They’re Watching: What Your Team Can Already Tell About Your AI Literacy

Your team already knows.

They know whether you actually use AI or just talk about it. They know whether you’ve built a real strategy or simply handed out Copilot licenses and called it a day. And they know whether you’re leading through this shift or quietly hoping someone else will figure it out.

Here’s the uncomfortable part: they’re making decisions based on what they see. Your best people are reading your AI fluency like a signal. It tells them whether this company is going somewhere or standing still; whether their skills will grow here or stagnate. 

AI literacy isn’t a luxury for business leaders anymore. It’s a credibility marker. And your team is already keeping score.

“We Use Copilot” Isn’t a Strategy

There’s a moment that keeps happening in meetings across all industries: someone asks about AI, and the CEO responds with some version of: “Yeah, we use Copilot.” And that’s it. End of answer.

“My number one tell that someone isn’t on top of their AI strategy is when AI comes up, and they say, ‘We use Copilot,'” said Sarah Bhatia, Director of AI Product Innovation at Slingshot. “You need to do more.”

The statement reveals a superficial understanding masquerading as progress. It signals that you’re treating AI as a subscription rather than a strategy. It tells the room that leadership checked a box without building anything behind it.

Doug Compton, Principal AI Developer at Slingshot, added another tell: “When a CEO who’s not into AI talks about it, really all they’re thinking about is chatting with it. They’re not thinking about creating agents or building skills.”

There’s a meaningful gap between using a chatbot and deploying AI as a business capability. Teams see it. And competitors who’ve closed that gap are already pulling ahead.

Your Team Reads the Signals You’re Not Sending

Even when a leader isn’t in the room, employees can piece together exactly how invested leadership is in AI. The clues aren’t subtle.

“You can tell strategically based on what tools the team has access to,” Sarah explained. “When I hear people say ‘They just gave us ChatGPT,’ and there’s not really anything beyond that, that tells me there’s not a strong strategy from the top down for how to use AI to actually transform what they’re doing.”

The signals go beyond tool access. Doug pointed to even more basic questions: “Does the CEO even talk about AI? Is it just business as usual? How encouraging is leadership with people using AI? Are they scared of it? Are they encouraging people to explore and play with it?”

Those small indicators add up fast. When a CEO treats AI like background noise, teams follow suit. When a business leader actively frames it as a priority, invests in exploration, and creates space for experimentation, the culture shifts.

And the inverse is just as true. When there’s no direction from the top, employees default to whatever’s comfortable. They don’t challenge limits or experiment; they wait. And standing by is a competitive liability.

What AI Leadership Actually Looks Like

What does it actually mean to lead on AI? It’s not about becoming a prompt engineer or memorizing model designs; it’s about creating the conditions for your team to move.

“What we’ve seen work is when the CEO’s role is really about structure,” Sarah said. “It’s about protecting people’s time, setting tangible goals, empowering the people with the skill set and enthusiasm, and finding the right vendor-partner relationships when you hit that execution ceiling.”

She shared a strong example of this in practice: a leadership team that created a dedicated strategic business unit whose sole purpose was to find opportunities and efficiencies within the organization. That unit became the internal engine for identifying AI use cases, while an outside innovation partner provided the technical pulse on what was possible.

“It’s really replicable across industries and across size,” Sarah said. “It boils down to empowerment from the C-suite: identifying the people that want to bring this to life, building structure around it, and then finding the appropriate execution partner when and where they’re needed.”

That model works because it doesn’t require the business leader to be a technologist. It requires them to be a systems builder. To set up feedback loops, protect the time and attention of internal champions, and know when they’ve hit a ceiling and need outside expertise.

Fear Is Real, and So Is the Risk of Ignoring It

Even when CEOs get the strategy right, adoption can stall from a completely different direction: fear.

“There’s a huge gap there, and people are afraid for their jobs,” Doug said. “Why would an employee start using AI and show their company how to use it if they thought that it would replace them? The business leader needs to be able to speak to that and assure their people that this isn’t about replacing jobs; it’s about making people more efficient so they can grow the company.”

This fear isn’t a small problem: a significant portion of the American workforce remains skeptical of AI. Fear of displacement, loss of relevance, and general uncertainty are real forces. And when leadership doesn’t address them, those feelings harden into resistance.

Sarah highlighted a practical tactic for breaking through: “Find a small group of supporters and let them win. Showcasing those minor wins creates trust within your organization.”

And how you present it matters just as much as what you build. “So much of AI is a PR game,” Sarah said. “The most impactful implementation comes from using AI to solve problems that enable your team to do more of what they’re good at and enjoy doing. Use AI for cognitive offloading, so that humans can be more human and do the things that they’re best at.”

That reframe changes the narrative entirely. Instead of ‘AI is coming for your job,’ it becomes ‘AI takes the worst parts of your job off your plate.’ One of those messages creates resistance. The other creates buy-in.

You Don’t Have to Know Everything (But You Can’t Be Absent)

One of the biggest traps CEOs fall into is believing that AI literacy means knowing everything about AI. That expectation creates paralysis. And paralysis, in this context, looks a lot like inaction.

Sarah pushed back on the idea that leadership needs to be spending all their free time researching AI trends: “It’s not realistic to think that when your day is full with keeping the lights on and running the business, you can also stay on top of technology that’s evolving at a pace we’ve never seen. That’s what outside experts and consultants are there for.”

But there’s a difference between tracking every AI development and never opening the tools yourself. You don’t need to become the in-house AI expert, but you do need to be a regular user.

Doug stressed the significance of staying personally connected to the tools: “Leaders should be using AI nonstop to stay on top of it and know what it can do. They should be using it to help strategize so they know how to lead other people.”

Doug also noted a common budget mistake that undermines even good-faith efforts: “There’s a large difference between AI models; don’t skimp by giving your teams access to ‘lesser’ models. If you’re going to spend the money, get the good ones, because they’re so much better. You’ll actually save more money in the long run.”

The takeaway isn’t that business leaders need to become AI power users. They need to use AI enough to understand its potential, invest enough to equip their teams with real tools, and build enough structure to turn exploration into results.

The Score Your Team Is Already Keeping

Your team isn’t waiting for your next all-hands to form an opinion about your AI leadership; they’ve already formed one. It lives in the tools leadership provides (or doesn’t). In the time they free up for experimentation (or don’t). In the strategy they hand down (or the silence where one should be).

AI literacy for a CEO isn’t about technical depth; it’s about visible commitment, structure, investment, and the willingness to lead through something uncomfortable and unfamiliar without pretending you have all the answers.

Because your competitors aren’t going to announce how far ahead they are. That gap will show up in ways you don’t expect, and by the time you notice, the distance is already real.

By the time you notice, the gap may already be too wide to close. Your team sees the score. The question is whether you’re ready to change it.

Slingshot