Artificial intelligence is reshaping work. That part isn’t up for debate. From hiring platforms and scheduling tools to project planning, documentation, and internal search, AI is increasingly baked into the systems people use every day. But while most organizations are focused on engineering pipelines or automation strategies, they’re missing a more foundational shift: AI fluency as a workforce-wide competency.

We need to stop thinking of AI skills as belonging only to technical roles. Today, fluency with AI tools, knowing how to use them effectively, evaluate their outputs, and integrate them into decision-making, is becoming as fundamental as being able to write a clear email or lead a productive meeting. It’s not just about knowing how AI works. It’s about knowing how to work with it.

A Signal from Higher Ed: AI Literacy for Everyone

This fall, The Ohio State University is launching a new AI Fluency initiative, embedding AI education directly into general undergraduate requirements and major-specific curricula. The goal is not to turn every student into a developer. It’s to equip them with the ability to apply, question, and innovate with AI across disciplines.

As Ohio State President Walter “Ted” Carter Jr. explained in the university’s announcement: “Artificial intelligence is transforming the way we live, work, teach and learn. In the not-so-distant future, every job, in every industry, is going to be impacted in some way by AI.”

The AI Fluency initiative will begin with first-year students this fall, emphasizing responsible use of AI in the context of each student’s area of study. The expectation isn’t that everyone becomes technical. It’s that everyone becomes literate and that mindset needs to carry over to the workplace.

What Does “AI Fluency” Actually Mean

AI fluency isn’t about coding or understanding how machine learning works under the hood. It’s the ability to understand what AI tools can and can’t do, how to get meaningful results from them, and how to apply those results in the real context of your role.

In HR, for example, AI fluency could look like a recruiter who knows how to prompt a sourcing tool for better candidate matches, but also knows when to double-check those suggestions for relevance or bias. It could mean understanding how to use AI to write a job description faster, and just as importantly, knowing when to revise and humanize the draft before publishing.

Fluency includes a filter — the moment where you pause and ask: “Does this result make sense? Should we trust this result? What’s missing?” That judgment is just as critical as technical skill, and it’s what separates productive AI use from thoughtless automation.

AI Is Already in the Workflow, But Teams Just Don’t Know It

Many organizations still treat AI like it lives in a separate lane. But AI is already integrated into tools people are using across functions. Marketing teams use it to brainstorm campaigns. Operations teams use it to summarize workflows. Finance teams use it to clean up data before analysis. HR teams are using it for onboarding documentation or policy drafts.

In that sense, AI is already ambient. But many companies still haven’t built the support systems or learning culture employees need to navigate this shift confidently.

We don’t need every employee to become an AI expert. But we do need them to feel confident using AI, asking questions, and identifying risks. And confidence doesn’t come from mandates. It comes from exposure, experimentation, and context.

Why We Should Stop Treating AI as a Headcount Replacement

A common misconception is that AI’s main use case is replacing people. That logic is not only flawed, it’s counterproductive. The real value of AI is in amplifying human performance, not replacing it.

When used well, AI helps people focus on higher-value work: decisions, relationships, creative thinking, and strategy. It reduces time spent on repetitive tasks and increases space for problem-solving. But it only works if people know how to use the tools, trust them appropriately, and integrate them into their unique workflows.

 The companies that thrive won’t be the ones that cut jobs. They’ll be the ones that give their people the skills and permission to use AI in ways that improve how they work.

Where HR and L&D Teams Come In

Most people are still figuring AI out. And that’s where people leaders have a critical role to play. AI fluency isn’t something you assume. It’s something you build, deliberately, patiently, and inclusively.

That means moving beyond generic technical training. It means investing in learning programs that show employees how AI can help in the actual context of their jobs, whether that’s writing, scheduling, analysis, or planning. It’s also about helping them feel safe experimenting without the fear of “getting it wrong.”

This is where hands-on, low-stakes exposure matters. Let employees try using AI to brainstorm ideas, summarize notes, or create first drafts. Show them how the tool can save time or reduce friction in familiar tasks. The goal isn’t mastery. It’s comfort. Curiosity. Confidence.

Peer learning is also essential. Create space for teams to share what’s working, and what isn’t. Sometimes the best teacher isn’t a formal training session, but a colleague showing how they used a tool to save 30 minutes on a recurring task.

The Inclusion Case for AI Fluency

If only a narrow slice of the company understands how to use AI, they’re the ones making the decisions about how it gets implemented. That’s a real equity problem.

Democratizing AI literacy ensures more perspectives are part of how tools are used, evaluated, and improved. A customer service agent might spot bias in AI-generated responses. A warehouse manager might recognize a scheduling process ready for automation. These aren’t edge cases, they’re exactly the types of insights we miss when fluency is limited to technical teams.

There’s also a career growth angle. Employees who gain confidence with AI become more capable of problem-solving, decision-making, and leadership. They’re able to do more, and they know it. That’s empowerment. And it pays dividends across performance, retention, and engagement.

Fluency Should Include Judgment, Not Just Function

It’s worth repeating: AI fluency doesn’t mean full automation. It doesn’t mean unquestioning trust in every output. It means pairing tool use with thoughtful review.

We still need empathy, ethical reasoning, and human context, especially as AI begins to touch decisions about people, policy, and strategy. Being fluent doesn’t mean deferring to machines. It means working with them effectively while knowing when to step back, ask questions, and make the call yourself.

This balance is the real goal. Not either/or, but both/and.

Don’t Ignore It

If companies ignore AI fluency or treat it as optional, they’re not just risking inefficiency, they’re risking irrelevance. Teams that don’t understand AI will struggle to keep pace with how work is changing. They’ll miss out on productivity gains, decision-making speed, and internal innovation.

But more than that, they’ll miss out on building a resilient, adaptable workforce.

The good news is, it’s not too late. AI fluency is not innate, it’s teachable. And if we treat it like any other essential skill, with support, exposure, and time, we can bring everyone along.

The future of work doesn’t belong to the few who already “get” AI. It belongs to the many who are ready to learn, ask questions, and grow into it together.