3 things an executive can do: influencing in passive-aggressive cultures
The Chief Digital Officer (CDO) had a compelling vision for leading a digital transformation that would be critical to remaining a viable competitor in their marketplace. She was hired to deliver on this innovation, and everyone knew that without implementing this vision, the company would not survive for more than four or five more years.
Yet, the CDO could not get her C-Suite peers to have a reasonable debate and reach a decision on a path forward. The rest of the leadership team was avoiding the issue, and her attempts to engage them went unanswered. They weren’t hostile, and in fact expressed agreement on the importance of the change—they just refused to respond and take needed action. Because the company had this “nice” culture that avoided even healthy debate, the CDO was completely frustrated. She was losing ground rapidly, and yet was under the gun to deliver. She didn’t know what to do.
During a coaching session, she said to me, “Do I express my frustration and risk being seen as angry? That will not get me far. So how can I be authentic without upsetting my peers? I am tired of being ‘nice’ and getting nowhere! There are two big non-traditional competitors out there who will eat our lunch if we do not act now. Don’t they see that inaction will lead to the death of the company? I was given responsibility for a mission-critical job, yet no one wants to debate it or make any decisions! I’m going crazy!”
“Nice” cultures: death by a thousand unspoken cuts
The CDO was describing a passive-aggressive organization. These cultures are not rare. In fact, studies have found that over 25% of companies can be classified as passive aggressive. On the surface, everyone is friendly, which makes reaching consensus easy. The problem is that the consensus is really false agreement since it was reached without constructive debate. As a result, few people are really committed to the decision since they gave in rather than buying into the decision. So, everyone drags their feet when it comes to supporting implementation.
A common symptom of false consensus is second guessing. Since team members don’t express their true concerns the first time around, they may bring up a concern or a question later, after you thought the team had made a decision. And since no one likes confrontation, the second guessing brings everything to a halt.
Everyone is pleasant, but nothing can get done. And this can go on for months, if not years. Meanwhile, the company’s competitors are starting to steal market share.
3 things a leader can do
We worked with this leader to plan her path. These three actions, when done in combination, can unlock conversation, collaboration, healthier debate, as well as a way to accelerate your ideas, while navigating the culture of “nice.”
- Make the case – the executive team needs to be persuaded on the value and benefits to move off their position
Explain, in simple language, why the company needs a digital transformation now. Use a few key pieces of data. For example, tell a quick but compelling 2-3-minute story of how a customer filed a complaint because the company’s databases did not talk to each other. Or refer to an industry study that makes the case for the need for a transformation. Show data that is important to your audience – your C-Suite peers.The goal is to show them you need to take action now. - Explore their resistance – understanding what’s behind their behavior helps you to connect to what matters to them
Of course, as you are making your case, your audience is thinking of all the reasons not to take any bold actions.To break the norm of a passive-aggressive culture, it is important to make it safer for people to voice their concerns. You need to understand their resistance, not ignore it. How can you deal with their resistance if you do not know what it is? You want concerns out in the open, rather than buried under a veneer of “nice.” The trick is to create the setting to make this comfortable and productive.
In this case, we coached the CDO to break down the executive team into groups of 3 or 4 people and start the conversation with something like, “You all have heard my plans for a digital transformation. I know I probably didn’t think of everything. Maybe there are some unintended consequences I haven’t considered. Or maybe I am not aware of some data you have. Or maybe parts of my plan seem ambiguous or not clear. In your breakout groups, I’d like you to discuss your biggest concerns and questions. I need to know them so I can make the right tweaks to my plan. Come back with a list of your biggest concerns.”
By doing this, she is giving them permission to challenge her. But, at the same time, she is making it clear she is going ahead with her plan. This process is a good authentic way to display both the humility required in a “nice” culture, as well as the assertiveness needed to get things done.
Hopefully, this type of exercise will yield some insights into their real resistance, which makes it easier to respond to concerns, and possibly adjust your plans to meet their needs. And sometimes you will not be able to meet their needs, but at least they will feel heard, and you may be able to offer an alternative solution. For example, you can say, “I understand this initiative will take resources away from you, but this mission-critical project is in the best interest of the company and will keep us sustainable. Perhaps we can find some way to give you some temporary help.”
By hearing and responding to their concerns, you are increasing the chance of buy-in and hopefully minimizing the second guessing that often comes later.
If you have successfully made your business case (step #1 above) and you have been given the responsibility to transform the company, you do not need to make sure everyone agrees with you 100%. The goal of decision-making, even consensus, is not unanimity, but unity.And once you have that unity – the agreement to proceed with the transformation – the next step is to rally the troops. - Inspire the troops – lay the groundwork to engage and inspire everyone to do their part in delivering on the transformation
Once the C-Suite is united around the vision of the digital transformation, it’s time to get everyone, not just the executive team, on board. Often, a leader can have the right vision, but the troops will stifle execution. Especially in a passive-aggressive culture, a functional or department head may be talking negatively about your vision to their people but saying positive things to your face. Talking to and hearing from people directly eliminates the backchanneling and filter.
One powerful option is to go on a “vision tour” and meet with the various departments and functions to explain the vision and answer questions. For our CDO, ideally, she would be accompanied by the CEO and the department leader.
A successful vision tour focuses on two points:
- Demonstrating how the change will benefit the audience
Everyone probably has a horror story about the current situation that is leading up to the change – it could be something like how frustrated they are when trying to get accurate information quickly, or how their systems do not talk to each other. Share a short story from someone in that function about their pain points and draw the connection to the change. Show how you understand their frustrations and how this initiative will make their work life better
- Giving people a chance to ask questions and express their concerns
Consider convening a virtual or in-person town hall. Ask people to get together in small groups and come up with three questions or concerns. Have a spokesperson from each group take turns sharing a concern. Answer as many of these questions are possible. It is important to be as honest and transparent as you can. If you do not know the answer or need more time to give one, say so, but be sure to get back to the group with a response as soon as possible. By being authentic and honest, people will begin to trust you and see you have the best interest of the enterprise at heart. In passive-aggressive cultures, people are used to leaders saying everything will be fine when everyone knows everything will not be “fine.” You will gain lots of credibility if you are honest with people about the challenges change brings.
And just as important, you will model a way to be “nice” and respectful without the need to avoid difficult conversations.
Be appropriately nice and appropriately assertive
If you follow these three steps, you will greatly increase your ability to influence change. True, you can’t change a passive-aggressive culture overnight. But you can take some actions to minimize the chances that your ideas will be stymied and gently killed by a “nice” culture. Remember, “nice” cultures are really not very nice. As Carolyn McCray says, “You do realize that passive-aggressive behavior is aggressive behavior for cowards, right?” You need to take the fear out of speaking up.
You are expected to lead, so lead. You are also expected to be nice, so be nice. You can do both.
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.