Latest / Executive Careers with Fexingo: VP, C-Suite, and Senior Leadership Career Strategy / How Senior Leaders Use AI as a Career Accelerator
Transcript
- Lucas: So there's this idea in chess called a 'rook' — a piece that becomes exponentially more powerful as the board opens up. I've been thinking about how senior leaders can create a similar effect with AI. Luna: A rook? As in, a career rook — not a chess rook? Lucas: Exactly the same word, but I mean it as a metaphor. A career rook is a capability or tool that gives you disproportionate leverage as the landscape shifts. And right now, AI is the rooks' rook. Most executives I talk to are either delegating AI to their teams or treating it as a productivity hack. Very few are building a personal AI capability that makes them indispensable. Luna: So you're saying the real career play isn't 'learn to use ChatGPT' — it's 'build something with AI that only you can do'? Lucas: That's exactly it. Let me give you a real example. I've been following a chief marketing officer at a mid-cap consumer goods company. Let's call her Sarah. She spent about three months teaching herself how to fine-tune a large language model on her company's customer service transcripts, product reviews, and social media comments. Luna: Three months is a big time investment for a CMO. What was the payoff? Lucas: She built a custom sentiment analysis tool that could identify emerging brand perception trends in 48 hours — whereas her team used to take three weeks with external consultants. But here's the career-relevant part: she didn't just use the tool. She became the only person in the company who could interpret its outputs and connect them to strategy. The board noticed. Six months later, she was invited to join the board of a portfolio company. Luna: So the AI wasn't the differentiator — it was the combination of the AI and her domain expertise. She created a bottleneck of insight. Lucas: Exactly. She built a monopoly on understanding something critical. And because the tool was proprietary to her, she couldn't be easily replaced. That's the rook: a capability that scales with your judgment, not against it. Luna: How did she frame it to the board? I imagine saying 'I built an AI tool' might come across as a technical sideline. Lucas: She framed it as a strategic capability. She presented it as: 'Our customer intelligence cycle is now compressed from weeks to days, and I can now give you real-time guidance on brand risk and market positioning.' She didn't say 'I learned Python.' She said 'I've created a decision advantage.' Luna: That framing is everything. The board doesn't care about the tool — they care about the outcome. Speed, accuracy, reduced dependency on outside vendors. Lucas: Right. And that's the play for any senior leader. Pick a domain where you already have deep expertise — legal, finance, supply chain, whatever — and build a custom AI application that gives you a unique view. Not a generic tool, but something that embeds your judgment. Luna: Let's talk about the adoption gap. I'm seeing a lot of executives who are intimidated. They feel like AI is for data scientists or the IT team. Lucas: That's exactly the opportunity. The C-suite adoption curve is still early. A McKinsey survey from late 2025 showed that only about 12 percent of senior executives had personally built or customized an AI tool. The vast majority are consumers, not creators. That gap is a window. Luna: So the first mover advantage is real. But what about the risk? What if you build something and it gives wrong outputs, or it breaks, or the company decides to standardize on a vendor tool? Lucas: Those are real risks. But I'd argue the bigger risk is doing nothing. If you wait for the company to adopt an enterprise AI solution, you become a user — not a leader. And users are replaceable. The leaders are the ones who shape how AI is applied in their domain. Luna: That reminds me of something. A CFO I know — he built a custom tool to analyze the company's contract database. He used a no-code platform, not even coding. He could ask natural language questions like 'Which contracts have renewal clauses that expose us to currency risk?' and get answers in seconds. Lucas: Perfect example. He didn't need to be a software engineer. He needed to understand the business question and know how to frame it. And now he's seen as the go-to person for contract intelligence. Luna: And that visibility leads to career growth. I think we're getting to a point where not having a personal AI capability is going to be a red flag on a senior executive's profile. Lucas: I agree. Let me zoom out a bit. The most important career asset for a senior leader is what I call 'interpretive authority' — the ability to make sense of complex information and guide decisions. AI, used strategically, amplifies that authority. It doesn't diminish it. Luna: So how should a listener start? Let's say they're a VP of HR or a head of strategy. They've never touched AI beyond using ChatGPT for emails. Lucas: Start with a pain point. What's a question you get asked repeatedly that takes you days to answer? For an HR leader, maybe it's 'What's our retention risk by department?' For a strategy head, maybe it's 'How do our competitors' pricing changes correlate with our market share?' That's the seed. Luna: And then what? Do they need to learn to code? Lucas: No. Most of the tools today are no-code or low-code. Platforms like Relevance AI, Fixie, or even custom GPTs in ChatGPT allow you to build a prototype in hours. The key is to define the input data and the output you want. Then iterate. Luna: I've seen leaders who treat it like a side project. They spend weekends tinkering. That seems to work well. Lucas: It does. And when they show the prototype to their team or their boss, the reaction is usually 'How did you do that?' That's the moment they become the expert. Not an AI expert per se, but the expert at applying AI to their domain. Luna: We've been talking about building tools, but there's also the aspect of using AI to shape your own career narrative. Like, using it to analyze your own performance data or industry trends to position yourself. Lucas: That's a great point. I know a general counsel who used AI to scan regulatory filings and identify emerging compliance risks before her peers. She then wrote a white paper and shared it with the board. That led to her being asked to chair a risk committee. Luna: So the AI rook isn't just a tool — it's a visibility engine. It creates artifacts that demonstrate your value. Lucas: Exactly. And those artifacts — a dashboard, a report, a presentation — are what get you noticed. They're concrete evidence of your unique contribution. Luna: I want to talk about the elephant in the room: the fear that AI will replace senior leaders. I hear that from some of my coaching clients. Lucas: I think that fear is misplaced. AI won't replace senior leaders. But senior leaders who use AI will replace those who don't. The value of a CEO isn't in typing emails or running spreadsheets — it's in judgment, relationships, and vision. AI augments those. It doesn't replace them. Luna: So the rook is really about staying ahead of the curve. And honestly, that's a big part of why we do this show — to help our listeners think strategically about their careers. Lucas: Absolutely. And if this conversation has given you one concrete idea to explore, that's the goal. We try to keep this show free of ads and paywalls because we believe senior leaders need this kind of practical insight without noise. If you find value in it, you can support us at buy me a coffee dot com slash fexingo. It's a simple way to help us keep going. Luna: Yeah, every bit helps. And we genuinely appreciate it. Now, back to the rook idea — let's talk about how to protect that advantage once you've built it. Lucas: Good. Because the rook can become a vulnerability if you don't manage it. The first risk is over-dependence. If your tool breaks or the data source changes, you need a backup plan. The second risk is that others learn to replicate it. Luna: So how do you keep it proprietary without being a bottleneck? Lucas: You document the methodology but retain the judgment layer. You can teach someone the steps, but the intuition for when to trust the output and when to challenge it — that's yours. Also, continuously improve it. Add new data sources, new questions. Make it a living system that only you can evolve. Luna: So it's a moat that requires constant investment. That's actually a good thing — it forces you to stay engaged and learning. Lucas: Exactly. And that learning signals to your organization that you're forward-looking. In a world where the half-life of skills is shrinking, being seen as someone who invests in their own capability is a huge career asset. Luna: Let's end with a practical takeaway. If a listener wants to build their first AI rook this month, what's the first step? Lucas: Pick a recurring question you answer poorly or slowly. Spend two hours this week exploring a no-code AI tool. Talk to a vendor, watch a tutorial, or use a custom GPT. The goal isn't perfection — it's to prove to yourself that you can. Once you have that first win, you'll see the board open up. Luna: And then you've got your rook. Lucas: Then you've got your rook.