“We’ve got a team on it”: Why AI Needs Your Leadership - Not Just Your Delegation
- Liza Engel
- Sep 15
- 3 min read
“AI is important - we’ve got a team on it.”
An innovative, capable leader recently told me this, and it’s something I often hear: delegate AI to a specialist group while leadership stays focused on the “real” work.
But here’s the risk: when leaders stay too far removed, they miss the opportunity to build their own clarity, confidence, and vision in an area fundamentally reshaping how we work and lead.
The Context Leaders Are Facing
Leaders today are navigating a fast-changing AI landscape while still delivering on the fundamentals: developing people, managing costs, and ensuring resilience. It’s tempting to hand off AI entirely to an innovation team.
But doing so can unintentionally signal: “This isn’t my domain.”
The alternative isn’t to master AI overnight or launch a flawless transformation. It’s to start small - with manageable yet meaningful experiments. Each becomes part of an ongoing learning cycle, not a final destination.
Core Ideas to Guide You
Reframe What It Means to Be “Expert”
Your role isn’t to master every tool. It’s to ask good questions:
Where could AI reduce friction in my team’s work?
What repetitive tasks could be reimagined?
Where might speed or insight create real value?
Try Meaningful Experiments
1. Team Development
Invite a team member to use an AI tool to draft an agenda, summarize notes, or brainstorm ideas. Reflect together: What worked? What didn’t? What would you do differently next time? This builds capability, curiosity, and confidence.
2. Workforce Management
Use AI to test “what if” scenarios: What if demand grows 10%? What if costs rise 5%? It’s not about perfect predictions - it’s about sharpening your planning muscle through continual exploration.
3. Cost Structure
Ask AI to analyze your reporting, procurement, or scheduling processes. Even modest gains here can free up resources for higher priorities. The goal isn’t perfection - it’s progress.
Lead with Responsibility
Every experiment should include a pause: What risks might we be missing? Responsible leaders balance curiosity with care - for trust, fairness, and long-term impact.
And by framing experiments as iterative, they normalize what outstanding leadership often looks like in fast-changing times: test, learn, adjust, repeat.
A Simple Framework to Start
Use the 3C Framework to shape your AI experiments:
Curiosity - Frame each experiment as a question, not a solution.
Collaboration - Involve your team so learning spreads.
Calibration - After each step, assess what worked, what didn’t, and where to go next. Progress through iteration, not perfection.
The Leadership Stretch
AI is no longer just the domain of specialists.
As a leader, your stretch is to explore - not once, but consistently - in practical, purposeful ways. When you model iteration over perfection, you show your team what modern leadership looks like: not knowing everything, but learning with intention.
Power Prompts to Start Right Now
Not sure where to begin? Use these two prompts - one for your team, and one for your AI tool - to take a meaningful first step.
For Your Team
Ask in your next meeting:
“If we had to use AI to make one part of our work 10% faster, easier, or smarter - where would we start?”
Use this to surface practical opportunities and build shared ownership of the learning journey.
For Your AI Tool
Ask your next chat:
“What are three ways we could use AI to improve [insert team process, e.g., customer onboarding/reporting/meeting prep] by 10% - in speed, quality, or insight?”
This keeps the focus on incremental value and encourages action, not abstraction.
Start small, learn fast - the journey is on!
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