Artificial intelligence is already shaping how students learn and how graduates are expected to work. The question is no longer if students will use AI. It’s whether their education will help them learn to use it effectively.
As Henry Mann, Senior Director of Product Development at CompTIA, explained during a recent webinar, “The workforce doesn’t need more AI engineers or prompt engineers. What the workforce needs is just more AI-fluent workers.”
That statement captures a shift that is reshaping expectations across education and employment.
AI is no longer a specialization
When generative AI first gained attention, much of the conversation focused on new job titles and advanced technical roles. Mann noted that this framing did not hold up once organizations began applying AI broadly.
“Sometimes we talk to people, and they ask, ‘How do I prepare my students for AI jobs?’” he said. “I think it’s more about how do you prepare your students to use AI skills in whatever jobs they go into?”
Employers are not looking for graduates who can describe AI conceptually or who have simply experimented with tools. They are looking for people who understand how and when to use AI across all roles and industries. Sales teams, healthcare workers, marketers, educators, and operations staff are all expected to interact with AI as part of their everyday work.
The common thread is not specialization, it’s fluency. “AI is not just some new skill for technical workers,” Mann said. “It is a new technical skill for all workers.”
That shift has major implications for educators. Skills that apply across roles can’t live only in advanced or elective courses. They must be treated as foundational, alongside other core literacies students are expected to develop.
Familiarity is not the same as readiness
Most students today are familiar with AI tools. They open chat interfaces, ask questions, summarize content, and experiment informally. That kind of personal experimentation, however, does not build the professional practice employers expect.
“What we see when we look at young people using AI tools is familiarity,” Mann observed. “But employers expect AI fluency.”
Fluency goes beyond knowing that AI exists or using it occasionally. It includes understanding what AI can and cannot do, applying context effectively, using AI to improve productivity, and recognizing when human judgment must remain in control.
The gap between familiarity and fluency presents a challenge for educators. Restricting AI use entirely may feel like a way to preserve academic integrity, but Mann cautioned that this approach often removes guidance rather than reducing usage.
“The reality is that [banning AI use] hasn’t stopped students from using AI,” he said. “It’s just removed institutional guidance on how to use it well.”
Education needs a common framework
Across conversations with educators, CompTIA has heard consistently that while institutions broadly agree that AI literacy matters, they struggle to translate that belief into practice.
“There is a real understanding that AI literacy and AI fluency are critical skills for students,” Mann said, “but there’s not a clear sense of how to actually provide a curriculum that teaches those skills.”
Complicating matters further are inconsistent policies, unresolved questions about data privacy, and the difficulty of creating safe environments where students can practice with AI in meaningful ways.
“If you want students to work with real AI, that often means choosing a vendor, dealing with privacy concerns, and managing accounts,” Mann explained. “Those are very thorny questions.”
These challenges are not limited to one level of education or one discipline. They appear across the student journey, from early exposure through workforce preparation.
Teaching students when to use AI matters as much as teaching how
One of the strongest themes to emerge from the webinar was the importance of judgment. “Deciding when to use AI and how to use AI is a critical skill,” Mann said. “That’s true in both school and work.”
In academic settings, this distinction becomes especially important. Responsible use begins with clarity around purpose. “In an academic context,” Mann explained, “AI should support learning, not substitute for learning.”
Using AI as a tutor, editor, or coach can be appropriate when students remain the authors of their work and can explain their ideas. Problems emerge when AI replaces the learning process altogether. In practice, many situations fall into gray areas, making shared discussion and guidance more effective than rigid rules.
“There are gray areas,” Mann acknowledged. “They require judgment, and they may differ from institution to institution.”
Rather than avoiding those conversations, institutions need frameworks that help students and instructors talk through them with shared expectations.
From awareness to action
Most institutions have already agreed that AI literacy matters. The challenge now is less about awareness and more about alignment: how to ensure students encounter consistent expectations and guidance as they move through their education. While approaches vary, the underlying need is the same across institutions and programs.
At a broader level, this shift is about redefining what it means to be “prepared” as a graduate. “If we can teach every student how to use AI well,” Mann said, “that prepares graduates for AI-fluent workplaces and gives institutions a framework for responsible AI use today.”
Treating AI fluency as a baseline skill reframes the challenge. It shifts the focus from individual tools or policies to the broader expectation that students graduate with shared, transferable AI capabilities, regardless of how specific technologies evolve.
As Mann concluded, “Whether you work with CompTIA or not, I hope this message resonates. Teaching students how to use AI well is something we need to do across the industry.”
Continue the conversation
To see how AI readiness begins earlier in the pipeline, read AI Readiness in High School.
For how AI literacy applies across disciplines, explore AI Fundamentals for Every Major.
For a practical overview of program design, see What Is CompTIA AI Fundamentals.
To hear the full discussion in context, watch the From Buzzword to Baseline Skill webinar.