How to Lead Your Team Through AI Disruption Without Losing Your Culture
AI is changing how every team works, and most leaders are getting the transition wrong. They are either moving too fast and leaving their people behind, or moving too slow and watching competitors pull ahead. Chris Dyer, a keynote speaker, former 5x Inc. 5000 CEO, and Inc. Magazine’s #1 Leadership Speaker on Culture, has spent years helping organizations navigate exactly this challenge. His approach is different from most AI thought leaders because he starts with the human side: the culture, the moments that define how people experience the transition, and the leadership behaviors that determine whether AI adoption builds your team up or tears it apart. This guide shares the framework Chris uses with organizations like NASA, Johnson & Johnson, General Motors, Intuit, and ispot.tv to help leaders integrate AI without losing what makes their teams work.
Table of Contents
1. Why Most Organizations Are Getting AI Adoption Wrong
2. The Culture-First Approach to AI Disruption
3. Five Leadership Strategies for Navigating AI Change
4. The Moments That Matter During AI Transitions
5. What Leaders Get Wrong About AI Resistance
6. How to Know If Your Culture Can Handle the Shift
7. Frequently Asked Questions About Leading Through AI Disruption
Why Most Organizations Are Getting AI Adoption Wrong
The conversation around AI in most organizations has become binary. Leaders are either all in, pushing rapid adoption with mandates and deadlines, or they are waiting, hoping the hype passes or that someone else will figure it out first. Both approaches fail for the same reason: they treat AI adoption as a technology problem when it is fundamentally a people problem.
When ispot.tv brought Chris Dyer in for their 2026 Sales Kickoff in Seattle, their leadership was dealing with a version of this challenge that will sound familiar to most organizations. Teams were operating in silos. People were defaulting to old habits. Budget tightening meant that every new initiative, including AI tools, was met with skepticism rather than enthusiasm. The issue was not that ispot.tv lacked smart people or good technology. The issue was that the conditions for change had not been established at the cultural level.
This is the pattern Chris sees across industries. The technology is ready. The people are not, and the reason the people are not ready is almost never about skills or training. It is about trust, communication, and whether the organization has built a culture that can absorb disruption without fracturing.
McKinsey’s research on digital transformations consistently shows that the majority of them fail to meet their objectives. The reasons are almost always human: unclear communication from leadership, employees who feel their concerns are being ignored, middle managers who lack the frameworks to guide their teams through ambiguity, and cultures that punish mistakes rather than learning from them. AI adoption is just the latest version of this pattern, but it is arguably the highest-stakes version because the pace of change is faster and the implications for people’s roles are more personal.
The Culture-First Approach to AI Disruption
Chris Dyer’s approach to AI disruption starts with a question that most technology-focused consultants never ask: Is your culture strong enough to handle this?
This is not a soft question. It is a diagnostic one. Chris uses his 7 Pillars of Amazing Culture framework to assess whether an organization has the cultural infrastructure to support a major transition like AI adoption. The seven pillars are Transparency, Positivity, Measurement, Acknowledgment, Uniqueness, Listening, and Mistakes. Each one plays a specific role during AI disruption.
Transparency determines whether your people trust the information they are receiving about AI’s impact on their roles. If your organization has a history of withholding bad news or sugarcoating difficult realities, your team will assume the worst about AI regardless of what leadership says. The antidote is radical honesty: here is what we know, here is what we do not know, and here is how we will figure it out together.
Listening determines whether leadership is actually hearing what their teams are worried about. In most organizations navigating AI adoption, leaders are so focused on the strategic opportunity that they miss the specific fears their people are carrying. Those fears are rarely about the technology itself. They are about relevance, job security, and whether the skills they have spent years developing still matter. Leaders who listen to those concerns and address them directly build the trust that makes adoption possible.
Mistakes may be the most critical pillar during AI transitions. Organizations that punish mistakes will see their teams refuse to experiment with AI tools because the cost of getting it wrong feels too high. Organizations that treat mistakes as learning opportunities will see their teams lean into experimentation, share what works and what does not, and accelerate adoption organically. The difference between these two outcomes is not training. It is culture.
Acknowledgment matters because AI transitions inevitably ask people to let go of workflows and expertise they have spent years building. If leadership does not acknowledge the value of what people have contributed before the transition, those people will experience AI as an erasure of their work rather than an evolution of it. Simple acts of recognition during transitions, acknowledging someone’s expertise while asking them to build new skills, can be the difference between a team that engages and a team that quietly disengages.
The remaining pillars, Positivity, Measurement, and Uniqueness, each play supporting roles. Positivity creates the emotional environment where people can be honest about their concerns without fear. Measurement gives teams objective data on how the transition is progressing rather than relying on anecdotal impressions. Uniqueness reminds the organization that AI is a tool that should amplify what makes the team distinctive rather than homogenize it.
Five Leadership Strategies for Navigating AI Change
Based on his work with more than 300 keynotes in over 20 countries and his experience building companies that earned “Best Place to Work” recognition 15 times, Chris Dyer recommends five leadership strategies for organizations navigating AI disruption.
Strategy 1: Lead with the “why” before the “what.” Most AI rollouts start with the tool: here is the software, here is the training, here is the deadline. Chris recommends starting with the reason: here is the problem we are solving, here is how this makes your work better, here is what this means for the team’s future. When leaders skip the “why,” they create compliance. When they lead with the “why,” they create commitment. The difference shows up in adoption rates, in the quality of how people use the tools, and in whether the best performers stay or start looking elsewhere.
Strategy 2: Identify and protect the moments that matter. Chris’s Moments That Matter framework identifies seven moment types that shape how people experience leadership: Inception, Transition, Decision, Recognition, Connection, Truth, and Culmination. During AI adoption, Transition Moments and Truth Moments carry disproportionate weight. Transition Moments are the spaces between the old way of working and the new one. Leaders who acknowledge the difficulty of that in-between space, rather than pretending it does not exist, earn the trust that carries the team through. Truth Moments are the times when leaders have to deliver honest information about what AI means for specific roles and functions. How a leader handles those conversations defines the entire experience of the transition for the people in the room.
Strategy 3: Create safe spaces for experimentation. The organizations that adopt AI most successfully are the ones where people feel safe trying new tools, making mistakes, and sharing what they learn. This does not happen by default. It has to be designed. Chris recommends creating explicit “experiment and report” structures: designated time for teams to try AI tools on real work, with the expectation that they will share both successes and failures with their peers. This turns AI adoption from a top-down mandate into a collaborative learning process.
Strategy 4: Use the Ladder of Abstraction to calibrate your message. Different audiences in your organization need different levels of detail about AI adoption. Executives need the strategic picture: where are we going and why. Middle managers need the operational picture: what changes in their day-to-day responsibilities and how do they guide their teams. Frontline teams need the practical picture: what specific tools am I using, what happens to my workflow, and who do I ask when I get stuck. The Ladder of Abstraction is a communication tool Chris teaches leaders to use for calibrating their message to the audience in front of them. The mistake most leaders make is delivering the executive message to the entire organization and wondering why the frontline feels confused.
Strategy 5: Measure adoption by engagement, not compliance. Most organizations track AI adoption through usage metrics: how many people logged in, how many prompts were submitted, how many hours of training were completed. These metrics tell you about compliance, not adoption. Real adoption shows up in engagement: are people voluntarily using AI tools to solve problems they were not asked to solve? Are teams sharing tips and techniques with each other? Are people asking for more advanced training? Chris recommends tracking these qualitative signals alongside the quantitative ones because they tell you whether your culture is absorbing the change or merely tolerating it.
The Moments That Matter During AI Transitions
Chris Dyer’s Moments That Matter framework, based on his bestselling book of the same name, identifies seven moment types that carry disproportionate weight in how people experience any transition. During AI adoption, three of these moments are especially critical.
Inception Moments are the first impressions your team has of the AI transition. How leadership announces the change, what language they use, whether they acknowledge the uncertainty, and whether they invite questions or deliver a monologue all shape the narrative your team builds about the transition. A poorly handled Inception Moment can create resistance that takes months to undo. A well-handled one can create curiosity and openness that accelerates everything that follows.
Transition Moments are the spaces between the old way of working and the new one. This is where most AI adoptions lose momentum because leadership underestimates how disorienting the in-between space is for people. Chris calls this the “Third Space,” a concept from his book, and teaches leaders to acknowledge it explicitly: you are not fully in the old world and not fully in the new one, and that is normal. Leaders who normalize the discomfort of transition rather than pretending it does not exist build teams that move through change faster.
Decision Moments are the points where leaders have to make calls about AI that affect people’s roles, workflows, and futures. The 10-10-10 Rule, another framework from Moments That Matter, helps leaders evaluate these decisions through three lenses: how will this feel in 10 minutes, 10 months, and 10 years? This prevents the two most common mistakes in AI adoption: making impulsive decisions driven by hype (the 10-minute lens) and avoiding necessary decisions out of fear (the 10-year lens).
What Leaders Get Wrong About AI Resistance
Most leaders interpret resistance to AI as a skills gap or a mindset problem. In Chris Dyer’s experience, resistance is almost always a signal that one or more cultural pillars is weak.
When people resist AI because they do not trust leadership’s intentions, the problem is Transparency. When people resist because they feel their concerns are being dismissed, the problem is Listening. When people resist because they are afraid of looking incompetent with new tools, the problem is Mistakes. When people resist because nobody has acknowledged the value of the work they did before AI, the problem is Acknowledgment.
The leadership instinct in these situations is usually to increase training, mandate adoption, or bring in an AI consultant. None of those solutions address the underlying cultural issue, which is why the resistance persists even after the training is complete and the mandate is in place.
Chris’s approach is to diagnose which pillar is weak and address it directly. This is faster and more effective than generic change management because it targets the specific cultural condition that is creating the resistance rather than treating all resistance as the same problem.
This is also what makes Chris Dyer’s approach to AI disruption different from most AI keynote speakers. Most AI speakers focus on the technology: what AI can do, how to implement it, which tools to use. Chris focuses on the human infrastructure that determines whether the technology gets adopted successfully. His question is not “What AI tools should we use?” but “Is our culture ready for these tools, and if not, what do we need to build first?”
How to Know If Your Culture Can Handle the Shift
Here is a quick diagnostic, based on Chris Dyer’s 7 Pillars framework, that leaders can use to assess whether their organization’s culture is ready for AI adoption.
Transparency Test. When leadership last delivered difficult news, did people believe it? If your team has a history of hearing one thing from leadership and experiencing another, AI communications will be filtered through that same skepticism.
Listening Test. When was the last time a frontline employee’s concern visibly changed a decision? If your people do not believe their input matters, they will not share their concerns about AI. They will just quietly disengage.
Mistakes Test. What happened the last time someone on your team made a visible mistake? If the consequence was blame or embarrassment, your team will not experiment with AI tools. The perceived cost of failure is too high.
Acknowledgment Test. When you ask people to change how they work, do you first acknowledge the value of how they worked before? If not, every new initiative, including AI, feels like a criticism of what came before.
Positivity Test. Does your team generally believe that changes are made for good reasons? Or has a history of poorly handled transitions created a default assumption that new initiatives are just the latest thing leadership is excited about this quarter?
If an organization scores poorly on three or more of these, Chris recommends addressing the cultural foundations before pushing AI adoption. The technology will still be there in three months. The trust you lose by forcing adoption into a weak culture may take years to rebuild.
Frequently Asked Questions About Leading Through AI Disruption
How do I introduce AI to a team that is resistant to change?
Start by listening. Resistance is almost always a signal that a specific concern has not been addressed, not a sign that people are incapable of change. Identify whether the resistance is rooted in trust (Transparency), fear of failure (Mistakes), feeling unheard (Listening), or feeling undervalued (Acknowledgment). Address the root cause and the resistance often resolves on its own.
What is the biggest mistake leaders make during AI adoption?
Treating AI adoption as a technology rollout rather than a cultural transition. The tools are the easy part. Building the trust, communication, and psychological safety that make people willing to experiment with those tools is the hard part, and it is the part most organizations skip.
How can a keynote speaker help with AI adoption?
A keynote speaker who specializes in the human side of AI adoption, like Chris Dyer, can do something that no internal memo or training program can: create a shared experience that shifts how the entire organization thinks about the transition. When 500 people hear the same framework at the same time, it creates a shared language that makes subsequent conversations about AI easier and more productive. Chris Dyer’s keynotes on AI and change have helped organizations like NASA, Johnson & Johnson, General Motors, and ispot.tv navigate this exact challenge.
What is the Moments That Matter framework?
Moments That Matter is a framework developed by Chris Dyer and detailed in his bestselling book of the same name. It identifies seven moment types, Inception, Transition, Decision, Recognition, Connection, Truth, and Culmination, that carry disproportionate weight in how people experience leadership and change. During AI adoption, the most critical moments are Inception (how the change is announced), Transition (the disorienting space between old and new), and Decision (the calls leaders make about roles and workflows). Leaders who handle these moments well build trust that accelerates adoption. Leaders who mishandle them create resistance that persists long after the technology is in place.
How much does it cost to book Chris Dyer for an AI or change keynote?
Chris Dyer’s keynote speaking fee ranges from $15,000 to $25,000. Workshops and keyshops start at $25,000. All fees include a pre-event discovery call, full keynote customization, and the presentation. Contact 6 Degrees Speaker Management at shannyn@6degreesspeakers.com or call (888) 584-4177 to check availability.
What topics does Chris Dyer cover related to AI and change?
Chris Dyer’s most relevant keynotes for AI disruption include “AI and the Future of Work” (the human leadership challenge of technology adoption), “Thriving Through Relentless Change” (a culture-first approach to navigating transitions), and “Making the Most of Moments That Matter” (identifying the moments that define how people experience change). Each can be tailored to your organization’s specific AI adoption challenges. Visit chrisdyer.com to watch keynote clips.
Is AI really a culture problem?
AI adoption is a technology solution to a business challenge, but the success or failure of that adoption is determined by culture. Organizations with strong transparency, psychological safety, and communication practices adopt AI faster and with less disruption than organizations with weak cultural foundations. This is consistent with broader research on organizational change: the technology is rarely the bottleneck. The people and culture are.
Chris Dyer is a keynote speaker, 3x bestselling author, and former 5x Inc. 5000 CEO. He is ranked #1 Leadership Speaker on Culture by Inc. Magazine, #15 on the Global Gurus Top 30 Organizational Culture Professionals for 2026, and has been named a Top 101 Global Employee Engagement Influencer by Inspiring Workplaces for five consecutive years (2022 to 2026). He has delivered more than 300 keynotes in over 20 countries for organizations including NASA, Johnson & Johnson, General Motors, OnStar, MetLife, Intuit, IKEA, and Southwest Airlines. To book Chris Dyer for your next event, visit chrisdyer.com or contact 6 Degrees Speaker Management at shannyn@6degreesspeakers.com.
