Strategy isn’t set anymore. It’s adapted.

In today’s business environment, strategy no longer unfolds neatly from vision to execution. Disruption is constant, complexity is accelerating, and expectations are shifting in real time. In this context, strategy that is overly scripted becomes brittle. The organizations that thrive today are the ones that have learned to improvise. Not reactively, but with intention, agility, and confidence. To many executives, the idea of “strategy improv” might sound risky or chaotic. In truth, great improvisation is neither. It is a learned discipline rooted in presence, trust, and adaptability. It is what enables teams to respond purposefully in the face of the unexpected. And it is quickly becoming a core leadership capability for our times.

Why strategy needs to shift

For decades, the dominant model of strategy has been based on control. A select few defined the vision, cascaded goals through layers of the business, and expected execution to follow. Success was measured by fidelity to the plan. The world no longer works that way. Markets are volatile. We are in a technology super cycle. Customer needs evolve faster than product roadmaps. And the economic, geopolitical, and environmental future is increasingly uncertain. Rigid strategies struggle to survive this level of flux. They become outdated before implementation begins. Worse, they force teams into patterns of execution that ignore emerging data, evolving context, or untapped insight. What is needed now is not more precision. What is needed is more adaptability.

Strategy as intention, not prescription

In improvisational terms, a strategic plan is no longer a fixed script. It is a shared intention. It is a direction, not a destination. It is a compass, not a map. The core strategic question is no longer, “What is our five year plan?” but instead: “How do we respond wisely, quickly, and collectively to whatever emerges in service of our purpose?” This does not mean abandoning structure or discipline. In fact, it demands more of both. But the emphasis shifts from defining every move in advance to cultivating the conditions where people can make smart decisions in the moment. Here is the distinction:

• A goal says: “We will grow 17 percent in revenue.”

• An intention says: “To grow 17 percent, we will delight our clients, grow our impact, and operate with excellence to unlock long term value.”

The first is measurable. The second is both meaningful and measurable. And it is meaning that enables action when the path becomes unclear.

What improv really means

Improv in business is ripe for misunderstanding. It is not winging it or hoping for the best. Great improv is highly disciplined. It is grounded in preparation, presence, and shared principles. Here are a few improv principles that matter most for leaders and teams:

• Yes, And… Build on what is already in motion instead of shutting it down. That is how momentum grows.

• Make Your Partner Look Good. Execution is collective. Leaders who elevate others create trust and shared ownership.

• Be Present. You cannot rely on what worked yesterday or predict what comes tomorrow. Execution happens in this moment.

• Listen for What Is New. Do not just confirm your beliefs. Notice weak signals, dissenting voices, and emerging shifts.

• Commit to the Scene. Once you step in, go all in. Half-hearted execution drains energy and derails progress.

These are not stage tricks. They are everyday disciplines for how leaders and teams show up together when the path is not clear.

The boundary: What can and cannot be improvised

Not everything can or should be improvised. You cannot spin up a new factory in six weeks or redo a regulatory filing on the fly. Capital projects, infrastructure, hiring pipelines, and compliance require structure, discipline, and lead time. Within those guardrails, much of execution is improv. The actions and moves you make can and show flex with the need and the moment. Such moves might include:

• How you respond to a customer this week

• How you redeploy resources when a competitor surprises you

• How you adjust product features in response to early user feedback

The art is knowing the difference. Improv lives inside the boundaries, not outside them. And that is where the advantage lies.

We know it works

We have already seen this in action. During COVID, strategy as improv was not optional. Plans dissolved overnight. Leaders had to pivot in real time, trust their teams, and reimagine value on the fly. Many succeeded, not because they had the perfect plan, but because they had the capacity to improvise. Consider two everyday situations:

• Telecommunications company: With hardware and software tightly linked, this company faced constant tension between short-term changes in a release and the permanence of installed infrastructure. By learning to improvise in the short term with software while anchoring their long-term vision in hardware roadmaps, they delivered quick wins without derailing future value. To do so, leaders had to abandon siloed “hardware first” or “software first” thinking and live in both worlds at once.

• Global manufacturer: Preparing for volatility in regulation and transportation, this company had shifted to thinking of its manufacturing footprint as a portfolio of capabilities rather than fixed plants. When sudden shifts hit sooner than expected, they could improvise quickly, rebalancing capacity across countries, not because they were ready but because they had already rehearsed some of the moves. The adjustments were urgent, but they felt planful.

These are not exotic cases. They are reminders that when strategy execution meets reality, it is the organizations that can improvise with purpose that thrive.

From plans to response

The core strategic question has changed. It is no longer, “What is our five year plan?” but instead: “How do we respond wisely, quickly, and collectively to whatever emerges?” Capacity, creativity, and commitment to the purpose and intention of the strategy, not certainty, are now the keys to competitive advantage. Those attributes are built through people: their judgment, their alignment, and their ability to act in service of shared priorities.

How to build strategic improv into your organization

Improv is not just an individual skill. It is an organizational capacity. Here are five practical ways to embed it into how your teams work:

1. Ground the organization in purpose and priorities. Make sure everyone knows the “why” behind your strategy. Not just the outcomes you are chasing, but the value you aim to create. Purpose creates the throughline that allows teams to improvise without drifting.

1. Build enterprise perspective at all levels. Give people visibility into how their choices affect the whole. When teams understand upstream and downstream impacts, they act with greater confidence and coordination.

1. Normalize adaptation, not perfection. Shift the narrative from flawless execution to responsive evolution. Celebrate learning, reward and highlight intelligent risk taking, and treat change as a constant, not a crisis.

1. Practice collective sensemaking. Create space for cross functional conversation, reflection, and signal sensing. Encourage teams to bring forward what they are noticing, not just what they are reporting.

1. Train for improvisation. Just as improv actors practice, so can your leaders. Build their capacity to navigate ambiguity, connect dots, and co-create solutions in real time. The payoff is not just agility. It is resilience.

Final thought

Strategy execution today is less about control and more about capability. It is less about knowing the answers and more about creating the conditions where your people can discover the right answers for now, together. Companies that thrive in uncertainty will not be the ones with the tightest plans. They will be the ones that can improvise with purpose, with confidence, and with each other. When the world will not wait, improv is not optional. It is the new strategic advantage.

In the 1990s, Business Process Reengineering (BPR) was the Big Bet. Companies launched tightly controlled pilot programs with hand-picked teams, custom software, and executive backing. The results dazzled on paper.

But when it came time to scale? Reality hit. People weren’t ready. Systems didn’t connect. Budgets dried up. The pilot became a cautionary tale, not a blueprint.

We’ve seen this before with Lean, Agile, even digital transformations. Now it’s happening again with AI, only this time, the stakes are different. Because we’re not just implementing a new solution, we’re building into a future that’s unfolding. Technology is evolving faster than most organizations can learn, govern, or adapt right now. That uncertainty doesn’t make transformation impossible, but it does make it easier to get wrong.

And the dysfunction is already showing up, just in two very different forms.

Two roads to the same cliff

Today, we see organizations falling into two extremes. Most companies are either overdoing the control or letting AI run wild.

Road 1: The free-for-all

Everyone’s experimenting. Product teams are building bots, prompting, using copilots. Finance is trying automated reporting. HR has a feedback chatbot in the works. Some experiments are exciting. Most are disconnected. There's no shared vision, no scaling pathway, and no learning across the enterprise. It’s innovation by coincidence.

Road 2: The forced march

Leadership declares an AI strategy. Use cases are approved centrally. Governance is tight. Risk is managed. But the result? An impressive PowerPoint, a sanctioned use case, and very little broad adoption. Innovation is constrained before it ever reaches the front lines.

Two very different environments. Same outcome: localized wins, system-wide inertia.

The real problem: Building for optics, not for scale

Whether you’re over-governing or under-coordinating, the root issue is the same: designing efforts that look good but aren’t built to scale.

Here’s the common pattern:

• A team builds something clever.
• It works in their context.
• Others try to adopt it.
• It doesn’t stick.
• Momentum dies. Energy scatters. Or worse, compliance says no.

Sound familiar?

It’s not that the ideas are flawed. It’s that they’re built in isolation with no plan for others to adopt, adapt, or scale them. There’s no mechanism for transfer, no feedback loops for iteration, and no connection to how people actually work across the organization.

So, what starts as a promising AI breakthrough (a smart bot, a helpful copilot, a detailed series of prompts, a slick automation) quietly runs out of road. It works for one team or solves one problem, but without a handoff or playbook, there’s no way for others to plug in. The system stays the same, and the promise of momentum fades, lost in the gap between what’s possible and what’s repeatable.

We’ve seen this before

These aren’t new problems. From BPR to Agile, we’ve learned (and re-learned) that:

• Experiments are not strategies. Experiments show potential, not readiness for adoption. Without a plan to scale, they become isolated wins; interesting, but not transformative.
• Culture is the operating system. If the beliefs, behaviors, and incentives underneath aren’t aligned, the system breaks, no matter how advanced the tools.
• Managers matter. Without their ownership and support, change stalls.
• Behavior beats code. Tools don’t transform companies. People do.

Design thinking promised to bridge this gap with user-driven iteration and empathy. But in practice? Most efforts skip the hard parts. We tinker, test, and move on, without ever building the conditions for adoption.

AI and the new architecture of work

Many organizations treat AI like an add-on—as if it’s something to bolt onto existing systems to boost efficiency. But AI isn’t just a project or a tool; it changes the rules of how decisions are made, how value is created, and what roles even exist. It’s an inflection point that forces companies to rethink how work gets done.

Companies making real progress aren’t just chasing use cases. They’re rethinking how their organizations operate, end to end. They’re asking:

• Have we prepared people to reimagine how they work with AI, not just how to use it?
• Are we redesigning workflows, decision rights, and interactions—not just layering new tech onto old routines?
• Do we know what success looks like when it’s scaled and sustained, not just when it dazzles?

If the answer is no, whether you’re too loose or too locked down, you’re not ready.

The mindset shift AI demands

AI isn’t just a tech rollout. It’s a mindset shift that asks leaders to reimagine how value gets created, how teams operate, and how people grow. But that reimagination isn’t about the tools. The tools will change—rapidly. It starts with new assumptions, new stances, and a new internal leader compass.

Here are three essential mindset shifts every leader must make, not just to keep up with AI but to stay relevant in a world being reshaped by it:

1. From automation to amplification

Old mindset: AI automates tasks and cuts costs.

New mindset: AI expands and amplifies human potential, enhancing our ability to think strategically, learn rapidly, and act boldly. The question isn’t what AI can do instead of us, but what it can do through us—helping people make better decisions, move faster, and focus on higher-value work.

2. From efficiency to reimagination

Old mindset: How can we use AI to make current processes more efficient?

New mindset: What would this process look like if we started from zero with AI as our co-creator, not a bolt-on?

3. From implementation to opportunity building

Old mindset: Roll out the tool. Train everybody. Check the box.

New mindset: AI fluency is a core human capability that creates new realms of curiosity, sophistication in judgment, and opportunity thinking. Soon, AI won’t be a one-time training. It will be part of how we define leadership, collaboration, and value creation.

From sparkles to scale

In most organizations, the spark isn’t the problem. Good ideas are everywhere. What’s missing is the ability to translate those isolated wins into something durable, repeatable, and enterprise-wide.

Too many pilots are built to impress, not to endure. They dazzle in one corner of the business but aren’t designed for others to adopt, adapt, or sustain. The result? Innovation that stays stuck in the lab—or dies.

Designing for scale means thinking beyond the “what” to the “how”:

• How will this spread?
• What behaviors and systems need to change?
• Can this live in our whole world, not just my sandbox?

It’s not about chasing the next use case. It’s about setting up the conditions that allow innovation to take root, grow, and multiply, without starting from scratch every time.

Here’s how to make that shift:

1. Test in the wild, not just in the lab

Skip the polished demo. Put your solution in the hands of real users, in real conditions, with all the friction that comes with it. Use messy data. Invite resistance. That’s where the insights live, and where scale begins. If it only works in ideal settings, it doesn’t work.

2. Mobilize managers

Executives sponsor. Front lines experiment. But it’s team leaders who connect and spread. Equip them as translators and expediters, not blockers. Every leader is a change leader.

3. Hardwire behaviors, not just tools

The biggest unlock in AI is not the model—it’s the muscle. Invest in shared language, habits, and peer learning that support new ways of working. Focus on developing behaviors that scale, such as:

• Change readiness: the ability to spot opportunity, turn obstacles into possibilities, and help teams pivot.
• Coaching: getting the best out of your AI “co-workers” just like human ones.
• Critical thinking: applying human judgment where it matters most—context, nuance, and ethics.

4. Align to a future-state vision

To scale beyond one-off wins, people need a shared sense of where they’re headed. A clear future-state vision acts as an enduring focus, allowing everyone to innovate in concert. That alignment doesn’t stifle innovation. It multiplies it, turning a thousand disconnected pilots into a coherent transformation.

5. Track adoption, not just “wins”

Don’t mistake a shiny, clever prompt for progress. A great experiment means nothing if it can’t be repeated by many people. From day one, design with scale in mind: Can this be adopted elsewhere? What would need to change for it to work across teams, roles, or regions? Build for transfer, not just applause.

The real opportunity

AI will not fail because the tech wasn’t good enough. It will fail because we mistook experiments for solutions, or because we governed innovation into paralysis.

You don’t need more control. You don’t need more chaos. You need design for scale, not just scale in hindsight.

Let’s stop chasing sparkles. Let’s build systems that spread.

Today, change isn’t just constant—it’s compounding.

AI is reshaping roles. Supply chains remain volatile. Customer expectations evolve faster than annual planning cycles can keep up. In this context, a strategy that looks great on paper often falls apart in practice. Imagine a team, for instance, who spent months crafting a detailed strategy—every milestone mapped, every risk assessed. But when conditions shifted, their well-laid plan quickly felt more like a burden than a beacon. Sound familiar?

This is a reality many organizations face. The traditional top-down approach to strategy, where a select few create the plan and hand it down, is cracking under the pressure of a faster, more complex world. Organizations need a strategy that’s dynamic, resilient, and, most importantly, actionable by everyone. To make this a reality, today’s leaders must bring strategy to life through a more inclusive, flexible model that empowers teams to contribute and adapt in real time.

In this new approach, strategic planning is about more than a set of priorities and goals—it’s about creating a two-way dialogue with people across the organization, building a culture of ownership, and embedding adaptability at every level. Here’s how to reinvent strategy in a way that turns it from an isolated exercise into a collective movement, creating a fast track to impact and ownership.

Create feedback loops closer to the customer

In conventional strategy sessions, plans are often crafted behind closed doors, only to be revealed once they’re fully formed. This approach may feel efficient, but it leaves out insights from those closest to the work—and to customers. Without input from these critical perspectives, strategies risk being disconnected from the realities on the ground.

This doesn’t mean handing over the strategy process to every employee or crowd-sourcing big decisions. Leaders still set the direction. The key is being intentional about when and where employee input will sharpen the strategy. Rather than starting with a blank slate, offer specific, targeted opportunities for feedback—especially from those on the front lines.

From: Senior leaders make the strategy and inform employees of the plan

To: Employees are engaged at critical moments early in the strategy planning process

An example: A SaaS company set an ambitious goal to double in size within three years—but early alignment was missing. Leaders were energized by big ideas but lacked a shared direction. To clarify the path forward, they created a set of strategic alternatives rooted in a clear purpose. Rather than relying solely on executive input, they brought in next-level leaders to pressure test early ideas and offer real-world feedback. These leaders piloted key parts of the strategy in their markets and then offered insights from their experiences that helped sharpen the long-term strategy. By intentionally involving the right people at the right moments, the organization gained clarity faster—and built stronger alignment early on.

By building feedback loops at the right moments, you can:

• Capture frontline insights that executives may not see, enriching the strategy.
• Generate early buy-in by giving employees a voice in shaping the “how” of the strategy where they are better positioned to know what will work.
• Align daily work with strategic goals by allowing employees to test the strategy and spot where it will work—and where it won’t.
• Create an environment where teams feel empowered to surface new insights and adapt.

A participatory approach at the right times along the strategy process doesn’t just inform the strategy—it makes it stronger and more grounded in real challenges, empowering employees to shape an outcome that feels both ambitious and achievable.

Cultivating ownership at every level

Even the best strategy is only as effective as the people who execute it. Ownership at all levels is essential to driving speed and adaptability, but it doesn’t happen by accident. When employees have clarity on how the strategy aligns to their individual roles and on the decisions they can own, they feel empowered and motivated to contribute to its success. This sense of ownership fosters a nimble, resilient organization.

By building purpose and clarity into every level of the plan, leaders can:

• Empower informed decisions at the right level that support company goals.
• Create momentum by showing employees their impact early on.
• Encourage continuous learning and adaptability anchored in the customer and market.
• Shift from static planning to an iterative, progress-driven mindset.

When employees see how their roles connect to larger goals and feel like they have the authority to make decisions, they are more willing—and prepared—to take ownership. This alignment, combined with a focus on purpose, drives momentum even in a shifting landscape.

From: Strategy execution is top-down, with decisions held at the leadership level.

To: Employees at all levels have clarity on how their roles connect to the strategy and where they can make decisions, fostering ownership and speed.

An example: One global healthcare company, having grown rapidly through acquisition, struggled with a fractured strategy—each business unit pulling in a different direction. Their turning point came not from a better plan, but from a unifying purpose. By helping teams see how they fit into a bigger vision, people could start seeing themselves in the future of the company. This shared purpose became a powerful driver of ownership—especially when disruption hit. When a major supply chain issue emerged just months later, teams didn’t splinter. Instead, they used that shared purpose as a compass, identifying new ways to deliver value and keep momentum going.

Align strategy and culture

All too often, strategy and culture are treated as separate domains. Yet, no matter how robust your strategic plan, it can only succeed if it aligns with the organization’s cultural norms and ways of working. For example, adopting a more agile operating model might mean shifting the culture toward quicker decision-making and cross-functional teamwork.

To create alignment between strategy and culture, leaders should:

• Identify key behaviors and ways of working that support strategic objectives—and those that are getting in the way.
• Focus on how these behaviors show up in everyday actions and decisions, and start making small shifts that reinforce what’s needed to execute the strategy.
• Experiment and iterate, and as you see success, formalize new ways of working.

When strategy and culture move in harmony, they generate powerful momentum. Strategy becomes part of the organization’s DNA, reinforcing behaviors that propel the company toward its goals.

From: Strategy and culture are treated as separate priorities.

To: Strategy and culture are intentionally aligned, with behaviors, ways of working, and decision-making reinforcing strategic goals.

An example: A company formed through a series of acquisitions faced a challenge: culture fragmentation. With each acquired unit operating by its own norms, there was no shared way of working—and no clear basis for making strategic tradeoffs. Before any strategy could take hold, leadership recognized that the organization needed a common foundation. The breakthrough wasn’t a new plan, but a cultural one: reconnecting people to why they were part of the same company and what future they were building together.

By identifying consistent ways of working across teams and aligning on a shared purpose, they built the cultural scaffolding needed to execute strategy effectively. When external conditions changed, teams responded not with confusion, but with cohesion. Cultural alignment became the engine that made adaptive strategy possible.

Build in flexibility and adaptability

Even the best strategies need room to flex. But too often, organizations treat adaptability as an exception—something reactive, triggered only when disruption hits.

In a world where the conditions you plan for rarely match the ones you execute in, flexibility can’t be an afterthought—it must be a built-in feature of how strategy takes shape and stays alive.

The problem? Most strategy processes are built for control, not change. They prioritize precision over learning, timelines over feedback, and reporting over reflection. The result: strategies that look solid on paper but crack under real-world pressure.

Everyone talks about agility. It’s become a fixture in executive keynotes and strategy decks. But what’s often missing is the how—the operating system that actually enables teams to move quickly and stay aligned when conditions shift.

To build that system, leaders need to rethink not just their planning cadences, but the behaviors, structures, and decision-making norms that shape how strategy is executed day to day.

Here’s what that looks like in practice:

• Empower teams to surface real-time insights and propose tactical shifts—so strategy stays grounded in frontline reality.
• Support rapid adjustments without losing strategic direction—aligning short-term moves with long-term outcomes.
• Strengthen leaders’ resilience and decision-making under pressure—so they can lead through ambiguity without stalling progress.
• Establish structured feedback loops and clear decision rights—so teams know when to escalate, when to adjust, and when to act.

These shifts aren’t abstract ideals—they’re already reshaping how leading organizations approach strategy execution. One global logistics company, facing rapid expansion and constant external pressure—from shifting customer expectations to volatile supply chains—recognized that reacting faster wasn’t enough. They needed to design for adaptability from the start.

Instead of relying on rigid quarterly plans, they implemented a 30-, 60-, and 90-day strategy rhythm. These weren’t status updates—they were structured checkpoints designed to challenge assumptions, surface real-time insights, and recalibrate execution before small issues became big ones.

So, when disruption came—as it inevitably does—the teams didn’t freeze or fall behind. They flexed with purpose and kept moving, not because they had all the answers, but because they were built to shift. Adaptability wasn’t a reaction—it was how the organization worked, by design.

A new era of strategic planning

Strategic planning today isn’t about crafting the “perfect” plan—it’s about building the capability to learn, adapt, and align at scale. What’s different now? Disruption is no longer episodic—it’s constant, compounding, and often coming from directions leaders didn’t anticipate. AI is rewriting roles. Markets move overnight. And decision-making is no longer confined to the top—it’s distributed across teams, functions, and geographies.

In this environment, traditional planning cycles collapse under pressure. The organizations that thrive won’t be the ones with the most polished strategy deck—they’ll be the ones with the strongest strategic muscles: the ability to sense, shift, and stay aligned in real time.

By replacing rigid plans with dynamic systems, leaders can activate strategy as a living, participatory process—shaped by insight from every level, reinforced through culture, and tested through execution.

Because in a world that won’t wait, the real advantage isn’t having the right answers upfront—it’s building an organization that knows how to respond when the questions change.

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.