It started with my calendar.
I was exhausted. Not from overwork, but from the wrong tasks. I had another week full of back-to-back meetings, conflicting priorities, and endless context switching. I felt busy but ineffective, productive yet unfulfilled.
Life is busy for me right now. A startup, young family, relationship time, personal time, home commitments, and little space to stay fit, eat healthy and remain focused on what matters.
Every Sunday night, I’d spend an hour manually optimizing my schedule for the week ahead. I’d block “thinking time” I rarely protected. I’d try to carve space for strategic work. But by Wednesday, it always unraveled into reactive chaos.
Then one day, I decided to test something.
I uploaded my calendar to an AI scheduling agent and asked it to reorganize my week for optimal focus, creativity, and leadership leverage.
Within seconds, it responded:
- It deleted 40% of my meetings.
- It grouped similar activities into focus blocks.
- It added protected time for reflection, strategy, and decision-making.
- It suggested I delegate three standing meetings I’d stubbornly held onto.
I stared at the screen—half impressed, half offended. This machine didn’t know me. Who was it to tell me how to lead my week?
But I was curious. So I tried it for one week, and the results were extraordinary.
I made better decisions. I had more energy. I ended the week feeling accomplished, not depleted.
And perhaps most importantly: I realized I wasn’t the only person that needed to decide how I should spend my time.
That moment kicked off something deeper. A mindset shift. I started asking questions I hadn’t before:
- What else am I holding onto that I should hand off?
- Where am I the bottleneck?
- Which decisions could machines make better than me?
This wasn’t just about productivity. It was about leadership.
The kind of leadership required to thrive in an AI-native world isn’t about having all the answers, it’s about knowing which decisions to let go of.
What habits of my past, and holding me back from a better future?
Let me break down what it takes to become an AI-native leader:
- The traits you need to unlearn and relearn
- The tasks you should stop doing (and start delegating to AI)
- The tools that help you lead more effectively
Because if we want to lead in the future, we can’t just add AI to our workflow.
We have to let AI change how we decide.
The Traits of AI-Native Leaders
An AI-native leader doesn’t just “use AI”, they design their leadership style around it. This demands a fundamental transformation of self, especially in how decisions are made, who makes them, and what role the leader plays in a machine-augmented world.
1. Coach over Commander
In traditional hierarchies, leaders gave orders. In AI-native organizations, the best leaders guide systems—human and machine—toward clarity and purpose. They build the environment, not dictate the execution.
→ Mindset shift: You’re no longer the bottleneck for decisions. Let go of being the “smartest person in the room” and become the one who orchestrates intelligence across people and machines.
Quick example? Planning for an AI-Augmented Strategy Session. My dated mindset on planning was that you set a strategic direction, set KPIs, build the roadmap (often alone), spend hours crafting timelines, and make all final calls.
Today? Well, I feed my goals into an AI planning agent. It drafts multiple strategic scenarios, highlights risks, and suggests resourcing trade-offs. Now I meet with my team to discuss and curate the best direction together based on the various scenarios, options, and choices.
I’m no longer solving the entire puzzle. We’re reviewing the options and guiding the narrative.
2. Curious over Certain
AI-native leaders cultivate the courage to say, “I don’t know, let’s explore.” Instead of clinging to what’s worked before, challenge your assumptions, test faster, and embrace continuous learning as your superpower.
→ Unlearning needed: Certainty and expertise can become liabilities. The faster the world moves, the more dangerous old playbooks become. AI gives us capabilities to explore many options, cheaper, faster, and deeper than before. Why not leverage it instead of relying solely on what you know.
3. Transparent over Tactical
Trust is no longer just built through charisma—it’s built through clarity. AI-native leaders communicate why decisions are made, what data was used, and where human judgment fits in.
→ Decision-making upgrade: You’re not hiding behind data. You’re helping teams understand how to collaborate with it, critique it, and ultimately, improve it.
I wrote about this 5 years ago in Good To Great Decisions. Learning to recognize the difference between the quality of decisions, the quality of results, and chance is a powerful perspective to improve our outcomes.
When we have this mindset, we can intentionally improve our decision-making systems and subsequent outcomes over time through reflection, refinement, and deliberate practice. AI can help you design, improve, and iterate your decision-making system.
The Tasks of AI-Native Leaders
Leading in an AI-native world is not about delegating everything to machines. It’s about reconfiguring what only humans can do and building systems that extend those strengths at scale.
1. Designing Decision Loops
Old task: Make the decision.
New task: Design the system that makes decisions.
AI-native leaders focus on building high-quality decision frameworks, systems where data flows, feedback is fast, and humans and machines learn together. They obsess over how decisions are made, not just what gets decided.
→ Mindset shift: You’re not here to make every decision. You’re here to architect better decisions. And you can show your work to everyone on how you come up with your conclusion. DO IT!
2. Allocating Human Attention
With AI handling the mundane, leaders must become stewards of focus. What gets human attention? Where is judgment still needed? What requires creative insight or ethical consideration?
→ Unlearning needed: Just because something lands on your desk doesn’t mean you need to do it. Your new value lies in deciding where human capacity matters most.
Context switching is one of the largest hidden costs in work. If AI understands your working style, how you want to work, and when you want to work, it’s a game changer. I batch similar tasks in timeboxes once the machine knows the class of work. It’s easier to find flow and get more throughput.
3. Creating Cultures of Experimentation
AI-native leaders build environments where it’s safe to test, fail, and learn fast. They prioritize progress over perfection and embed experimentation into daily operations.
→ Decision-making shift: Stop asking for business cases before you try something. Start making micro bets and learning your way forward.
Every week in our company, we encourage people to try a new trait, automate a task, or experiment with a tool before sharing it back with the rest of the team. The insights, knowledge created, and bar lifting that happens are quite extraordinary.
The Tools of AI-Native Leaders
AI-native leadership is not only a mindset shift, it’s a toolset update too. These leaders don’t wait for enterprise solutions to catch up. They roll up their sleeves and build the workflows of the future, today.
1. Personal Intelligence Stack
AI-native leaders design a personalized AI stack—agents for writing, summarizing, scheduling, recruiting, researching, and decision-support. These aren’t toys. They’re teammates.
Last week I had dinner with a friend. He’s leading a scaling business. Each Sunday, he has an agent that runs across each team to see if they submitted weekly reports for Monday morning’s meeting. The agent goes through Slack, their PM tool, and team email lists. It aims to synthesize all the information into an agreed format, and republishes it on Slack first thing on Monday to say, does this reflect what you’ll share in the meeting today?
He says Monday morning meetings have never been so good in his entire life, and the team says the same too.
→ Toolset tip: Don’t delegate adoption. Get hands-on. Try everything. Build workflows around what actually improves your decisions, not what’s trendy.
2. Augmented Team Collaboration
Rather than Slack and Zoom being the only digital interfaces, AI-native teams integrate live summarizers, insight extractors, and agents that track priorities, deadlines, and mood. They treat AI as another participant in the team—one that never sleeps.
→ Unlearning needed: You don’t just assign work to people. You assign work to systems—human and machine alike. Use tools that work well for you, and AI agents to pull them together.
3. Decision Auditing and Feedback Systems
AI-native leaders use tools like decision journals (powered by AI), retrospectives on past moves, and real-time dashboards to measure decision quality. Every decision is a data point for improvement.
→ Mindset shift: Winning isn’t about being right in the moment. It’s about building a system that gets smarter over time.
Final Reflection: Unlearn to Relearn
The leaders who thrive in this era are not those with the most experience. They’re the ones most willing to let go of how they succeeded in the past to achieve extraordinary results.
In Unlearn, I wrote: “Success is often the greatest inhibitor to future success.”
That rings more true now than ever. AI-native leadership is about letting go of old models—not because they were wrong, but because they’re now irrelevant.
You don’t need to become a prompt engineer.
You don’t need to become a product manager.
You need to become a possibility architect.
Ask yourself:
- What am I holding onto that once made me successful, but now holds me back?
- Where do I resist AI, not because it won’t help, but because it threatens my identity?
- What decisions am I still making manually that a machine could handle, or even improve?
Ready to Go All-In?
As our AI Technology Leader at Nobody Studios, Jeremy Shankle said in our podcast conversation, “Once I went all-in on AI, I didn’t just change how I worked—I changed who I was.”
This is your call to go all-in.
Experiment. Explore. Unlearn.
Because the future doesn’t belong to the best predictors.
It belongs to the best adapters.
If you’re a leader ready to make the mindset shift, I’ve created a free diagnostic to help you map where to begin. Because becoming AI-native isn’t just about using the tools—it’s about becoming the kind of leader the future needs.