AI is fundamentally reshaping business, pushing organizations to rethink how they adapt to rapid change. Leaders use AI to work more efficiently and generate faster insights, yet many struggle to align those gains with organizational goals. Organizations may have broad visions for AI’s strategic potential, but they struggle to connect that vision to the day-to-day work that makes an impact.
The missing link isn’t technology, it’s culture: helping people understand how their individual contributions connect to the organization’s collective mission, especially as AI changes what work looks like.
But what do we mean by culture?
Culture is the self-reinforcing web of beliefs, practices, and behaviors that drive how leaders and organizations make decisions and the way things get done. In short, culture makes strategy happen. For AI integration, understanding the relationship between AI & culture change is vitally important.
Why Is Culture Change Necessary for AI Integration
Successful AI adoption across an organization requires a collaborative culture. When individuals use AI in isolation, productivity gains stay isolated. When teams use AI collaboratively — sharing insights, challenging outputs, building on one another’s work — the impact compounds. That shift happens when senior leaders intentionally shape the culture to support AI integration.
We’ve spent decades researching organizational culture change, and our experience has given us insight into how organizations can successfully move toward more interdependent, collaborative ways of working that are better positioned to leverage AI’s potential. Senior leaders play a critical role: they model the behaviors, set the expectations, and create the conditions where interdependent leadership culture takes root.
In previous research, we identified 5 principles that increase the likelihood of successful culture change. Here, we apply those principles to help senior leaders shift workplace culture to enable effective AI integration.
5 Principles for Shifting Culture to Effectively Integrate AI
1. Culture change is a guided, public-learning process.
Senior leaders architect the organization’s AI strategy and play a pivotal role in aligning AI efforts with the organization’s mission, vision, and values. But strategy alone doesn’t drive adoption; transparency does. As senior leaders adopt AI, they must embrace transparency, openly communicate what’s working and what isn’t, and learn from missteps.
AI adoption creates uncertainty. Workflows change. Roles evolve. People worry about relevance. When senior leaders publicly navigate that uncertainty — sharing their own experiments, setbacks, and adjustments — they signal that it’s safe for others to do the same.
What this means for your organization: Be transparent about how AI is adopted and used.
- Clearly communicate guardrails for AI use.
- Model behavior by being open and vulnerable about what you and your organization are learning about AI, sharing personal successes / failures with AI.
- Keep messaging about AI’s role aligned to your organization’s mission.
By fostering a culture of open experimentation and communication, you can both proactively model the culture change needed and create an environment where it can thrive.
2. Senior leaders must do the change work first.
Our research of nearly 300 leaders over 2.5 years showed that teams with high degrees of psychological safety reported higher levels of performance and lower levels of interpersonal conflict. For AI adoption, creating psychological safety at work is critical: people need to feel safe with experimenting with new tools, admitting when they don’t understand how AI works, and challenging AI outputs without fear of judgment.
Senior leaders create that safety by going first. When they model new behaviors — using AI transparently, sharing their learning process, admitting when they need to adjust — they signal that experimentation is welcome. The rest of the organization watches what leaders do, not just what they say.
What this means for your organization: Model psychological safety and drive change by emphasizing 3 key areas: resilience, experimentation, and accountability.
- For resilience, help your organization understand how to weather disruption, whether that’s because of the impact of AI or the leadership needed to navigate polycrisis — the web of interconnected, interrelated challenges we face today.
- For experimentation, create space for new and potentially wild ideas, fostering a learning culture that’s willing to take risks and learn from mistakes.
- For accountability, take responsibility for integrating AI throughout the organization and be willing to admit when adjustments are needed.
3. Developing vertical capability transforms your leadership culture.
Individual AI skills matter — knowing how to ethically use the tools, write effective prompts, and validate outputs. But organizational AI adoption requires something deeper: a culture where leaders think differently, not just work differently.
This is called vertical development. It means developing more complex and sophisticated ways of thinking, greater wisdom, and clearer insights. It involves gaining new perspectives and leadership mindsets needed to make your organizational strategy work.
Without vertical development, leaders optimize their own productivity but miss how AI could transform collaboration, innovation, or strategy execution across the organization. They see AI as a personal efficiency tool, not as a lever for organizational change.
What this means for your organization: Develop and encourage the mindset to ask bigger questions.
- How does AI change how we collaborate?
- How do we balance individual AI experimentation with organizational alignment?
- What does it mean to lead when AI is reshaping workflows and roles?
Vertical development gives leaders the capacity to navigate these questions, which is especially helpful during culture change — not with perfect answers, but with the sophistication to hold complexity and guide the organization through it.
4. Leadership culture changes by advancing beliefs and practices simultaneously.
Real cultural shifts come from understanding how beliefs and behaviors shape and reinforce each other. New beliefs lead to new practices, which in turn reinforce or reshape beliefs, creating a continuous cycle. Senior leaders play a pivotal role in connecting and maintaining this cycle for their organizations.
What this means for your organization: You probably hear a range of beliefs about AI. Some leaders are skeptical, others see it as useful, and some view it as essential to productivity. Many leaders may already be integrating AI into their work and championing it to colleagues. But true cultural growth is unlikely to occur unless senior leaders harness the relationship between belief and action.
- Start with belief barriers: What explicit or implicit beliefs are holding your organization back? For example, does your organization have a culture of “not my problem” around certain issues or change initiatives? Do leaders view AI as someone else’s responsibility — IT’s job or the innovation team’s project — rather than a shared strategic priority?
- Then shift practices: If the belief is “AI isn’t my concern,” create practices that make it everyone’s concern. Require senior leaders to share how they’re using AI in team meetings. Build AI experimentation into strategic planning sessions. Make collective AI learning part of leadership development.
When beliefs and practices shift together, they reinforce each other. Leaders who experiment with AI develop new beliefs about its potential. Leaders who believe in AI’s strategic value create new practices to leverage it. The cycle compounds.
5. Managing culture change is a learn-as-you-go process, embedded in the work of the organization.
Organizations that want to adopt AI effectively need an agile, reflective approach to understand how AI is impacting the organization and what opportunities it creates. The same is true for culture change — it takes time, develops unevenly, and can’t be forced. Continuous learning is essential for navigating both, showing up at multiple levels:
- Individual: Leaders develop AI literacy, test and learn with new tools, and share insights.
- Team: Teams figure out how AI changes collaboration and innovation, and experiment with new processes.
- Organizational: The organization develops governance models, decides where to centralize vs. decentralize AI adoption, and adjusts strategy based on what’s working and what isn’t.
What this means for your organization: Ask questions and use the answers to derive deeper insights:
- How will your organization adapt to the impact of AI at different levels?
- How will it adopt AI strategically?
- What governance models will it develop to effectively harness AI across functions?
- Will a decentralized approach, where each function best determines how to incorporate AI into its work, be more appropriate than an organization-wide model?
Organizations committed to continuous learning will be more prepared to tackle these questions, learn from successes and missteps, and apply those lessons to future decisions.
From Strategy to Action: Integrating AI for Organizational Impact
Effectively integrating AI in your organization requires a leadership development strategy that connects individual leader performance to collective achievement. By pursuing a strategic approach to leadership that adopts AI as a transformative tool across individuals, teams, and the organization, you can expand mindsets, foster innovation, and propel organizational success.
Ready to Take the Next Step?
If you and the rest of the senior leadership team are ready to start transforming your organization, partner with the experts in our Organizational Leadership practice to assess the effectiveness of the executive team, evaluate your current and needed future leadership culture, and ensure it supports your business strategy and priorities.
