Ten Leadership Lessons for Generative AI

How Personal Experience and Leadership Principles Empower Effective Work with AI

About two and a half years ago, during an Information Systems class early in my MBA program, my professor introduced us to ChatGPT. At the time, artificial intelligence felt distant from my studies. If someone had predicted I'd dedicate thousands of hours to exploring AI without a clear endpoint, purely out of curiosity, I wouldn't have believed them.

Yet, that's precisely what happened. This journey led to a surprising discovery: my background in leadership, shaped by experiences like military service, offered more practical value for working effectively with AI than any specific technical skill I possessed. It turns out that fundamental human principles provide a powerful compass for navigating this rapidly evolving technological landscape.

Here are ten key lessons from my leadership experience that have proven invaluable in engaging with Generative AI:

1. People Remain Central: The old adage "People are our most valuable resource" holds true. No matter how advanced AI becomes, critical human judgment is always required—whether setting goals, defining processes, or making the final call. Technology assists, but people direct.
2. Find Your Own Center: Good leaders identify unique strengths. Similarly, LLMs adapt to the individual user, placing you at the center of your unique capabilities and interests, rather than forcing you into a predefined box.
3. Beware of Shortcuts: Just as tempting shortcuts in difficult terrain often lead to dead ends, seeking quick AI solutions without true understanding can have significant long-term costs. Thoroughness prevents costly detours.
4. Embrace Responsibility: If an AI-assisted task fails after inadequate review, the fault lies with the user, not the tool. Owning the outcome and maintaining high standards for verification are fundamental, regardless of the technology used.
5. Keep It Simple: Military strategy values simplicity, especially under pressure. With AI, there's a risk of overcomplicating tasks. Often, the most effective approach is the simplest and clearest one.
6. Question Everything: AI models can be persuasively confident, even when wrong. Like vetting information from any source, critically evaluating AI outputs—even asking "Are you sure?"—is a mark of professional diligence.
7. Adapt Constantly: As in poker, thinking you've mastered the game is the biggest mistake. The AI field changes constantly; continuous learning, flexibility, and the resilience to adapt are essential for staying effective.
8. Prioritize with Courage: Leadership involves focusing limited resources on what matters most. With countless AI tools available, success comes from strategically choosing where to invest your attention and effort.
9. Trust Your Gut: Experience builds intuition—an unconscious competence. AI analyzes data, but it lacks human instinct. Trust your experience-based gut feelings, especially when they diverge from a purely data-driven suggestion.
10. Believe in Yourself: Authenticity is key. Following your genuine curiosity and passion, as I did with AI, often leads to the most meaningful learning and growth. Be determined in your pursuit of understanding.

Ultimately, the rise of Generative AI reinforces the enduring value of human qualities. Critical thinking, adaptability, responsibility, and sound judgment are more important than ever. As we integrate these powerful tools, our own principles and intuition remain our most crucial guides.

What unexpected skills or past experiences have you found surprisingly relevant in navigating new technological frontiers?

"If you are not willing to learn, no one can help you. If you are determined to learn, no one can stop you." - Zig Ziglar