So many leaders I talk to right now are asking some version of the same question: how do we lead when the world is changing faster than the map can be drawn? That question feels especially urgent when we talk about AI.
AI is no longer a future topic. It is already shaping how we work, how we make decisions, how we learn, how we serve customers, and how organizations think about productivity and transformation. And yet, even as the tools become more powerful, many leaders are still trying to understand what all of this means for their people, their teams, and their own leadership.
That is why I was so excited to sit down with Michael Park, Senior Vice President of Global Partnerships and Channels at ServiceNow. He has also served as ServiceNow’s Chief Marketing Officer and led the company’s first dedicated AI go-to-market function. Over the last several years, AI has been at the center of his work, not as an abstract concept, but as something he is actively helping organizations understand, adopt, and integrate.
Michael is helping create the map while the terrain is still moving. And yet, the conversation was not only about technology. It was about the human capabilities that become even more important in a time of rapid transformation: action, learning, trust, gratitude, patience, and connection.
Action Before Certainty
One of the strongest themes in our conversation was Michael’s belief in taking action before certainty, which can be hard for leaders. Many of us were trained to gather enough information, build the right plan, reduce risk, and then move. Of course, data still matters. Thoughtfulness still matters. But in a world where technology is changing quickly and the “right” answer may not be obvious for long, waiting for perfect certainty can become its own kind of risk.
Michael described leadership in this moment as requiring movement even when the picture is incomplete. That does not mean acting recklessly. It means developing the capacity to make thoughtful moves, learn quickly, and adjust as the environment changes.
This is especially important with AI. The organizations that wait until everything feels clear may find that the landscape has already shifted again. Leaders do not need to know every answer before they begin. But they do need to start building fluency, experimenting responsibly, and helping their teams learn alongside them.
There is a kind of humility in that. It asks leaders to admit that they do not have the whole map. But it also asks them not to freeze. In uncertain moments, leadership is often less about having absolute confidence and more about creating enough clarity for people to keep moving.
AI Fluency Is Becoming a Leadership Skill
Michael talked about AI fluency as something leaders can no longer delegate entirely to technical teams. That stood out to me.
Leaders do not need to become engineers overnight. They do not need to understand every technical layer of every tool. But they do need enough fluency to ask better questions, make better decisions, understand the risks and opportunities, and model the kind of learning they want from others.
That last piece feels especially important. If leaders want their organizations to use AI thoughtfully, they need to show that they are also learning. Michael shared how he uses AI tools in his own work, including for executive briefings and staying current. That kind of modeling matters. People notice whether leaders are asking others to change while staying personally removed from the learning themselves.
AI fluency is not only about tool adoption. It is about mindset. It is the willingness to stay contemporary, experiment, build judgment, and understand where human expertise is still essential.
In fact, one of Michael’s clearest messages was that domain expertise matters more, not less, in the age of AI. The better we understand our field, our customers, our work, and our people, the better we can use AI as a partner rather than a replacement for human judgment.
Domain Expertise Still Matters
There is a common fear that AI will make human knowledge less valuable. Michael offered a more nuanced and, I think, more useful view.
AI can help us move faster. It can summarize, synthesize, draft, analyze, and support decision-making in powerful ways. But the quality of what we do with AI still depends on the quality of our judgment. And judgment is shaped by domain expertise, lived experience, pattern recognition, and the ability to understand context.
If we treat AI as a shortcut around expertise, we may weaken the very capabilities that help us use it well. But if we treat AI as a tool that can amplify expertise, then the goal becomes different. We are not asking, “How do we replace what people know?” We are asking, “How do we help people bring what they know to more complex, creative, and meaningful problems?”
That distinction matters for the next generation of workers too. Michael spoke about the importance of problem-solving, creativity, and learning how to manage through obscurity. Those are the capabilities people will need as the future of work continues to evolve. Technical fluency will matter, but so will curiosity, adaptability, and the ability to keep learning when the answer is not immediately obvious.
The Human Side of AI Readiness
Michael kept bringing the topic back to people. AI transformation is often discussed in terms of tools, platforms, workflows, productivity, and efficiency. All of that matters. But organizations do not transform simply because new technology is available. They transform when people understand why it matters, how it connects to their work, and what role they can play in the change.
Human readiness means people are not simply told to adopt something new. They are brought along. They are given context. They are invited to learn. They are supported through uncertainty. They are allowed to ask questions and build confidence over time.
This is where leadership becomes less about announcing change and more about creating the conditions for change to take root. It requires trust. It requires communication. It requires patience. And it requires an understanding that people adapt at different speeds.
For leaders, the challenge is to move in a way that others can follow.
Gratitude as a Leadership Practice
I loved that Michael brought gratitude into a conversation about AI and transformation. At first, gratitude may seem like a separate topic from technology. But the more we talked, the more connected it felt. When the pace of change is fast, it is easy for leaders to become consumed by what is missing, what is urgent, and what is not yet solved. Gratitude helps reframe the lens.
Michael spoke about gratitude as part of his own leadership development. It helps him stay grounded. It helps him see what is working, not only what needs to be fixed. It helps create a different internal state from which to lead.
That matters because leaders transmit more than strategy. They transmit energy. They transmit urgency, anxiety, confidence, frustration, hope, and steadiness. When leaders cultivate gratitude, they are not ignoring the difficulty of the moment. They are building the capacity to hold both reality and appreciation at the same time.
In positive psychology, we know that gratitude can support well-being, broaden perspective, and strengthen relationships. In leadership, that can become a very practical advantage. A grateful leader may be better able to notice effort, recognize progress, and create an environment where people feel seen during times of change.
Actionable Leadership Lessons from Michael Park
What I hope leaders take from this conversation is that AI readiness is not only about technology readiness. It is about leadership readiness. It is about whether we can stay curious, grounded, and connected while moving through uncertainty.
A few practical lessons stood out:
- Begin before you feel fully certain. Choose a responsible place to experiment with AI, learn from it, and refine your understanding. Waiting for total clarity may feel safer, but it can keep you and your team from building the fluency you need.
- Strengthen your domain expertise. The more you understand your work, your field, and your customers, the more effectively you can use AI as a tool for judgment, creativity, and problem-solving.
- Model the learning you want to see. If leaders want their teams to adopt AI thoughtfully, they need to demonstrate their own willingness to learn, experiment, and stay current.
- Invest in human readiness. Communicate the why. Make space for questions. Recognize that people have different levels of confidence and concern. Bring people along rather than simply pushing change onto them.
- Practice gratitude and patience. These may sound simple, but they are powerful leadership practices in a fast-changing world. They help leaders stay grounded, notice what matters, and create the kind of trust that makes transformation possible.
Staying Human While the Work Changes
For me, the heart of this conversation is that the future of work is about how we choose to lead as AI becomes part of the fabric of work.
Technology will keep changing. The pace will keep challenging us. New tools will continue to emerge. But the human work of leadership remains essential.
People still need trust. They still need clarity. They still need relationships. They still need leaders who can act before certainty without pretending to have all the answers. They need leaders who can move fast and remain patient. Leaders who can embrace technology and still center human connection. Leaders who can learn continuously without losing sight of what makes work meaningful.
Michael reminded me that the leaders who thrive in this next era will not be the ones who wait for the future to become perfectly clear. They will be the ones willing to engage with it, learn from it, and bring others along with both courage and care.
That feels like a deeply human way to think about AI. And it feels like exactly the kind of leadership we need now.
