How leaders can become AI fluent on the job

According to McKinsey, while more than 75% of organizations now use AI in at least one business function, only 1% describe themselves as fully “mature” in their deployment—and most executives still don’t feel confident leading it. Fluency, not just familiarity with AI, is the next big leadership gap.

I’ve spent three decades guiding leadership teams, government departments, and boards through the endless waves of emerging tech. If there’s one thing I know for sure, it’s this: Capability doesn’t come from dashboards or demos. It comes from shared language, strategic alignment, and the confidence to make informed decisions. 

Many of the executive teams I have AI discussions with remain fluent in all the right buzzwords, but lack the depth of understanding to turn shiny new tech into scalable, sustainable outcomes. With AI moving from nice to necessity, it’s time to steer the conversation in a new direction. Here’s how leaders can do it. 

1. More Talking Before Testing

AI fluency begins with conversation, not capability statements. Too often, leadership teams rush into pilots or platform demos before having the foundational discussions that guide responsible, effective use. If you want your team to lead with clarity, start by asking these questions:

• Governance: How are we managing AI risk and accountability?
• Customer impact: Where could AI enhance or erode trust?
• Workforce: What skills do we need to build, shift, or unlearn?
• IP and data: Who owns what we create? How are we protecting it?
• Ethics: Are our use cases aligned with company values?

These aren’t nice-to-haves. They’re essential questions, core to any organization’s resilience and relevance strategy. Skip them, and you risk building tools your team doesn’t understand and your clients don’t trust.

2. Run Fire Drills, Not Just Workshops

AI is moving faster than most leadership teams can process. That pace creates blind spots, and blind spots turn into problems. 

To stay relevant in an AI-driven world, you need a way to surface risks early.  Easiest way to do that? Start with a fire drill. 

Pick a scenario. Maybe your customer data is used without permission to train a public large language model. Or your chatbot starts making promises your business can’t afford to keep. Then, as you would for any contingency or risk mitigation plan, ask: How would we respond? 

This kind of simulation forces teams to make decisions under pressure. It reveals knowledge gaps and helps connect abstract AI risks to real world consequences. You don’t need to overengineer it. A whiteboard, some honest questions, and the willingness to sit with discomfort is enough. You won’t have all the answers, but you need to start probing.

3. Fluency Over FOMO

There’s mounting pressure on businesses to “do something with AI.” But when action is driven by FOMO, it usually results in shallow pilots, disconnected tools, or AI bolted on as an afterthought. That’s not strategy. And it’s certainly not sustainable. Fluency reframes the conversation.

The question isn’t “What can we automate?” It’s “What problem are we solving, and is AI the best tool for the job?”

Teams focused on fluency build slower, but smarter. They make better investment decisions, ask sharper vendor questions, and develop solutions that flex, scale, and last.

4. Make It Cultural, Not Just Strategic

AI capability isn’t something you tack onto operations. It must be baked into the way your organization thinks and acts. That means:

• Making AI literacy part of team member onboarding
• Reviewing how AI influences customer experience, products, and services
• Treating AI risk with the same weight as cyber risk, including shared accountability at the leadership table
• Creating space in board and executive agendas for regular AI discussions

One-off strategy days won’t cut it. Organizations that take AI seriously embed fluency in their culture, not just their calendar.

5. Ditch the Jargon, Lead With Questions

You don’t need a PhD in machine learning to lead confidently in this space. But you do need curiosity, courage, and a commitment to ongoing learning. Start by ditching the jargon. That creates space for honest, useful conversations. Encourage reverse mentoring. Trial tools together. Normalize not having all the answers. AI isn’t the next department or the next fad. It’s the new business as usual.

Leadership teams willing to sit in the unknown, learn the new language of business, and ask better questions will unlock opportunities others never see. The rest risk becoming irrelevant.