Can You Lead AI Without Using It Yourself?
1. The Trust Gap Between Strategy and Hands-on Experience
Explaining an AI strategy and approving budgets are not enough to understand the realities a team faces.
- Leaders who have not used AI in their own work struggle to discuss errors in its output or practical difficulties in using it.
- As this gap grows, teams lose trust in priorities and start working around leaders instead of sharing problems.
2. AI Is a Technology You Need to Use to Judge
AI is a tool people work with directly, and the same request can produce different results.
- Leading AI adoption requires personal experience alongside the approaches used for cloud or ERP transitions.
- Repeated use helps leaders learn what to trust, what to verify, and when to bring in human judgment.
- As capabilities change rapidly, regular briefings alone cannot keep leaders up to date on practical possibilities and limitations.
3. Judgment Changes More Than Efficiency
Building an inventory analysis tool with AI changed the author’s criteria for assessing investments and proposals.
- Working with real data showed him where AI could extend analysis and where an experienced practitioner’s judgment was needed.
- This experience made investment priorities, vendor proposal reviews, and conversations with the team more concrete.
4. Try It on the Work You Know Best
Leaders need to experience AI in work that puts their expertise to the test, beyond drafting emails or summarizing meetings.
- Apply it to work you are directly responsible for, such as strategy reports, important analyses, or reconciling competing interests across departments.
- Reviewing the results reveals both AI’s limitations and where your own judgment holds up or needs to change.
