AI literacy is one of those phrases we hear everywhere in higher education. Students are told to develop it, staff are encouraged to model it, and whole strategies are being written around it. But what does it actually mean, and why should it matter to you?
Across universities, we ask people to read AI guidance, attend workshops, or complete short courses designed to develop their AI literacy. These are valuable resources, but are we missing the most important step? Before we can expect people to engage with training, we need to give them a reason to care.
What AI Literacy Means to Me
When I talk about AI literacy, I’m not talking about becoming an expert in the technology behind it. You don’t need to know how to build an AI system to use one well. For me, AI literacy is about three things: awareness, judgement, and confidence.
Awareness is about understanding how AI tools actually work in practice, what they’re good at, where they’re unreliable, and why they sometimes produce convincing but inaccurate results.
Judgement is about deciding how and when to use AI: asking the right questions, checking the answers carefully, and knowing when it’s better not to use the tool at all.
Confidence comes from building those first two, so that you can use AI in ways that are purposeful, safe, and genuinely useful.
In other words, AI literacy, at least as I see it, is about navigating this new landscape with critical confidence.
Why It Matters
AI literacy applies to everyone in higher education, but for different reasons.
For students, the link is direct: employability. Most graduates will enter workplaces where AI is already part of everyday practice. Employers will expect them to use AI tools confidently, responsibly, and in ways that add value, without exposing the organisation to risk. AI literacy is what makes the difference between using AI to cut corners and using it to contribute effectively in a professional environment.
For staff, the case is just as important. Teaching and assessment must stay relevant to the world students are preparing for. If staff don’t understand how AI tools behave in practice, they risk creating tasks that feel outdated or easily undermined. Staff also have a responsibility to model safe and ethical use, and to guide students in developing the judgement they will need beyond university. Without AI literacy, it’s impossible to set fair expectations or support students in building their own skills.
In short:
Students need AI literacy to be employable and trustworthy in the workplace.
Staff need AI literacy to keep higher education meaningful and responsible in an AI-rich world.
This isn’t just a personal concern. In our most recent Digitally Enhanced Education Webinar, Rethinking Our Guidance on AI: What’s Working, What Isn’t?, more than 1,000 colleagues from across the sector joined the discussion. That level of engagement shows how widely these questions are being asked. Institutions everywhere are trying to work out not only what guidance to give, but how to make sure people have a real reason to follow it.
And this debate isn’t happening in isolation. The UK government has recently announced billions of pounds of investment in AI infrastructure, research, and growth zones, with the aim of creating thousands of jobs and attracting major international partners. That level of national commitment underlines the point: AI is not a passing trend. It will shape the workplace our graduates step into and the environment our universities operate within. Developing AI literacy is about making sure staff and students are ready for that future.
Making the Case for AI Literacy
If we want students and staff to engage with the guidance and resources we provide, we have to make the “why” impossible to ignore. A few ways institutions can do this:
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Show the employability link clearly. Connect AI literacy directly to workplace expectations, internships, and graduate destinations. Make it obvious that employers want graduates who can use AI responsibly — and that not having these skills could limit opportunities.
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Highlight national investment. With billions being invested in AI growth zones and research, we need to show students and staff that this is shaping the environment they’ll be working and studying in.
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Embed relevance in teaching. Don’t leave AI literacy as an optional extra. When students see it applied directly in their courses, in assessments, discussions, or project work, the message lands more strongly.
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Model good practice. Staff confidence is key. If students see their lecturers using AI transparently and responsibly, they’re more likely to mirror that behaviour.
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Frame it as essential, not optional. Just as digital literacy became a baseline expectation a decade ago, AI literacy is becoming one now. Institutions need to be clear: this is part of being ready for study, for work, and for the wider world.
The Risks of Ignoring It
Without AI literacy, it’s all too easy for students to be misled by inaccurate outputs or to lean on AI in ways that undermine their own learning. For staff, the risk is that assessments or teaching approaches don’t stand up in an AI-rich world. And for universities as a whole, the bigger danger is producing graduates who aren’t ready for the realities of work.
This conversation will keep evolving. Our next Digitally Enhanced Education Webinar, Teaching with AI: Early Insights from the New Academic Year, takes place on 5 November. It will be another chance to share what’s working, what isn’t, and how we can keep building AI literacy together across the sector.
Please complete the Digitally Enhanced Education registration form if you would like to join us.
Looking Ahead
AI will keep changing, and so will what it means to be literate. The end goal isn’t to keep up with every tool, but to build the judgement and adaptability to use AI well, whatever form it takes next. That’s why it’s worth asking yourself: are you using AI in ways that genuinely help you, while staying alert to its limits and risks? If the answer is “not yet,” then this is the right moment to start building that awareness, judgement, and confidence.
Becoming AI literate is not about keeping up with the technology. It’s about making sure the technology works for you, your learning, and your future.