Covid-19 and What Hasn’t Changed

Last night I started reading a book by Irvin Yalom, a psychiatrist who has written several novels that I’ve loved. But right now I’m reading something different—a book of short lessons he’s learned from many years of working with patients.

Early in his career, Yalom was inspired by something he read. The gist of it was that all people have a natural tendency to want to grow and become fulfilled—just an acorn will grow up to become an oak—as long as there are no obstacles in the way. So the job of the psychotherapist was to eliminate the obstacles to growth.

This was a eureka moment for Yalom. At the time, he was treating a young widow. Suffering through grief for a long while, she wanted help because she had a “failed heart”—an inability ever to love again.

Yalom had felt overwhelmed.  How could he possibly change someone’s inability to love?  But now he looked at it differently.  He could dedicate himself to identifying and eliminating the obstacles that kept her from loving.

So they worked on that—her feelings of disloyalty to her late husband, her sense that she was somehow responsible for his death, and the fear of loss that falling in love again would mean. Eventually they eliminated all of the obstacles. Then her natural ability to love—and grow—returned. She remarried.

Reading this story made me think of the responsibility of leaders toward the people they need to develop—and for the growth and learning that leaders themselves require to be the best that they can be.

Many leadership development challenges seem overwhelming—even impossible. The leaders that we coach usually have a list of areas where they want to get better, but how?  How do you “build better relationships with your peers and direct reports”?  How are you supposed to “get out of the weeds and demonstrate enterprise-wide thinking” or “build executive presence”?  All of these goals are as abstract as they are huge.

So the best approach is to not focus on the huge and fuzzy goal.  What we try to do is to break these goals down into concrete actions through working on real-time business problems. To put it simply, though, we do just as Yalom does: We identify the obstacles and work toward knocking them off, one at a time.

Leadership development is not usually a quick fix. You’re not going to develop executive presence through a half-day workshop or a one-time meeting.  If you’re interested in meaningful, lasting growth—whether for yourself or for those who work for you—it’s a commitment.

But don’t ever forget that we’re all capable of growth throughout life and our careers. The trick is to find the right coach or mentor who will guide you through that obstacle course.

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Feedback is one of the most powerful tools a leader has, shaping both individual and organizational culture. Yet, despite its value, it’s often met with apprehension—seen as judgment rather than an opportunity. Instead of fueling growth, it can create tension, leaving recipients feeling exposed and defensive.

This reaction is natural. Feedback touches on identity, competence, and self-worth. When framed as a verdict rather than an insight, it sparks defensiveness instead of openness. But what if feedback wasn’t about judgment? What if it was a tool for gathering better data—both for the recipient and the leader?

When leaders make feedback a habit, not a performance review, they gain sharper insights, model continuous improvement, and create a culture where learning thrives. The shift from evaluation to empowerment turns feedback into fuel for growth. And at the heart of this shift? Curiosity.

Leading in a MESSY world: Why feedback matters more than ever

Leaders today operate in constant disruption and complexity. They must move beyond assumptions and seek new perspectives. At BTS, we call this operating in a MESSY world:

• M – Making sense of the broader ecosystem
• E – Establishing emotional connections to build trust
• S – Seizing momentum to stay ahead
• S – Sensing the future amid uncertainty
• Y – Yielding ego to create space for others to grow

Feedback is critical in helping leaders navigate these challenges. It’s not just a tool for correction but a catalyst for innovation and collaboration. But without structure, feedback can fall flat. That’s where the AFIRM Model comes in.

Reframing feedback: From evaluation to exploration

Great feedback moves beyond transaction into mutual discovery. When leaders model effective feedback, they foster deeper connections and unlock insights that drive performance.

Curiosity plays a crucial role in this transformation. When leaders approach feedback with genuine curiosity—asking open-ended questions and actively listening—they shift conversations from critique to shared learning. Curiosity also provides leaders with better data on how they show up, helping them refine their approach and model the kind of feedback culture they want to create.

Balancing feedback with efficiency is essential. The AFIRM Model provides a structured approach that makes feedback actionable and constructive while keeping curiosity at the center.

Structure feedback for impact with the AFIRM model

AFIRM enables structured yet flexible conversations—ensuring feedback drives results. It provides a roadmap for leaders to create meaningful, productive discussions that foster growth and accountability. Here’s how it works:

A – Agenda

Set clear intentions. Define the purpose and desired outcomes upfront. A prepared conversation leads to honest, productive dialogue and signals that feedback is a shared responsibility rather than a one-sided critique.

F – Facts, Observations, Evidence

Keep it objective. Base feedback on data and observations to minimize bias. Stay neutral and constructive. Providing fact-based feedback ensures conversations remain focused and prevents emotional reactions that derail progress.

Curiosity fosters deeper dialogue—ask questions, seek perspectives, and pave the way for growth. Instead of assuming why something happened, ask “What led to this?” or “What challenges were you facing?” to create space for honest reflection.

I – Impact

Clarify effects. Who was affected? What were the consequences? Centering feedback on impact builds trust and accountability. Highlighting the broader implications helps individuals understand why feedback matters and how their actions contribute to team success.

R – Request

Co-create a path forward. Define actionable, SMART next steps (Specific, Measurable, Achievable, Realistic, Time-bound). Encourage collaboration by asking “How do you think we can move forward?” or “What support do you need?” Keeping the dialogue open ensures accountability while fostering autonomy.

M – Mutuality

Feedback is a partnership. Success requires shared ownership and commitment to growth. A strong feedback culture thrives when both parties see feedback as a two-way street—leaders should also invite input on how they can better support and enable success. Take time to ask “What feedback do you have for me?” to reinforce that feedback is a mutual learning process.

Creating feedback-driven growth

Imagine an organization where feedback fuels engagement and connection. When framed as a tool for growth rather than judgment, conversations shift from evaluation to exploration. Everyone is on the same team, with the same goals.

Great leaders don’t just give feedback—they seek it, reflect on it, and use it to sharpen their approach. By modeling curiosity and making feedback a daily habit, they foster a culture where feedback is normal, constructive, and empowering.

Feedback isn’t about fixing. It’s about discovering what’s possible. By approaching it as a shared learning opportunity, we move from judgment to collaboration, growth, and transformation.

What’s one question you could ask today to spark a meaningful feedback conversation?

The landscape of leadership is evolving as newer generations challenge traditional hierarchies. Outdated practices, focused on a top-down power dynamic, have fostered an “us vs. them” mentality, stifling collaboration, slowing innovation, and hindering sustained growth.In response, Future Relevant Organizations are adopting "next practices" that recognize and celebrate contributions, influence, and impact of contributions at all levels of the organization. Central to this shift is the movement from “leading others” to “leading with others,” recognizing that leadership isn’t confined to those in senior positions.“Leading with others” encourages a more inclusive, collaborative approach by:

• Encouraging employees to lead and influence across boundaries.
• Inspiring shared purpose and accountability toward collective goals.
• Prioritizing well-being, fostering psychological safety, and enabling open idea-sharing.
• Viewing vulnerability as a strength, recognizing that no one has all the answers.
• Maintaining focus and thoughtful engagement amidst uncertainty.

A biopharma company with a historically top-down leadership structure offers a clear example of the transformative power of this shift. While the company had enjoyed impressive growth, it faced competitive and pricing pressures from disruptive innovation, regulatory challenges, and supply chain vulnerabilities, all of which called for a fresh approach to leadership. Innovation and expansion were crucial to sustaining success.Recognizing the need for change, the company embraced the idea that leadership and influence aren’t confined to those at the top. Here’s how this new approach reshaped their organization:

• Empowering all levels: Leadership became less about titles and more about fostering a culture where every employee felt valued and capable of contributing. Through well-crafted experiences, 5,000 employees enhanced their self-awareness, challenged established norms, and adopted a long-term perspective aimed at collective growth.
• Redefining leadership: Leadership shifted from micromanagement to empowering others to make meaningful contributions. Employees were given greater agency and ownership, leading to increased adaptability in a dynamic market.
• Building trust through vulnerability: The organization encouraged vulnerability, quickly building trust across teams in an evolving, loosely connected environment. This strengthened team dynamics and established a supportive community ready to face new challenges.

Next practices: Shared leadership responsibility

The shift toward “leading with others” is not simply a change in leadership style; it is a strategic imperative. By embracing diverse perspectives and treating leadership as a collective responsibility, organizations gain more valuable insights that drive better decision-making and innovation. Companies that adopt this approach are better prepared to adapt to change, seize new opportunities, and build a culture where everyone is engaged in shaping the future.

“Leading with”: A more inclusive path forward

Adopting a “leading with others” mindset requires more than just structural changes—it calls for a fundamental shift in how leadership is understood at all levels. Leaders must actively create environments where contributions from all employees are expected, not optional. This inclusive leadership approach fosters a deeper sense of ownership and accountability, empowering employees to align their actions with the organization’s long-term goals.As the business landscape continues to evolve, organizations that embrace this collective approach to leadership will be better positioned not only to navigate uncertainty but also to thrive in the future ensuring future relevance.

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.