Building AI Leadership and Knowledge in Your Organization

11 Steps to AI Leadership

The future of leadership includes knowing how to build AI knowledge and culture into your company. You can’t delegate this. Not anymore. As AI reshapes industries, senior leaders must do more than observe. You need to engage. Not just with the technology, but with the people, the process, and the purpose behind it.

 

 

This is not about becoming a data scientist. It’s about building a leadership mindset that sees AI as a powerful tool for innovation, efficiency, and growth.

 

 

Here’s what I’ve learned from leading AI transformation in its early stages.

 

1. learn it yourself first

If you’re not curious, don’t expect anyone else to be. I started by using AI in small, personal ways. I would use it to analyze meeting notes, summarize articles, test new tools. Whether it is generating a document, creating a presentation, or writing a song, I used every app available. That hands-on experience gave me credibility and context.

You don’t have to master machine learning. But you do need to understand enough to ask smart questions and recognize smart answers.

 

 

 

2. make it part of your leadership conversations

Talk about AI in your exec meetings. Ask your team how they’re using it. Highlight real examples. The more it’s discussed, the less intimidating it becomes. Culture changes through repeated, consistent signals.

I often ask: “How could AI make this faster or better?” That one question reframes the conversation.

 

3. train everyone, not just the tech team

Big learning: AI is not an IT initiative. It touches marketing, legal, operations, sales, finance. It touches everyone in every department. We built a learning journey for our entire company, starting with basic AI literacy and then offering deeper tracks.

We used internal sessions, LinkedIn Learning, vendor-led classes, and open dialogue. AI lunch and learns. Experiment showcases. Office hours. AI hackathons.

 

4. create space for experimentation

If you punish people for trying new things, they’ll stop. Give teams permission to experiment. Low-risk, low-cost trials. Some failed. Some led to breakthroughs. We shared successes and lessons learned across departments. That cross-pollination made all the difference.

 

5. reward curiosity and initiative

Someone on your finance team builds a new AI model to forecast trends. Recognize it. Someone in HR tests AI to draft job descriptions. Applaud it. Curiosity is contagious (if it’s noticed).

Leaders shape culture by what they praise, question, and invest in.

 

6. build governance without killing momentum

AI needs boundaries…ethics…guardrails. But it also needs momentum. We formed an AI working group early on with voices from legal, compliance, IT, and business units. They helped shape policies we could live with—not just write down.

Don’t let compliance be a blocker. Make it a partner.

 

7. show what good looks like

Your team is watching. When I shared how I use AI to prep for speeches, develop strategy, or even to create headshots, it gave others permission to try. A CEO using it signals it’s safe to explore.

 

8. invest in scalable tools

Free tools are fine to start. But at some point, you need enterprise-grade systems that protect your data and scale across the business. We invested in platforms that integrated with our systems and made adoption easier.

Don’t expect momentum if the tools are clunky or siloed.

 

9. bring in outside voices

I am regularly talking to AI thought leaders and other CEOs. One conversation with a startup founder sparked an idea. You never know where it will come from, but here’s what I have learned: don’t build your AI future in isolation.

 

10. align AI to your mission

Every AI conversation comes back to this: What are we trying to do for our users? Our communities? Our purpose? If AI doesn’t connect to your mission, it will drift into gimmicks or confusion.

Tie every experiment, every investment, every story back to your values.

 

11. repeat it often

This is not a one-off campaign. Building AI literacy and culture is an ongoing effort. Keep talking about it. Keep learning. Keep experimenting. We’re not close to being done – we are just starting.

I am a student of AI and am learning every single day.

Eventually, AI will stop being a topic and just become part of how you work.

And that’s when you know the culture has changed.

 

 

 

 

 

 

Image Credit: mayukh karmakar and badea iowana