more honest. Insights stick. The client starts doing the work between sessions, not just during them. That's when coaching becomes genuinely transformative, and it can't be rushed or replicated in a one-off session.
The ICF and EMCC are clear on this: continuity is what dives outcomes. The coaching engagements that produce lasting change are the ones where each session builds on the last, not the ones that simply offer more access.
Three principles make that possible: Consistency, Continuity, and Completion.
1. Consistency
The foundation everything else is built on.
The temptation when designing a coaching program is to treat flexibility as a feature - let people book when they want, swap coaches freely, engage on their own schedule. But frequent coach changes reset the clock. Every new coach has to earn trust, learn context, and find their footing with the client. That's time spent getting started, not getting somewhere.
A stable coaching relationship works differently:
- The coach starts to see around corners, uncovering patterns the client can't see on their own
- The client stops performing and starts being honest
- The relationship itself becomes a source of accountability, not just the sessions
Consistency doesn't constrain the work. It's what makes the deeper work possible.
2. Continuity
What turns a series of sessions into genuine development.
Without continuity, coaching tends to be additive at best- each session offers something useful, but nothing compounds. With it, the work builds on itself in ways that can't happen in isolated conversations.
What continuity makes possible:
- A limiting belief surfaced in session three becomes a thread that runs through the rest of the engagement
- A behavioral pattern the client couldn't see at the start becomes impossible to ignore by the end
- Space opens up for the harder work - the kind that requires sitting with discomfort across multiple sessions, not resolving it quickly and moving on
That slower, deeper work is where lasting change actually happens. It doesn't come from more sessions. It comes from the right sessions, in the right order, with the same person.
3. Completion
The most underrated principle of the three.
In a world of unlimited access, there's no finish line, and without one, it's surprisingly hard to know what you're working toward, or whether you've gotten there. A defined endpoint changes the entire shape of an engagement.
A clear endpoint creates urgency and focuses every session on what matters most.
- Shifts the question from "what should we talk about this week?" to "what do we need to accomplish before we're done?"
- Gives both coach and client a body of work to look back on, not just a log of conversations
For talent leaders, this is also what makes coaching legible as an investment. Sessions logged is an activity metric. A cohort of leaders who completed a structured engagement and can articulate what changed, that's a result.
Don't just scale it, design it (here’s how)
The opportunity in front of talent leaders right now is significant. The organizations that will get the most from this moment are the ones that treat coaching design as seriously as coaching delivery.
Practical design decisions:
- Define the arc before you launch: set the number of sessions, the cadence, and the goals upfront, not after people have already started booking
- Protect the coaching relationship: Make coach switching the exception, not the default, and design your program to discourage unnecessary re-matches
- Build in milestones: create structured check-ins at the midpoint and end of each engagement so progress is visible to both the coach and the organization
- Separate on-demand support from developmental coaching: Use AI-enabled tools for in-the-moment guidance, and reserve structured engagements for the deeper work
- Measure completion, not just activation: Track how many people finish an engagement, not just how many start one
Questions to pressure-test your design:
- Does every participant know what they're working toward before their first session?
- Can your coaches see enough context about a client's journey to pick up where they left off?
- Would you be able to show, at the end of a cohort, what changed, and for whom?
Access opened the door. Intention is what makes it worth walking through.
Across industries, safety is undergoing a structural shift. What was once managed primarily as a compliance function or performance metricis increasingly understood as a reflection of how organizations are designed, led and continuously improved.
In complex and high-risk environments, safety is notachieved through stronger enforcement or additional programs alone. It emerges from the interaction between leadership behavior, operational design, decision environments and the organization’s capacity to learn and adapt.
Drawing on global safety science, Human & Organizational Performance (HOP), research on psychological safety, and our cross-industry transformation experience, eight key shifts are shaping the next evolution of safety culture.
1. Safety as a Core Organizational Value
Safety is moving beyond being treated as a shifting priority. Priorities compete. Values guide.
When safety becomes a core organizational value, it shapes decision-making, trade-offs under pressure, operational planning and resourceallocation. Safety becomes the natural consequence of how the system operates,rather than a campaign layered on top of production.
This shift also redefines the role of safety functions, from compliance policing to enabling safe and sustainable performance.
2. Learning as an Operating Discipline
Organizations are embedding continuous learning into everyday operations. Rather than focusing only on what failed, they exploreweak signals, near misses, operational friction and successful adaptations.
Learning becomes a core capability, accelerating insight, strengthening resilience and improving decision quality.
3. Leadership Ownership at All Levels
Safety culture is increasingly recognized as a leadership capability, not solely an HSE responsibility.
Executives define direction and tone.
Middle managers translate expectations into operational decisions.
Supervisors shape the daily decision environment.
Successful organizations translate safety expectations into concrete leadership behaviors and daily routines, creating clarity and alignment across levels.
4. Psychological Safety as Infrastructure
A strong safety culture depends on speaking-up environments.
When employees feel psychologically safe, weak signals surface earlier, risk trade-offs are openly discussed and learning accelerates.
Psychological safety is operational infrastructure , not a soft topic.
5. Amplifying What Works
There is growing recognition that most work is completed safely, often under variable conditions.
Studying success reveals adaptive capacity and strengthens resilience. This complements traditional incident analysis by reinforcing expertise and confidence.
6. Aligning Work-as-Imagined and Work-as-Done
Procedures and plans rarely capture operational complexity perfectly.
Leading organizations reduce the gap between policies and operational reality by inviting front line input and empowering stop-work authority.
The goal is better alignment between design and execution.
7. Designing for Human Decision-Making
Incidents often stem from predictable cognitive biases such as normalization of deviance, production bias, overconfidence and hindsight bias.
Recognizing these decision traps shifts focus from blaming individuals to strengthening decision environments.
8. Cultural Evolution as a Long-Term Capability
Sustainable safety culture requires integration rather than reinvention, structured capability journeys rather than one-off programs, and measurable behavioral impact rather than activity metrics.
Organizations that succeed:
- Integrate safety into existing leadership and operational systems
- Design earning journeys that support day-to-day application
- Measure behavioral change and operational outcomes
- Reinforce progress consistently over time
Cultural evolution is a sustained commitment to system alignment and capability building.
Conclusion
The evolution of safety culture is less about adding controls and more about strengthening systems.
Safety is something organizations produce — through leadership clarity, operational design, psychological safety and continuous learning.
Those who embed these capabilities consistently will not only reduce risk. They will build more resilient, sustainable and high-performing organizations.
Sources & references:
- WorldSteel Association. Safety Culture & Leadership Fundamentals.
- Norsk Industri (2025). Safety Leadership and Learning: A Practical Guide to HOP.
- D. Parker et al. / Safety Science 44 (2006). Development of Organisational Safety Culture
- Hollnagel, E. (2014). Safety-I and Safety-II: The Past and Future of Safety Management.
- Hollnagel, E. (2018). Safety-II in Practice: Developing the Resilience Potentials.
- Conklin, T. (2012). Pre-Accident Investigations: An Introduction to Organizational Safety.
- Edmondson, A. (2018). The Fearless Organizations
- Reason, J. (1997). Managing the Risks of Organizational Accidents.
- Resilience Engineering research (Hollnagel,Woods, Leveson and others).
Today’s customers are more informed, more selective, and more time-poor. They need conversations that help them prioritize, decide, and move forward.
And yet, 58% of sales meetings fail to create real value.
Not because sellers lack capability, but because conversations are not designed to move decisions forward.
“Customers don’t act on every need they recognize.
They act when something becomes a priority.”
In this short executive brief, you’ll discover
- Why most conversations inform… but don’t drive action
- What actually makes customers prioritize and move
- How to create urgency without damaging trust
- The shift from presenting solutions to enabling decisions
- What separates conversations that stall from those that accelerate momentum
If your teams are experiencing stalled deals, delayed decisions, or slow pipeline movement, this brief will help you understand why, and what to do differently.
Global organizations are facing a profound shift in how technology work is structured, managed, and experienced. In the age of artificial intelligence, the challenge of managing technology talent is no longer simply a question of supply and demand — it is a structural transformation of cognitive work itself.
Traditional narratives about the “war for talent” fail to capture the complexity of what organizations are experiencing today. What we are witnessing is not merely a competition for higher salaries, but a systemic reaction to organizational friction, outdated operating models, and the increasing complexity introduced by AI-driven development environments.
Recent data from the Spanish technology market provides a clear signal of this transformation. Nearly 70% of IT professionals report either active job searching or openness to new opportunities, a figure significantly higher than the global average. This trend reflects a growing disconnect between organizational expectations of productivity — often driven by rapid AI adoption and return-to-office mandates — and the everyday experience of engineers, developers, and technical specialists.
Rather than simply seeking better compensation, many professionals are responding to deeper structural challenges within organizations. These include bureaucratic processes, constant interruptions, fragmented information systems, and management practices that are poorly adapted to modern technology environments.
A changing talent ecosystem
Over the past decade, Spain has evolved from a nearshore services hub into a major European technology center. Global corporations have established innovation hubs in cities such as Madrid, Barcelona, Málaga, and Zaragoza, bringing new investment and opportunities.
However, this transformation has also created a dual labor market. On one side are traditional enterprises and consultancies operating within conventional management models. On the other are global technology companies and well-funded startups introducing international work practices and more competitive compensation structures.
This competition has intensified talent mobility. In cities like Madrid and Barcelona — which account for the majority of technology job movement in the country — switching employers has become increasingly frictionless for experienced professionals.
The hidden crisis of engagement
Beyond job mobility, a deeper issue is emerging: declining engagement among technology professionals.
Employee experience data shows a growing gap between how organizations perceive their culture and how employees actually experience their work. A significant share of employees would not recommend their company as a place to work, and overall engagement metrics have declined.
This erosion of engagement is particularly dangerous in technology environments where specialized talent is constantly approached by recruiters and global employers. Many professionals live in a state of what could be described as permanent passive job searching, where they remain open to opportunities even if they are not actively looking.
When professional pride declines and trust in leadership weakens, the barriers to leaving an organization disappear.
The rise of autonomy and project-based work
Another important shift is the growing appeal of contracting and project-based work models.
Historically, Spain has been a highly salaried technology labor market. However, an increasing number of senior professionals are exploring freelance or contracting models, not only for financial reasons but as a deliberate choice for greater autonomy.
These professionals prefer to manage their careers as independent service providers, selecting projects based on technical challenge, innovation potential, and learning opportunities.
For organizations, this creates a new form of competition. The challenge is no longer only competing with other companies for talent — it is also competing with the appeal of professional independence.
The AI productivity paradox
Artificial intelligence has rapidly become a central part of software development workflows. Tools such as generative coding assistants promise dramatic productivity gains.
However, emerging research suggests a more nuanced reality.
While AI tools can accelerate code generation, they do not eliminate the complexity of engineering work. Developers must still understand system architecture, interpret business context, design solutions, and debug subtle logic errors.
In many cases, AI-generated code introduces new challenges, including hidden bugs or inconsistencies that require additional validation. As a result, developers are increasingly shifting from writing code to reviewing, editing, and validating AI-generated outputs.
The productivity gains promised by AI therefore depend not only on technology itself but on how work is organized around it.
Developer experience: the overlooked productivity lever
One of the most revealing insights from engineering productivity research is how developers actually spend their time.
Studies suggest that developers spend less than 20% of their time writing code. The majority of their workday is consumed by coordination, meetings, searching for documentation, managing dependencies, and navigating internal systems.
These interruptions fragment attention and disrupt deep focus. Recovering from a single interruption can take more than twenty minutes, making sustained concentration difficult.
For this reason, leading organizations are increasingly focusing on Developer Experience (DevEx) as a strategic priority. Improving internal tools, reducing bureaucratic processes, and creating better workflows can unlock productivity gains far greater than technology adoption alone.
Leadership as the real bottleneck
As AI reshapes work processes, leadership practices must evolve as well.
In many organizations, middle managers find themselves under growing pressure. They are expected to accelerate innovation, adopt new technologies, and maintain productivity — while simultaneously managing uncertainty and organizational complexity.
Without new capabilities, the typical response is to increase control mechanisms: more reporting, more supervision, and more process.
Ironically, these responses often produce the opposite of their intended effect. Instead of increasing productivity, they generate additional friction and reduce team autonomy.
Effective leadership in the age of AI requires a fundamental shift in mindset. Managers must transition from task supervisors to architects of context — designing the conditions that enable teams to make effective decisions in complex environments.
This includes setting clear priorities, defining guardrails for AI usage, fostering psychological safety, and enabling distributed decision-making.
Rethinking the future of technology work
The transformation of technology work is not simply a technological shift — it is an organizational one.
AI does not eliminate complex cognitive work. Instead, it reconfigures it. The true constraints on productivity and innovation are increasingly found in operating models, leadership capabilities, and organizational design.
Organizations that succeed in this new environment will be those that create conditions where technology professionals can operate with clarity, autonomy, and trust.
Future competitive advantage will depend less on controlling work and more on enabling flow, learning, and collaboration.
In the age of artificial intelligence, the organizations that thrive will not be those trying to recreate the structures of the past, but those capable of building environments where people and technology evolve together.
Get to know how IT Workforce Transformation can help your organization build this capability, discover more at Netmind a BTS company
For more than a decade, Agile has played a central role in modernizing organizations. It improved collaboration, accelerated delivery cycles, and reshaped how teams build products and services.
However, Agile was never the final destination.
Scaling ceremonies does not redesign an organization. Implementing frameworks does not guarantee strategic adaptability. And in a world defined by exponential technological acceleration and artificial intelligence, improving execution alone is no longer sufficient.
Today, competitive advantage depends on something deeper: the ability to continuously adapt while still delivering value to customers.
This capability is known as Enterprise Agility.
Enterprise Agility as an organizational capability
Enterprise Agility is often misunderstood as a methodology or framework. In reality, it represents something far more fundamental.
It is the capability of an organization to generate sustainable value in uncertain environments through continuous adaptation of strategy, operating models, and culture.
Organizations with this capability are able to:
- Continuously prioritize the initiatives that generate the greatest impact
- Make faster and better-aligned decisions
- Reconfigure structures without major disruption
- Learn systematically from customers and market signals
- Integrate strategy and execution into a unified operating flow
When this capability becomes embedded within the organization rather than dependent on isolated initiatives, companies evolve into Adaptive Organizations.
But this evolution does not happen automatically. It requires activating structural change mechanisms across the enterprise.
The five levers that enable Enterprise Transformation
Enterprise Transformation is not about implementing Agile practices across teams. It is about building the capabilities required to sustain continuous adaptation.
Five structural levers play a critical role in enabling this transformation.
1. From methods to organizational design
For years, the conversation around agility focused on which framework to implement: Scrum, SAFe, LeSS, or Kanban.
Today, the more relevant question is different:
Is the organization designed to generate a continuous flow of value?
This shift requires moving beyond project-based structures toward operating models built around products, capabilities, and value streams.
Organizations must reduce structural friction and integrate strategy, execution, and learning into a single system.
Without this redesign, agility often remains superficial.
2. From rigid planning to continuous prioritization
Traditional annual planning cycles were designed for stable environments.
In today’s context, adaptive organizations manage dynamic portfolios and adjust priorities continuously based on real-time information.
Planning becomes an ongoing process rather than a yearly event.
Competitive advantage no longer comes from predicting the future better, it comes from the ability to adjust when the future changes.
3. From misaligned autonomy to distributed strategic coherence
Decentralization without alignment creates chaos. Excessive centralization creates slow decision-making.
Adaptive organizations balance these forces by enabling distributed decision-making within clear strategic guardrails.
Transparency, alignment, and shared accountability ensure that teams operate autonomously while remaining connected to the broader strategic direction.
4. From operational efficiency to accelerated learning
In the age of artificial intelligence, the speed of learning becomes more important than the speed of execution.
Organizations must build the ability to:
- Detect market signals early
- Understand strategic implications
- Experiment at low cost
- Learn systematically
- Adjust quickly
Artificial intelligence acts as a cognitive amplifier within this cycle, improving decision quality and enabling faster experimentation.
The objective is not simply to automate work, but to accelerate the organization’s adaptive capacity.
5. From change as a project to permanent adaptation
Many transformation initiatives fail because they are treated as temporary programs.
But adaptation is not a project, it is a strategic capability.
Organizations must integrate change into their daily operations by developing leadership capabilities, building adaptive cultures, and measuring real impact rather than superficial adoption metrics.
Transformation becomes a structural characteristic of the organization rather than an extraordinary initiative.
The real meaning of Enterprise Transformation
Agile was the first step, but it was never the destination.
Enterprise Transformation exists to build Enterprise Agility. And Enterprise Agility enables organizations to become truly adaptive.
In an environment where artificial intelligence accelerates innovation and lowers barriers to entry, stability is no longer a protection. Rigidity becomes a liability.
The critical question for organizations today is not whether they execute their plans efficiently.
It is whether they can change those plans faster than their competitors.
To understand how Enterprise Transformation can help your organization build this capability, discover more at Netmind a BTS company
Global spending on AI is forecast to reach $2.52 trillion by 2026, a 44% year-over-year increase, according to Gartner. At the same time, only about 10% of AI pilots scale beyond proof of concept.
What’s the disconnect?
Why aren’t most organizations seeing the ROI they hoped for, despite making such large investments?
It’s not because the technology isn’t ready. And it’s not because the use cases are unclear.
The disconnect exists because many organizations are investing in AI as a technology upgrade and expecting a business transformation in return.
The tools are advancing at breathtaking speed, and most organizations already have AI in motion. But the work itself often stays the same. AI gets layered onto existing tasks instead of being used to rethink workflows end to end. Adoption metrics go up, while decisions, operating models, and value creation remain largely untouched.
When teams first start using AI, they do what makes sense. They try to recreate today, just faster. Can it help me write this? Analyze that? Save a bit of time?
That’s a smart place to begin. But it’s not where ROI, or reinvention, actually shows up.
Getting over the hump
Real returns begin when teams experience what we often call “getting over the hump.”
This is the moment when two things click at once:
- AI can fundamentally change how work gets done.
- People don’t need deep technical expertise to make that change happen.
When teams see weeks of work compress into hours, or watch an end-to-end workflow suddenly run in a new way, something shifts. Confidence replaces hesitation. Curiosity replaces caution. The questions change, from “How do I use this tool?” to “What’s possible now?”
That shift matters, because ROI doesn’t come from using AI more often, it comes from using it to work differently.
Why ROI stalls as AI scales
As AI initiatives expand, many organizations discover that the limiting factor isn’t the technology itself. It’s the environment surrounding the work.
ROI shows up when teams are able to explore and redesign workflows, not just automate steps. That requires clarity on outcomes and guardrails, but also room to experiment, learn, and iterate. When AI is tightly controlled or narrowly deployed, pilots stay pilots. When people are trusted to rethink how work happens, value starts to compound.
Organizations that unlock ROI don’t chase perfect use cases upfront. They focus on learning faster and applying those insights where they matter most.
The early signal that ROI is coming
Long before AI shows up in financial results, there’s an earlier indicator that organizations are on the right path.
People are energized by the work.
You see it when teams start sharing experiments, when ideas move across functions, and when learning becomes visible rather than hidden. Progress feels owned, not imposed.
That energy isn’t accidental. It’s a signal that people feel trusted to rethink how work happens, and that trust is essential to turning investment into impact.
Reinvention happens closer to the work than most expect
AI reinvention rarely starts with a sweeping rollout or a multi-year roadmap. More often, it begins with one meaningful workflow, one team close to the work, and a willingness to ask a different question.
With the right support, that team gets over the hump. What they learn becomes reusable. Patterns emerge. Over time, those insights connect, creating enterprise-wide impact and sustained ROI.
That’s how organizations move from isolated pilots to real returns.
What this means for AI investment
No organization feels fully “caught up” with AI, and that’s true across industries.
The organizations that will realize ROI aren’t waiting for certainty or the next breakthrough tool. They’re reinvesting their AI spend into new ways of working that scale human potential alongside technology.
Handled thoughtfully, AI doesn’t distance people from the work. It brings them closer - to better decisions, stronger collaboration, and better outcomes.
For many organizations, that’s where the real return begins.
Technology choices are often made under pressure - pressure to modernize, to respond to shifting client expectations, to demonstrate progress, or to keep pace with rapid advances in AI. In those moments, even experienced leadership teams can fall into familiar traps: over-estimating how differentiated a capability will remain, under-estimating the organizational cost of sustaining it, and committing earlier than the strategy or operating model can realistically support.
After decades of working with leaders through digital and technology-enabled transformations, I’ve seen these dynamics play out again and again. The issue is rarely the quality of the technology itself. It’s the timing of commitment, and how quickly an early decision hardens into something far harder to unwind than anyone intended.
What has changed in today’s AI-accelerated environment is not the nature of these traps, but the margin for error. It has narrowed dramatically.
For small and mid-sized organizations, the consequences are immediate. You don't have specialist teams running parallel experiments or long runways to course correct. A single bad platform decision can absorb scarce capital, distort operating models, and take years to unwind just as the market shifts again.
AI intensified this tension. It is wildly over-hyped as a silver bullet and quietly under-estimated as a structural disruptor. Both positions are dangerous. AI won’t magically fix broken processes or weak strategy, but it will change the economics of how work gets done and where value accrues.
When leaders ask how to approach digital platforms, AI adoption, or operating model design, four questions consistently matter more than the technology itself.
- What specific market problem does this solve, and what is it worth?
- Is this capability genuinely unique, or is it rapidly becoming commoditized?
- What is the true total cost - not just to build, but to run and evolve over time?
- What is the current pace of innovation for this niche?
For many leadership teams, answering these questions leads to the same strategic posture. Move quickly today while preserving options for tomorrow. Not as doctrine, but as a way of staying adaptive without mistaking early commitment for strategic clarity.
Why build versus buy is the wrong starting point
One of the most common traps organizations fall into is treating digital strategy as a series of isolated build-vs-buy decisions. That framing is too narrow, and it usually arrives too late.
A more powerful question is this. How do we preserve optionality as the landscape continues to evolve? Technology decisions often become a proxy for deeper organizational challenges. Following acquisitions or periods of rapid change, pressure frequently surfaces at the front line. Sales teams respond to client feedback. Delivery teams push for speed. Leaders look for visible progress.
In these moments, technology becomes the focal point for action. Not because it is the root problem, but because it is tangible.
The real risk emerges operationally. Poorly sequenced transitions, disruption to the core business, and value that proves smaller or shorter-lived than anticipated. Teams become locked into delivery paths that no longer make commercial sense, while underlying system assumptions remain unchanged.
The issue is rarely technical. It is temporal.
Optimizing for short-term optics, particularly client-facing signals of progress, often comes at the expense of longer-term adaptability. A cleaner interface over an ageing platform may buy temporary parity, but it can also delay the more important work of rethinking what is possible in the near and medium term.
Conservatism often shows up quietly here. Not as risk aversion, but as a preference for extending the familiar rather than exploring what could fundamentally change.
Licensing as a way to buy time and insight
In fast-moving areas such as AI orchestration, many organizations are choosing to license capability rather than build it internally. This is not because licensing is perfect. It rarely is. It introduces constraints and trade-offs. But it was fast. And more importantly, it acknowledged reality.
The pace of change in this space is such that what looks like a good architectural decision today may be actively unhelpful in twelve months. Licensing allowed us to operate right at the edge of what we actually understood at the time - without pretending we knew where the market would land six or twelve months later.
Licensing should not be seen as a lack of ambition. It is often a way of buying time, learning cheaply, and avoiding premature commitment. Building too early doesn’t make you visionary, often it just makes you rigid.
AI is neither a silver bullet nor a feature
Coaching is a useful microcosm of the broader AI debate.
Great AI coaching that is designed with intent and grounded in real coaching methodology can genuinely augment the experience and extend impact. The market is saturated with AI-enabled coaching tools and what is especially disappointing is that many are thin layers of prompts wrapped around a large language model. They are responsive, polite, and superficially impressive - and they largely miss the point.
Effective coaching isn’t about constant responsiveness. It’s about clarity. It’s about bringing experience, structure, credibility, and connection to moments where someone is stuck.
At the other extreme, coaches themselves are often deeply traditional. A heavy pen, a leather-bound notebook, and a Royal Copenhagen mug of coffee are far more likely to be sitting on the desk than the latest GPT or Gemini model.
That conservatism is understandable - coaching is built on trust, presence, and human connection - but it’s increasingly misaligned with how scale and impact are actually created.
The real opportunity for AI is not to replace human work with a chat interface. It is to codify what actually works. The decision points, frameworks, insights, and moments that drive behavior change. AI can then be used to augment and extend that value at scale.
A polished interface over generic capability is not enough. If AI does not strengthen the core value of the work, it is theatre, not transformation.
What this means for leaders
Across all of these examples, the same pattern shows up.
The hardest decisions are rarely about capability, they are about timing, alignment, and conviction.
Building from scratch only makes sense when you can clearly articulate:
- What you believe that the market does not
- Why that belief creates defensible value
- Why you’re willing to concentrate risk behind it
Clear vision scales extraordinarily well when it’s tightly held. The success of narrow, focused Silicon Valley start-ups is testament to that.
Larger organizations often carry a broader set of commitments. That complexity increases when depth of expertise is spread across functions, and even more so when sales teams have significant autonomy at the point of sale. Alignment becomes harder not because people are wrong, but because too many partial truths are competing at once.
In these environments, strategic clarity, not headcount or spend, creates advantage.
This is why many leadership teams choose to license early. Not because building is wrong, but because most organizations have not yet earned the right to build.
This article was originally publish on Rotman Management
IN OUR CONSULTING WORK with teams at all levels—especially senior leadership—my colleagues and I have noticed teams grappling with an insidious challenge: a lack of effective prioritization. When everything is labeled a priority, nothing truly is. Employees feel crushed under the weight of competing demands and the relentless urgency to deliver on multiple fronts. Requests for prioritization stem from both a lack of focused direction and the challenge of efficiently fulfilling an overwhelming volume of work. Over time, this creates a toxic cycle of burnout, inefficiency and dissatisfaction.
The instinctive response to this issue is to streamline, reduce the number of initiatives, and focus. While this is a step in the right direction, it doesn’t fully address the problem. Prioritization isn’t just about whittling down a to-do list or ranking activities by importance and urgency on an Eisenhower Decision Matrix; it also requires reshaping how we approach work more productively.
In our work, we have found that three critical factors lie at the heart of solving prioritization challenges: tasks, tracking and trust. Addressing these dimensions holistically can start to address the root causes of feeling overwhelmed and lay the foundation for sustainable productivity. Let’s take a closer look at each.
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Client need
For a 175-year-old technology company, competitive advantage isn’t just built on technical innovation: it’s built on leaders who know how to get the best thinking from every person around them. That culture of drawing out ideas, developing people, and driving innovation through engaged teams had been a defining feature of the organization for generations. And it depended on having the right infrastructure to keep developing frontline leaders at scale.
In 2020, that infrastructure was disrupted. The COVID-19 pandemic forced the organization to pivot its in-person development to virtual almost overnight, risking the erosion of frontline leadership capability while simultaneously needing to navigate the broader shocks of the pandemic: supply chain volatility, shifting materials costs, and a workforce managing profound uncertainty.
Stalling frontline leadership development meant risking productivity, employee engagement, talent retention, job performance, and downstream impacts on quality and operating margin, at a moment when the organization could least afford it.
The question now was how to reimagine frontline leader development to equip thousands of global leaders to continue supporting their teams through disruption, and to ensure the next generation of managers could help their people do their best work under any conditions.
Solution
The client partnered with BTS to reimagine frontline leader development from the ground up, equipping leaders globally with the practical skills, tools, and mindset shifts needed to support their teams in doing great, innovative work.
The partnership began in 2019, and over five years has reached over 1,600 frontline leaders capturing 700+ documented behavior change actions. In 2022, BTS collaborated with the organization to refresh the program to reflect their evolving strategy and develop a sharper focus on supporting a culture of continuous improvement and innovation with coaching and feedback.
The blended program experience combined the following elements:
- Immersive leadership simulations: Scenario-based experiences placing leaders in realistic situations, surfacing Multiplier and Diminisher tendencies in real time and making the learning immediately personal and actionable
- Multipliers and Diminishers framework: A structured exploration of how leaders either amplify or diminish the intelligence of those around them, including specific “experiments” leaders could use to better understand their own leadership approaches
- Custom leadership frameworks: Including a structured, step-by-step process for having significant feedback conversations, a tool to understand and flex to communication preferences, and a coaching approach designed to help leaders guide team members toward their own solutions, building capability and long-term ownership.
- Structured application sessions — on-the-job practice components designed to bridge the gap between the program experience and day-to-day behavior, giving participants specific frameworks to apply immediately with their teams
- Peer networking and breakout groups — cohort-based learning that participants identified as a standout feature, both for deepening the learning and for building cross-functional relationships that extended beyond the program
- A commitment-capture platform integrated into the program to log participant actions and reinforce behavior change after the program ended; over 670 participant actions were captured across the program’s delivery
Throughout the program, leaders examined the impact of their own behaviors, recognizing where they were unintentionally diminishing their teams, and built new habits around challenging, creating space for mistakes and learning, listening, questioning, giving developmental feedback, and creating ownership. The feedback model gave participants a practical process for the positive and constructive conversations that actually change performance.
Results
More than 1,600 frontline leaders and individual contributors have participated in the program—the population closest to daily execution, quality, and operations. A recent impact study told a clear story about the effects of the program across participants:
100% of participants reported actively applying what they learned. 59% reported producing significant, measurable business impact, with concrete evidence to describe it.
The results weren’t theoretical. One engineering leader restructured how his team developed project plans, creating space for debate and ownership instead of coming in with the answer. His team exceeded their quality target by 10 percentage points and accelerated the project timeline by +4 months.
One production leader used the feedback model to coach a struggling supervisor and cascade the process across his entire leadership layer. His unit reached #1 performance in its division, improving a key quality KPI by more than 18% year-over-year. A department head with over a decade in leadership set new production records after learning to flex his communication style and draw out quieter team members. And a development lab supervisor used the program to clarify her leadership identity, earn a promotion, and coach her direct report to one as well.
The study also confirmed that when managers actively supported participants post-program, the likelihood of significant business impact increased substantially, shaping the organization’s next phase of reinforcement and cohort follow-up.
For an organization whose competitive advantage rests on the innovation and intelligence of its people, the program gave its leaders something technical training rarely delivers: the confidence, the tools, and the self-awareness to make everyone around them better.
Testimonials
“The program gave me greater confidence to try new things as a leader. It helped me realize what I do and what I don’t do.” - HR Leader
“The skills I learned in the training helped me be more efficient. It helped me do the right thing, right away.” - Production Manager
“Feedback is very important to create a positive environment; and how to [give] feedback is a specific skill I learned from this training and how to share constructive feedback.” - Production Leader
Client need
A large U.S.-based health insurance organization operating at the center of a complex national ecosystem had already made a serious investment in enterprise AI. Leadership was not experimenting at the edges. They were leaning in.
Capability and commitment existed across the organization, but unevenly. Some teams were already pushing boundaries. Others hadn't yet found their footing. Most of the gains had come in personal productivity. Valuable, but the core work itself had not yet fundamentally changed. The opportunity was to go deeper, to move from AI-assisted individuals to AI-reinvented workflows.
Across the health insurance landscape, pressure was intensifying. Medicaid and government program contracts were becoming more competitive. Decision cycles were faster and more analytics-driven. Clinical evidence was evolving rapidly. Regulatory scrutiny was high. Security risks were constant. AI was no longer a future conversation. It was a present expectation.
Inside the organization, world-class experts were still constrained by manual processes.
Specialized teams were synthesizing large volumes of complex, fast-moving information, working to keep pace with an environment where the inputs never stopped changing. The work required deep expertise and judgment, and it also demanded repetitive processing that consumed days when it needed to take hours.
Other teams faced pressure where speed and precision directly influenced competitive outcomes. Manual approaches were creating lag at exactly the moments when faster insight mattered most.
Across functions, the pattern was consistent. Highly trained professionals were spending valuable time on low-leverage tasks, stitching together data, transforming files, and correlating inputs that AI could handle.
Leadership understood that AI licenses alone would not create advantage. To compete in an increasingly analytics-driven insurance environment, expertise had to scale. Insight had to move faster. Teams needed to reinvent how core work happened.
Solution
BTS partnered with the organization to move from AI access to AI application.
Through a series of focused design sprints, intact teams worked on their highest-value workflows using our GROUNDING → EXPERIMENT → BUILD → AMPLIFY methodology. The structure was simple and disciplined. Set context. Experiment quickly. Build against real work. Create a path to scale.
Participants brought their actual work into the room. Analytical frameworks. Competitive and operational documents. Risk and intelligence inputs. Data pipelines.
No generic demos. No abstract hypotheticals.
The turning point came when AI began working on their actual content.
Research syntheses that previously took days began structuring themselves in minutes. Competitive analysis that once required manual review surfaced patterns instantly. Data transformation workflows streamlined in real time.
Skepticism shifted to possibility.
We positioned AI as augmentation, not replacement. In a sector defined by professional expertise and accountability, that framing was critical. The goal was to elevate expert judgment, not automate it away.
Some teams left with working prototypes. Others left with detailed blueprints aligned to enterprise privacy and security requirements. Another team took away a re-prioritized set of additional tools to incorporate into a HIPAA-compliant environment. Every team left with a redesigned workflow.
Results
In five days, more than 100 leaders advanced 30 priority use cases tied directly to operational performance and competitive growth.
Early outcomes included:
- Significant reduction in manual research synthesis and data preparation
- Faster, more structured competitive intelligence to support high-stakes decisions
- Clear implementation pathways aligned to security and regulatory constraints
- A scalable model for continued AI-enabled workflow reinvention
Just as important was the mindset shift.
Participants stopped viewing AI as a tool sitting outside their work and began treating it as embedded infrastructure for how work gets done.
“This showed immediate relevance to our work.”
“Now I understand what’s actually possible for my team.”
“We just accomplished in two hours what used to take us two months.”
In a U.S. health insurance market where insight, speed, and precision directly influence who wins and who grows, the organization moved decisively from AI access to AI advantage.
Client need
Safety in the transportation industry has often been treated as a set of rules to follow and boxes to check. But one Spanish railway organization saw an opportunity to redefine safety as something far greater, a core value embedded into the culture of their company at every level.
This bold vision demanded more than compliance. It required a cultural transformation to challenge outdated behaviors, inspire teams, and empower leaders to embrace and model a safety-first mindset. For years, the organization had been working to foster a culture that prioritized protection over profit, setting new behavioral standards across the industry.
To accelerate this shift, the organization partnered with BTS to design a leadership development program that dismantled old practices and equipped leaders with the tools, insights, and behaviors needed to bring their vision to life.
- Deconstruct existing mindsets to enable cohesive change.
- Identify barriers preventing progress.
- Equip leaders with practical behavioral knowledge and tools.
Solution
BTS partnered with the organization to design a leadership journey that would reshape not just processes but perspectives, fostering a workplace where physical and psychological safety were paramount. Over eight months, the project team conducted interviews with leaders and focus groups to uncover critical behavioral insights and tailor the program to the organization’s unique needs.
Participants explored essential themes, including:
- Embedding safety into daily decision-making.
- Cultivating greater awareness of safety risks.
- Understanding the influence of their leadership on safety outcomes.
- Leading by example to set a cultural standard.
- Building trust, commitment, and open communication within their teams.
The program unfolded in three distinct phases to drive lasting behavioral change:
- Workshop preparation
Participants began with a self-assessment to uncover personal “safety blind spots” and mind traps. This phase, delivered through a custom online platform, helped leaders reflect on their current practices and prepare for the transformational journey ahead.
- Safety workshop
The one-day, immersive workshop was designed to spark deep conversations about safety culture, challenge ingrained mindsets, and equip participants with actionable strategies for change. Leaders engaged in real-world scenarios to explore the implications of their decisions and practice new behaviors. The day concluded with collaborative debrief sessions, leaving participants with practical tools to implement their insights immediately. - Implementation in action
To sustain momentum, the post-workshop phase extended over six months, offering six targeted activities. These activities reinforced key lessons, encouraged team collaboration, and provided ongoing support for integrating safety-first behaviors into daily routines.
The leadership program was delivered to 1500 participants over 66 workshops in seven locations across Spain.
Results
To measure results, the project team created a resource map evaluating progress.
Average completion rate of Activities One–Three: 57 percent. (One: 78.21%; Two: 53. 01%; Three: 40.57%)
A post-workshop survey was sent to participants, reporting on the following metrics:
- Average satisfaction — 4.7/5.
- Trainer’s evaluation — 4.9/5.
- NPS — 82 percent.
- “Saw improvement in safety alignment” — 93 percent.
- “Integrated safety tools in daily roles” — 82 percent.
- “Identified new initiatives for improving safety” — 77 percent.
- “Mitigated team/peer mind traps” — 93 percent.
- “More aware of risk in daily roles” — 98 percent.
- “Identified a normalized risk to work on” — 92 percent.
Testimonials
- “Many of the methodologies and tools not only help to improve safety but can also be used to improve operational or organizational processes.”
- “It has put us in front of the mirror of how we are today in terms of safety culture, opening our eyes to our development areas. Very participative and practical.”
Over the years, BTS has expanded its global footprint through thoughtful acquisitions and collaborations, bringing new creative capabilities and local expertise into the fold. From digital design studios to leadership consultancies across Europe, Asia, and the Americas, we’ve built a community that blends shared values with local perspective. That diversity has become one of our greatest strengths, shaping how we design and deliver learning that feels deeply personal everywhere we work.
Whether someone is in a leadership journey in Singapore, a coaching program in São Paulo, or a strategy workshop in Stockholm, the goal is always the same: to make the experience feel like it was made just for them.
Many of those experiences live on Momenta, BTS’s digital experience platform, powering journeys like Coaching, Multipliers, and other core programs.
As those experiences grew, so did the need for nuance. Every journey had to feel local, not just sound translated. Tone, humor, and cultural context have always been central to the BTS approach, and as demand expanded across formats and regions, our translation model was ready for its next evolution.
In early 2024, the team began exploring how AI could help. Rather than treating technology as the destination, we saw it as a catalyst, a way to rethink translation and deliver richer, more customized client experiences at scale. That curiosity sparked one of BTS’s most ambitious AI-first experiments, led by our Global Product Enablement Function team in partnership with our global network of linguists and translators.
Shifting to AI-first
The next step was finding the right place to experiment. Enter Phrase, a cloud-based translation management platform that quickly became our test lab. Phrase brings every part of the translation process into one place, from machine translation engines to human review, terminology management, and workflow tracking. It gives our linguists, designers, and project teams a shared space to collaborate, test ideas, and learn.
Over the next few months, two key discoveries reshaped how we think about translation, and ultimately, how we work.
Key discovery 1: Making AI a teammate
We began with a clear goal: make translation faster and more consistent. Using Phrase, AI handled the first drafts while our linguists refined them. Quickly, we realized there was potential for AI-value that went far beyond speed.
With AI completing the first 80% of the work in a fraction of the time, our linguists could focus on what matters most: nuance, tone, and cultural resonance. The relationship evolved from oversight to collaboration, AI structured and scaled, humans shaped and elevated.
The result was more than efficiency. It was better work, created by people and technology learning to amplify each other.
Key discovery 2: Turning a roadblock into a redesign
Next came a design challenge. Phrase, like most translation tools, struggled with text embedded in graphics, a hallmark of many BTS learning experiences. Instead of forcing the tool to adapt, we changed how we created.
We began designing with translation in mind: simplifying visuals, reducing text, and using modular components that could flex across languages. The constraint sparked better design, easier to scale, more consistent, and more inclusive for every audience.
Key discovery 3: Integrating systems for scale
With people, AI, and design in sync, the last barrier was process. Managing translations between Phrase and Momenta still required manual effort.
To fix that, we built an API integration linking the two platforms. Now, files move automatically, progress is tracked in real time, and everything stays connected.
That integration turned our workflow into a unified ecosystem, fast, transparent, and ready to scale globally.
Business impact
Just 18 months ago, our translation reviews lived in double-column Word docs. Today, we work in a fully connected, AI-first ecosystem. Each project feeds the next, refining prompts, tone profiles, and design patterns, so our translation process keeps getting faster, smarter, and more aligned with BTS’s voice.
Speed and quality. Translation cycles that once took months now wrap up in weeks, cutting turnaround times by over 40%. Phrase’s tools and AI-powered workflows accelerate production while maintaining quality through expert-approved reuse, glossaries, and automated quality checks. Even complex formats like videos and animations are localized faster, with AI supporting linguists at every step.
Smarter workflows. The integration between Momenta and Phrase automates project transfers and tracking, saving an estimated 2.5 hours per project. Teams across language, digital, and project management now collaborate in one streamlined environment.
Human focus. Our linguists remain the engine of quality and innovation. With AI managing repetitive tasks, they focus on nuance and meaning, and go further by creating specialized GPTs, training databases, and testing translation engines to continually raise the bar.
When BTS invented business simulations in the 1980s, leadership development was mostly theoretical – case studies, lectures, and frameworks about what good decisions looked like. Simulations changed that. They let leaders learn by doing, stepping into a realistic version of their business to test strategy, make decisions, and see the impact before the stakes were real.
Since then, simulations have evolved from spreadsheets to digital platforms to immersive virtual experiences that capture the complexity of leading in today’s world. Now, large language models and agentic AI are opening a new frontier, one where simulations evolve as fast as the world they reflect and experiential learning scales with the pace of change.
Creating space for exploration
Test quickly, abandon what doesn’t work, and share what you learn.
– Jessica Skon, CEO, BTS
A handful of simulation experts were pulled out of their day-to-day work and given the freedom to set their own direction. They had the authority to shape the roadmap and the protection to explore bold ideas without fear of critique. The brief was simple: go figure out what’s possible.
They had cover to fail fast, freedom to explore, and permission to get a little messy. Early wins were interesting but small. AI could draft faster, automate a few things – helpful, sure. Transformative? Not yet.
The breakthrough came when we stopped trying to bolt AI on to what we already did. We rebuilt our simulation platforms, our processes, and tools from the ground up around AI. Suddenly it wasn’t just about micro-gains & efficiencies, the canvas of possibility was much larger.
From experimentation to acceleration
So, we tested. Some tools showed promise, others, not so much. Every experiment taught us something. Each “failure” made us sharper about where AI could actually help, and where it would just get in the way.
What began as small experiments turned into a new way of working, a process and platform working as one.
AI now accelerates the first 80% of the work, the structure, synthesis, and early drafts, freeing BTS consultants to focus on the high-impact moments that drive behavior change: dilemmas, trade-offs, and conversations that build conviction.
Our new AI simulation platform and AI-First development process operationalizes that process:
- Enabling live co-creation and branching edits with clients
- Applying light guardrails for quality and security
- Integrating with enterprise systems for compliance and control
AI accelerates, people transform. That combination is what makes BTS… BTS.
Clients feel the impact in four ways
- Fast spin-ups for focused needs
For targeted challenges like coaching a customer conversation, debriefing a safety incident, aligning a sales team, we can now stand up bespoke simulations in days, not weeks. Teams co-create live; scenarios adjust in the room; relevance is immediate. - Enterprise simulations for strategy alignment
For multi-round, high-fidelity simulations, AI accelerates the structure without compromising quality. BTS experts still craft the dilemmas and trade-offs that drive conviction. - A broader platform portfolio
Beyond enterprise simulations, we now support conversational practice, skill drills, workflow redesign, and company or market modeling, helping clients choose the right tool for each need. - On-demand, without the risk
Clients can use our AI platform for self-authored micro-sims, where speed and iteration matter most. Our toolchain scaffolds the flow, enforces guardrails, and keeps quality high.
The best model is flexible: enable where DIY shines, co-build for complex challenges, and experts lead end-to-end when outcomes matter most.
What clients are already seeing
- Weeks to hours: Work that once took six weeks was delivered as a high-fidelity experience in just 13 hours, specific enough to engage a CEO on first pass.
- Lean, agile teams: Projects that required seven consultants now take two, with no loss in quality or impact.
- Live collaboration: Simulations are built with clients, not for them, adjusted in real time during design and delivery.
The result: faster delivery, deeper relevance, and experiences that scale across an enterprise without losing the human touch.
The bigger picture
BTS simulations have always given leaders a safe place to wrestle with real dilemmas. AI hasn’t changed that, it’s expanded the canvas. By rebuilding how we design and deliver simulations, we’ve removed the trade-off between speed and substance.
Focused needs can now be met in days. Complex transformations can move at the pace of business. Clients can engage however they choose, DIY, co-create, or end-to-end, with BTS expertise guiding every step.
We’re still early in this chapter, just like our clients. But the direction is clear: faster, smarter, more scalable experiential learning, anchored in human judgment, strategic alignment, and the craft that defines BTS.
Client need
A leading global media company, serving audiences in 170+ countries, had built its reputation on delivering high-quality content through a vast network of regional operations. With over 20,000 employees, its business relied on leaders at every level making fast, effective decisions in their markets while staying aligned to global strategy.
The company saw an opportunity to better support new leaders joining the organization globally and seasoned leaders seeking additional development opportunities, focusing on those responsible for bringing strategy to life every day.
To bridge that gap, the company set out to pilot a scalable leadership coaching program focused on:
- Building six leadership capabilities critical to business success
- Creating consistency across regions while respecting cultural and language nuance
- Measuring progress at individual, regional, and organizational levels
- Enabling development that lasts beyond the coaching engagement
The goal: strengthen alignment and elevate leadership impact across North America, Europe, the Middle East, Africa, and the Asia–Pacific region.
Solution
The challenge wasn’t just delivering coaching, it was creating a leadership development system that could work across continents, prove its impact, and adapt to local realities without diluting global priorities.
The company partnered with Sounding Board, a BTS company, to design a pilot that blended human expertise with scaled, tech-enabled insight to meet four imperatives:
- Activating frontline and mid-level leadership – Focused on people leaders who directly shape day-to-day execution and culture.
- Building the capabilities that matter – Six leadership behaviors rooted in the company’s unique culture, values, and strategic operating principles, ensuring development was relevant to how leaders drive success within the organization.
- Ensuring quality at scale – AI-driven matching connected each leader to a coach with relevant industry, regional, and cultural experience.
- Making growth measurable and sustainable – Biweekly coaching reinforced through a digital platform for goal tracking, reflection, and feedback, plus structured manager check-ins to keep progress aligned to business needs.
Scaled coaching gave the company a consistent platform and approach to leadership development, developing leaders in every region to the same leadership expectations and behaviors. Real-time insights surfaced trends in behavior change, engagement, and alignment early enough to adjust the program midstream. The data struck the right balance between consistency and cultural relevance, showing where local adaptations strengthened leadership and where global priorities needed to hold firm.
Results
By the end of the program, leaders across continents were working from the same playbook, speaking a shared leadership language, and working in ways that respected local context and in alignment to how they wanted leaders to show up in the organization. Managers noticed stronger alignment with their direct reports, leaders felt more confident in their roles, and the data showed tangible shifts in the behaviors tied to business success.
Impact at a glance:
- 84% completion rate demonstrated sustained engagement.
- 92% of coachees advanced their development goals, with nearly as many showing measurable improvement in targeted leadership behaviors.
- 84% of coachees and 64% of managers reported stronger alignment in how they approached priorities and collaboration.
- 76% of leaders progressed toward broader career goals, signaling a stronger leadership pipeline.
- 87% satisfaction rate with coaching, reinforced by a 95% coach match success rate.
- 30% of coachees reported increased job satisfaction—critical in a competitive talent market.
What’s next:
The company expanded coaching to 50+ additional team leaders and began planning its rollout to mid-level managers worldwide, confident they have a model that delivers measurable growth, alignment, and cultural agility at scale.
Testimonials
“I have seen [my report] take it to another, more strategic level, particularly as she engages with her senior stakeholder. She spent time reflecting on what she wanted to get out of their first meeting, how to present herself as his new partner, what kind of questions would solicit the most meaningful responses etc.” — Senior Manager
“[My report] increased her capacity to appreciate the views of others and to work to develop them. She expanded her horizons to think outside of her comfort zones and to draw out some fine work from others. She showed improved capacity to help others develop their own ideas, rather than imposing her own on them.” — Senior Manager
“[Coaching] has helped me have a better understanding of where I enjoy working and developing most so I can continue to do so.” — Coachee
Client need
By 2024, artificial intelligence was transforming how medical devices industry operated, from product design and manufacturing to clinical insight and customer engagement. Competitors were already using AI to shorten development cycles, improve quality, and bring smarter devices to market faster. Startups were pushing the boundaries even further.
For one Fortune 100 global medical devices company, the question wasn’t if they would use AI, but how fast and how deeply they could make it part of the business. Like many organizations in this space, they saw enormous promise, but also the practical challenges that come with scale, regulation, and change.
The leadership team saw the potential for AI to transform how the business worked, yet progress was uneven. Teams held different views of what AI could do, and early experiments surfaced concerns about data privacy, accuracy, and safety. Many employees weren’t sure how AI fit into their day-to-day work or how to use it responsibly.
To move forward, the company needed to focus on a few critical shifts:
- Tackling questions and concerns at every level of the organization
- Creating a shared understanding of where and how AI drives value
- Helping leaders translate AI strategy into meaningful action with their teams
That’s where BTS came in.
Solution
To accelerate transformation at scale, BTS designed a phased capability-acceleration program that met leaders where they were, building confidence, speed, and AI fluency across the enterprise through immersive, business-driven experiences.
Tailored by leadership level
From executives shaping enterprise strategy to directors driving operational execution, each audience experienced targeted challenges and decision contexts that made AI real and relevant to their work.
Global alignment
A multilingual, virtual rollout enabled simultaneous engagement of thousands of employees worldwide, ensuring speed, consistency, and measurable impact across regions.
Continuous evolution
Regular refresh cycles kept the experience aligned to the company’s advancing AI maturity, embedding adaptability and readiness as ongoing capabilities.
Wave 1: Executive immersion
Audience: Senior leadership | Format: Live, in-person
The journey started with the top 100 leaders reimagining how AI could power growth and innovation. In an immersive, board-based simulation, executives pressure-tested new business models, explored disruptive use cases, and made high-stakes decisions with AI in real time.
By “taking the future for a test drive,” they moved past abstract discussions and directly experienced how AI could:
- Accelerate time to insight
- Sharpen strategy and decision quality
- Unlock new sources of business and customer value
The group left with a defined vision and roadmap for putting AI to work, where it adds value, how it changes leadership decisions, and what to prioritize first. It also helped leaders address their early concerns about reliability and safety together, building collective confidence to lead the change.
Wave 2: Director activation
Audience: ~300 directors globally | Format: Live workshops
Next came the catalyst for scale. Directors translated the executive vision into practical, measurable action through fast-paced, hands-on simulations built around their toughest business challenges.
They didn’t just learn about AI, they used it. In realistic decision scenarios, directors practiced how to:
- Ask sharper, data-driven questions
- Interpret insights and balance human judgment with machine input
- Identify opportunities to automate, innovate, or reimagine workflows
- Treat AI as a trusted performance partner, not just a technical tool
Each director left with a concrete activation plan, tailored to their function, and the confidence to lead change from the middle.
Wave 3: Global rollout
Audience: ~13,000 employees | Format: Virtual, multilingual, concurrent delivery
Finally, the transformation went enterprise-wide.
Through a high-energy, virtual experience, more than 13,000 employees across all regions and functions built shared confidence and capability to use AI in real work.
The experience made AI tangible for every role, from marketing and R&D to manufacturing and commercial teams. Participants discovered how small, real-world applications could:
- Simplify everyday tasks
- Drive smarter, faster decisions
- Deliver immediate business impact for teams and customers
Results
While quantitative metrics such as revenue impact or cycle-time reduction are still emerging, qualitative outcomes point to faster adoption, stronger engagement, and immediate business applications.
“The session was great. My team was inspired. They quickly got the foundations, and many of them actually went out that night and came back the next day with applications and output that we can put to work almost immediately.” – Senior Vice President of Marketing, September 2024
The momentum continues. BTS and the client are expanding the program into a scalable system for agility that keeps pace with the business. New sessions and scenarios are built into daily work, giving leaders and teams ongoing opportunities to apply AI in real decisions.
Client need
A leading global aluminum manufacturer faced a pivotal challenge: how to create a unified, empowered workforce in a highly decentralized organization. Each business unit operated autonomously, making it difficult to align global learning with local needs. The company recognized the need for enterprise-wide development programs that supported its business and HR strategies while preserving local flexibility.
To meet this challenge, the organization launched a Corporate Learning University—a multi-year initiative to transform its approach to employee development. BTS collaborated with HR and L&D leaders to co-create a comprehensive portfolio of programs tailored to different roles and career stages across the enterprise.
Solution
The transformation began with a clear vision: align learning with strategic outcomes to unify and empower a decentralized workforce. BTS worked with the company to create an impact map linking business priorities—financial performance, safety, and employee engagement—to the behaviors and skills required at each level of the organization.
The map established three key learning objectives:
- Foster unity and collaboration across a decentralized structure.
- Strengthen business acumen to improve contribution and decision-making.
- Build a shared leadership identity aligned with company values.
Using these objectives as a foundation, BTS and the client designed programs for every stage of the employee journey.
For mid-level leaders, a nine-month Leadership Development Program combined two in-depth workshops with an online learning journey:
- Leading Self: Introduced Liz Wiseman’s Multipliers framework, enabling leaders to expand their teams’ capacity through role-plays and practical exercises.
- Leading the Business: A three-day custom business simulation where participants acted as CEOs, balancing profitability, safety, and customer satisfaction across simulated fiscal years.
The learning ecosystem expanded beyond mid-level management to include: Frontline leader training focused on operational excellence and people management.
Executive development sessions designed for senior leaders to strengthen strategic alignment and culture building.
By embedding strategy directly into every program, the company built a cohesive, enterprise-wide learning culture that reinforced leadership capability, collaboration, and business impact.
Results
The co-created programs delivered measurable, strategic outcomes across safety, engagement, and financial performance.
Key results included:
- Financial performance: Optimized production schedules and reduced inventory, improving cash flow.
- Operational efficiency: Empowered managers to focus on asset utilization and controllable budget items.
- Cultural transformation: Embedded the Multipliers framework to drive collaboration, daily CapEx reviews, and safety-oriented onboarding for new hires.
- Leadership excellence: Increased coaching and feedback frequency, improving communication and alignment across teams.
These initiatives not only elevated employee engagement but also positioned the company as an industry leader in workplace culture and performance.
By integrating business and HR strategy into a unified learning ecosystem, BTS helped the manufacturer achieve its vision of becoming the most exciting place to work and invest—demonstrating the power of tailored, results-driven leadership development.
Client need
A global engineering organization with a 170-year legacy of innovation had long thrived by evolving—advancing technology, entering new markets, and solving complex industrial challenges at scale.
As the pace of change accelerated—driven by new technologies, shifting customer expectations, and growing sustainability demands—the leadership team faced a critical realization: technical expertise and operational excellence alone were no longer enough. To succeed in a fast-moving world, the company needed a culture rooted in accountability, collaboration, and adaptability.
Leaders saw the opportunity to strengthen the bridge between strategy and execution by embedding consistent leadership behaviors across 15,000 employees, four divisions, and 50+ countries. The goal was to weave these behaviors into everyday decision-making, team interactions, and change leadership—preparing the business for its next era of growth.
Solution
BTS partnered with the organization to embed this cultural transformation across all levels of the business. The initiative began with a discovery process involving 20+ stakeholder interviews, dozens of employee focus groups, and analysis of culture and engagement data. This uncovered both the organization’s existing strengths and the barriers holding back consistent leadership behaviors.
These insights informed a multi-phase transformation journey—starting small, then scaling intentionally. The first step was an immersive, digital-first leadership development experience for a pilot group of 100 senior leaders. Hosted on a custom learning platform, the experience balanced global consistency with local relevance and helped leaders model the culture they sought to create.
Key elements included:
- Immersive learning modules featuring videos, real-world simulations, and interactive exercises based on the company’s business context.
- Instructor-led workshops emphasizing high-impact behaviors, change leadership, and collaboration—creating a clear connection between strategy and execution.
- Peer pods and action labs that encouraged accountability, community, and the practical application of new habits.
- Activation tools such as behavioral dictionaries, meeting-in-a-box resources, and ambassador toolkits to help cascade the culture shift throughout the business.
To ensure momentum, selected pilot participants were trained as internal facilitators—empowering them to lead sessions, coach peers, and champion the desired culture from within.
Results
The program gained rapid traction, sparking a shift toward shared accountability and adaptive leadership.
Leaders reported:
- High engagement and relevance of the experience (average score: 3.63/4)
- Strong facilitation and safe spaces for reflection (3.81/4)
- Clearer understanding and application of desired leadership behaviors (3.61/4)
Follow-up engagement surveys showed that the new leadership behaviors ranked among the top five most recognized organizational shifts, signaling early success in the transformation effort.
The organization continues to invest in expanding the initiative, viewing an adaptive, behavior-led culture not as a one-time project but as an enduring capability for navigating complexity and driving long-term success.
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Jessica Skon Named a Top 25 Consulting Firm CEO of 2025
BTS proudly announces that Jessica Skon, President and CEO, has been named one of The Top 25 Consulting Firm CEOs of 2025 by The Consulting Report.
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BTS was recently recognized as a Top 20 Assessment and Evaluation Company in 2025 by Training Industry, Inc.
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