Machines do.
Use AI to organize context, suggest questions, and help you prepare for the human work of leadership.
- →Keep shared goals in view
- →Prepare thoughtful questions
- →Surface assumptions
- →Support follow-through
Frontline AI Leadership
Machines do. Managers decide. Leaders develop.
Leadership means understanding what matters to someone and helping them take the next step. Jon shows how AI can support that work: preparing a coaching conversation, challenging an assumption, noticing a contribution, and remembering a commitment. The relationship and responsibility stay with the leader.
The framework
Use AI in service of the people you lead.
Machines do. Managers decide. Leaders develop. Each part supports a clear purpose: helping leaders pay attention, act with judgment, and invest in another person's growth.
Managers decide.
AI can recommend. Human managers still own judgment, context, boundaries, and consequences.
- →Verify the output
- →Add the context
- →Know the boundary
- →Own the consequence
Leaders develop.
Use that preparation to listen, coach, recognize contributions, and help people grow toward goals that matter to them.
- →Listen before judging
- →Recognize specific contributions
- →Follow through on commitments
- →Develop the next leader
Leadership in practice
Remember what matters to your people. Follow through.
Jon uses AI to keep individual goals in view and notice people who may be overlooked. His leadership approach turns that context into preparation for coaching, recognition, and development conversations. The leader listens, checks assumptions, and takes responsibility for the next step.
Explore the goals and coaching practiceA documented leadership practice. Employee-development outcomes have not yet been measured.
What leaders can apply
Prepare to understand.
Start with what a person has shared. Use AI to suggest questions and surface assumptions worth checking.
Recognize with evidence.
Look for a specific contribution. Verify the context and deliver the recognition personally.
Follow through.
Keep an agreed development goal and your own next commitment in view. Return to the conversation.
The human part
Better preparation. A more thoughtful conversation.
Before a difficult conversation, use AI to consider another perspective and examine the assumptions in your first draft. Then ask the person what you are missing.
Before a development conversation, revisit a goal the employee has shared and prepare questions about the support they need. Agree on a next step together and make your own commitment explicit.
Human Reinvestment gives this work a place on the calendar. When AI also saves time, use some of that time for listening, coaching, and following through.
The question to take back to work
Who needs your attention, what do you need to understand, and what have you promised to do next?
Built for people-intensive organizations
Franchise systems and multiunit operators
Restaurants and hospitality
Retail
Healthcare
Manufacturing and logistics
Distribution and field services
Trade associations and leadership conferences
Why Jon
Jon Harmeling is a West Point graduate, former West Point systems engineering instructor, Army veteran, and Chick-fil-A Operator. He applies AI inside a real frontline business with real employees, customers, and P&L pressure.
The keynote draws on his use of AI to track individual goals, surface overlooked contributions, and examine his own leadership questions. He shares the practices, their limits, and the decisions a leader must still make in person.
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