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
Global spending on AI is forecast to reach $2.52 trillion by 2026, a 44% year-over-year increase, according to Gartner. At the same time, only about 10% of AI pilots scale beyond proof of concept.
What’s the disconnect?
Why aren’t most organizations seeing the ROI they hoped for, despite making such large investments?
It’s not because the technology isn’t ready. And it’s not because the use cases are unclear.
The disconnect exists because many organizations are investing in AI as a technology upgrade and expecting a business transformation in return.
The tools are advancing at breathtaking speed, and most organizations already have AI in motion. But the work itself often stays the same. AI gets layered onto existing tasks instead of being used to rethink workflows end to end. Adoption metrics go up, while decisions, operating models, and value creation remain largely untouched.
When teams first start using AI, they do what makes sense. They try to recreate today, just faster. Can it help me write this? Analyze that? Save a bit of time?
That’s a smart place to begin. But it’s not where ROI, or reinvention, actually shows up.
Getting over the hump
Real returns begin when teams experience what we often call “getting over the hump.”
This is the moment when two things click at once:
- AI can fundamentally change how work gets done.
- People don’t need deep technical expertise to make that change happen.
When teams see weeks of work compress into hours, or watch an end-to-end workflow suddenly run in a new way, something shifts. Confidence replaces hesitation. Curiosity replaces caution. The questions change, from “How do I use this tool?” to “What’s possible now?”
That shift matters, because ROI doesn’t come from using AI more often, it comes from using it to work differently.
Why ROI stalls as AI scales
As AI initiatives expand, many organizations discover that the limiting factor isn’t the technology itself. It’s the environment surrounding the work.
ROI shows up when teams are able to explore and redesign workflows, not just automate steps. That requires clarity on outcomes and guardrails, but also room to experiment, learn, and iterate. When AI is tightly controlled or narrowly deployed, pilots stay pilots. When people are trusted to rethink how work happens, value starts to compound.
Organizations that unlock ROI don’t chase perfect use cases upfront. They focus on learning faster and applying those insights where they matter most.
The early signal that ROI is coming
Long before AI shows up in financial results, there’s an earlier indicator that organizations are on the right path.
People are energized by the work.
You see it when teams start sharing experiments, when ideas move across functions, and when learning becomes visible rather than hidden. Progress feels owned, not imposed.
That energy isn’t accidental. It’s a signal that people feel trusted to rethink how work happens, and that trust is essential to turning investment into impact.
Reinvention happens closer to the work than most expect
AI reinvention rarely starts with a sweeping rollout or a multi-year roadmap. More often, it begins with one meaningful workflow, one team close to the work, and a willingness to ask a different question.
With the right support, that team gets over the hump. What they learn becomes reusable. Patterns emerge. Over time, those insights connect, creating enterprise-wide impact and sustained ROI.
That’s how organizations move from isolated pilots to real returns.
What this means for AI investment
No organization feels fully “caught up” with AI, and that’s true across industries.
The organizations that will realize ROI aren’t waiting for certainty or the next breakthrough tool. They’re reinvesting their AI spend into new ways of working that scale human potential alongside technology.
Handled thoughtfully, AI doesn’t distance people from the work. It brings them closer - to better decisions, stronger collaboration, and better outcomes.
For many organizations, that’s where the real return begins.
Technology choices are often made under pressure - pressure to modernize, to respond to shifting client expectations, to demonstrate progress, or to keep pace with rapid advances in AI. In those moments, even experienced leadership teams can fall into familiar traps: over-estimating how differentiated a capability will remain, under-estimating the organizational cost of sustaining it, and committing earlier than the strategy or operating model can realistically support.
After decades of working with leaders through digital and technology-enabled transformations, I’ve seen these dynamics play out again and again. The issue is rarely the quality of the technology itself. It’s the timing of commitment, and how quickly an early decision hardens into something far harder to unwind than anyone intended.
What has changed in today’s AI-accelerated environment is not the nature of these traps, but the margin for error. It has narrowed dramatically.
For small and mid-sized organizations, the consequences are immediate. You don't have specialist teams running parallel experiments or long runways to course correct. A single bad platform decision can absorb scarce capital, distort operating models, and take years to unwind just as the market shifts again.
AI intensified this tension. It is wildly over-hyped as a silver bullet and quietly under-estimated as a structural disruptor. Both positions are dangerous. AI won’t magically fix broken processes or weak strategy, but it will change the economics of how work gets done and where value accrues.
When leaders ask how to approach digital platforms, AI adoption, or operating model design, four questions consistently matter more than the technology itself.
- What specific market problem does this solve, and what is it worth?
- Is this capability genuinely unique, or is it rapidly becoming commoditized?
- What is the true total cost - not just to build, but to run and evolve over time?
- What is the current pace of innovation for this niche?
For many leadership teams, answering these questions leads to the same strategic posture. Move quickly today while preserving options for tomorrow. Not as doctrine, but as a way of staying adaptive without mistaking early commitment for strategic clarity.
Why build versus buy is the wrong starting point
One of the most common traps organizations fall into is treating digital strategy as a series of isolated build-vs-buy decisions. That framing is too narrow, and it usually arrives too late.
A more powerful question is this. How do we preserve optionality as the landscape continues to evolve? Technology decisions often become a proxy for deeper organizational challenges. Following acquisitions or periods of rapid change, pressure frequently surfaces at the front line. Sales teams respond to client feedback. Delivery teams push for speed. Leaders look for visible progress.
In these moments, technology becomes the focal point for action. Not because it is the root problem, but because it is tangible.
The real risk emerges operationally. Poorly sequenced transitions, disruption to the core business, and value that proves smaller or shorter-lived than anticipated. Teams become locked into delivery paths that no longer make commercial sense, while underlying system assumptions remain unchanged.
The issue is rarely technical. It is temporal.
Optimizing for short-term optics, particularly client-facing signals of progress, often comes at the expense of longer-term adaptability. A cleaner interface over an ageing platform may buy temporary parity, but it can also delay the more important work of rethinking what is possible in the near and medium term.
Conservatism often shows up quietly here. Not as risk aversion, but as a preference for extending the familiar rather than exploring what could fundamentally change.
Licensing as a way to buy time and insight
In fast-moving areas such as AI orchestration, many organizations are choosing to license capability rather than build it internally. This is not because licensing is perfect. It rarely is. It introduces constraints and trade-offs. But it was fast. And more importantly, it acknowledged reality.
The pace of change in this space is such that what looks like a good architectural decision today may be actively unhelpful in twelve months. Licensing allowed us to operate right at the edge of what we actually understood at the time - without pretending we knew where the market would land six or twelve months later.
Licensing should not be seen as a lack of ambition. It is often a way of buying time, learning cheaply, and avoiding premature commitment. Building too early doesn’t make you visionary, often it just makes you rigid.
AI is neither a silver bullet nor a feature
Coaching is a useful microcosm of the broader AI debate.
Great AI coaching that is designed with intent and grounded in real coaching methodology can genuinely augment the experience and extend impact. The market is saturated with AI-enabled coaching tools and what is especially disappointing is that many are thin layers of prompts wrapped around a large language model. They are responsive, polite, and superficially impressive - and they largely miss the point.
Effective coaching isn’t about constant responsiveness. It’s about clarity. It’s about bringing experience, structure, credibility, and connection to moments where someone is stuck.
At the other extreme, coaches themselves are often deeply traditional. A heavy pen, a leather-bound notebook, and a Royal Copenhagen mug of coffee are far more likely to be sitting on the desk than the latest GPT or Gemini model.
That conservatism is understandable - coaching is built on trust, presence, and human connection - but it’s increasingly misaligned with how scale and impact are actually created.
The real opportunity for AI is not to replace human work with a chat interface. It is to codify what actually works. The decision points, frameworks, insights, and moments that drive behavior change. AI can then be used to augment and extend that value at scale.
A polished interface over generic capability is not enough. If AI does not strengthen the core value of the work, it is theatre, not transformation.
What this means for leaders
Across all of these examples, the same pattern shows up.
The hardest decisions are rarely about capability, they are about timing, alignment, and conviction.
Building from scratch only makes sense when you can clearly articulate:
- What you believe that the market does not
- Why that belief creates defensible value
- Why you’re willing to concentrate risk behind it
Clear vision scales extraordinarily well when it’s tightly held. The success of narrow, focused Silicon Valley start-ups is testament to that.
Larger organizations often carry a broader set of commitments. That complexity increases when depth of expertise is spread across functions, and even more so when sales teams have significant autonomy at the point of sale. Alignment becomes harder not because people are wrong, but because too many partial truths are competing at once.
In these environments, strategic clarity, not headcount or spend, creates advantage.
This is why many leadership teams choose to license early. Not because building is wrong, but because most organizations have not yet earned the right to build.
This article was originally publish on Rotman Management
IN OUR CONSULTING WORK with teams at all levels—especially senior leadership—my colleagues and I have noticed teams grappling with an insidious challenge: a lack of effective prioritization. When everything is labeled a priority, nothing truly is. Employees feel crushed under the weight of competing demands and the relentless urgency to deliver on multiple fronts. Requests for prioritization stem from both a lack of focused direction and the challenge of efficiently fulfilling an overwhelming volume of work. Over time, this creates a toxic cycle of burnout, inefficiency and dissatisfaction.
The instinctive response to this issue is to streamline, reduce the number of initiatives, and focus. While this is a step in the right direction, it doesn’t fully address the problem. Prioritization isn’t just about whittling down a to-do list or ranking activities by importance and urgency on an Eisenhower Decision Matrix; it also requires reshaping how we approach work more productively.
In our work, we have found that three critical factors lie at the heart of solving prioritization challenges: tasks, tracking and trust. Addressing these dimensions holistically can start to address the root causes of feeling overwhelmed and lay the foundation for sustainable productivity. Let’s take a closer look at each.