Demonstrating Executive Presence During the COVID-19 Crisis
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Obviously, we are living through an extraordinary and unprecedented situation in the world today—both personally and professionally.
Collectively, we are all doing our best to reimagine how we live as well as how we work. Given that the crisis has created an unimaginable level of uncertainty as well as anxiety across the globe, leaders need to be doing a good deal of soul searching about what matters most now.To that end, I’ve given much thought over the last week about what executive presence needs to look like from leaders in the face of this crisis.
Over the past five years, I’ve worked with thousands of leaders on executive presence, coaching 400 or 500 of them individually after they received feedback from their manager, peers, direct reports and others on executive presence. Based on my work with these leaders and my understanding of the science behind executive presence and influence, here are the facets that leaders most need to demonstrate now—and how to make them actionable.
1. Composure
This quality reflects how much the leader is perceived as steady in a time of crisis. Basically, emotions are contagious—for better and worse!What to do now. Be “real” about the crisis—don’t downplay the reality or magnitude of it. Allow some time to check in with people about how they’re feeling today about the crisis. But then you want to make sure everyone is generating light rather than heat. Get everyone to focus on how to make course corrections: What can be done to address today’s concerns while anticipating tomorrow’s downstream consequences?
2. Interactivity
The quantity and quality of two-way communication between the leader and others will be important than ever during this crisis.What to do now. You can create a greater sense of calm by ensuring that there is predictability about how and when you exchange ideas and concerns with your team. Consider announcing a more frequent cadence of meetings for the immediate future. As the news and outlook changes several times a week, make sure people aren’t left to wonder what’s happening and why. Staying in touch regularly also means that you’ll keep your finger on the pulse of what others wants and need right now.
3. Resonance
While meeting more regularly is a great step, this crisis also means that you need to be able to dig deeply into understanding everyone’s hopes, fears, and needs.What to do now. Make a point of asking questions that surface what others are thinking, feeling, and planning to do. Failing to do so will make you run the risk of appearing “tone deaf” during a crisis. Take it a step further and pick up on the nonverbal behavior of others, as people often will show what they’re feeling before they’re willing or able to say what’s in their head or heart. If you notice body language that seems troubled or uncertain, hit the pause button and ask questions to find out what’s really going on. That‘s why video is such an advantage over a simple phone call when working remotely. More than ever, people need to know that their leaders care about how they’re doing.
4. Authenticity
In addition to being a good listener and focusing on others during a time of crisis, you need to balance that by being candid, transparent, and genuine about what you yourself share.What to do now. In the face of so much uncertainty right now, you may be tempted to “wait and see” and go silent. But if you do, the risk is that people will fill that void with their own assumptions—and those often can turn negative. This leads to more churn, distraction, and disengagement. Even when you don’t have all the answers, you need to be talking to people—sharing at least the process of what will happen even if you don’t yet have the content.
5. Vision
Authenticity is strongly linked to Vision. In both cases, people need to understand the why behind the what—the intent behind the content.What to do now. With Vision, you need make that “why” come alive by telling the story of the road ahead and why everyone should feel a sense of mission and purpose about that. If you’re not sure about what that vision of the future should be, the first step may be to go on a “vision listening tour” in order to “crowdsource” ideas. Another idea would be to create a short-term vision: What do we need to focus on for the next few weeks at least? Providing clarity about what everyone’s doing and why will help keep people energized through difficult times.All 15 facets of executive presence can be valuable in a time of crisis. But for now, focus on these five qualities. If you have a strength in one of these facets, now is the time to leverage it. If one of these qualities is more difficult for you, get help from a trusted advisor, mentor, or coach to make sure it’s not a derailer during this challenging time.
Above all, remember that this crisis represents not only a challenge but unique opportunity for you and your organization. By displaying these qualities, you can position your organization to find its way through a dark moment in history and move toward a brighter dawn.For more resources on leading through these unprecedented times, click here.
Related content
Related content
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.
- They don't think it will help them
- Nobody around them is using it
- They don't feel capable
- 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.
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.