I may not be alone in saying that I’m tired of seeing the phrase ‘AI literacy’ thrown around without explanation, and with a distinct lack of clarity on the skills someone needs to be considered AI literate.
It’s concerning because AI literacy is becoming one of the most important skills of our time. Alongside relationship building and strategic thinking, it’s one of the top three fastest-growing in-demand skills in the UK. So organisations are scrambling to close the AI skills gap – but how can they when there’s no collective understanding of what AI literacy looks like?
AI literacy is a spectrum, not a destination
AI literacy is like learning a language. Some will become fluent and write poetry, others just need to know enough to get by in the workplace without accidentally ordering a plate of frogs. And that difference is okay. What matters more is that people have the opportunity to learn and that the training they receive matches the reality of their role, industry and ambitions.
The recent trend of creating personalised AI-generated dolls particularly fascinated me because it speaks volumes about what AI literacy really is. Everyone had access to the same tools, but while some users barely scratched the surface, others created entire alter-egos. Same tech. Wildly different outcomes. It’s a reminder that AI isn’t a binary skill. It’s layered, contextual and shaped by how empowered people feel to engage with it.
While there are a few good attempts to define AI literacy (The Digital Education Council’s AI Literacy Framework, for example, outlines categories such as understanding, ethical awareness and creative application), most people don’t know these frameworks exist. And I would argue that such frameworks are too reductive. There’s no single definition of AI literacy; what’s labelled “AI” in one organisation might just be a bit of smart automation in another.
What good AI training actually looks like
I work for Instep, a company that designs and delivers training programmes for organisations across industries. And I can tell you with confidence: AI literacy can’t be distilled into a standardised list of skills. It’s far more fluid than that.
The best results come when training is, first of all, consultative and tailored. Off-the-shelf workshops don’t work, not in the long-term, because they disregard context. AI literacy is about understanding the digital maturity of the specific company, the goals of the team and the current capability gaps within the organisation. That information then needs to be leveraged to build something bespoke that makes AI tangible, useful and relevant.
Training must also be grounded in real-world application. The goal isn’t to turn everyone into prompt engineers. It’s to help people feel comfortable using tools that make their jobs easier, faster and more rewarding. That means hands-on learning, not hypothetical scenarios. Showing someone a generic slide on what ChatGPT could do for marketing isn’t very helpful or sustainable. But guiding them on how to write and refine an actual email campaign using AI, then evaluating what worked, what didn’t and where the human touch added value – that gives them real power and knowledge.
Finally, AI is evolving too fast for one-time training to cut it. What people and businesses both depend on is a culture of continuous learning, a workplace where curiosity is encouraged and experimentation is safe.
Why this matters more for women
All of this is even more urgent when viewed through a gender lens. Recently, I read a piece in Red Magazine that explored the gender imbalance in AI and the threat it poses for women in the workforce.
According to that, 21% of women’s jobs are at risk of being replaced by AI, compared to 17% of men’s. Office administrative jobs are a prime example; 70% of these roles in the UK are staffed by women, and the duties they involve (record-keeping, scheduling, data entry) are increasingly automatable with AI software.
Compounding the issue, 54% of men use AI tools regularly, versus just 35% of women. If fewer women are using AI tools, fewer women will be part of shaping how these tools are embedded into working practices, and that will inevitably cook bias into the systems we use daily.
While these are interesting statistics, they don’t necessarily align with my own experience. My colleagues and I are in a very unique position. At Instep, the people leading the AI conversation and initiatives are women. It’s not that men are being excluded, it simply comes down to the fact that a high percentage of those who have been hired specifically for their technical skills are women. But it seems that we’re an outlier, as it’s not the case in a broader sense across the UK.
Women, especially those outside of STEM roles, need access to AI training that doesn’t assume prior technical expertise. They need space to explore and experiment, and they need to see other women leading by example.
At Instep, that visibility comes naturally because women are already leading. While it’s not by design, it proves a point: when barriers are removed and capability is prioritised, women step into these roles – and excel. Across the UK, businesses need to create the same conditions: environments where women can lead in AI, training that feels accessible, and cultures that support exploration without judgement.
Building an AI-literate future
Investing in AI literacy training isn’t just about adapting to change, but shaping a future where technology enables inclusive innovation and sustainable progress. The reality is not everyone is part of the conversation, and not everyone has access to the kind of training and support that makes these tools feel usable, let alone empowering. I know how lucky I am to work in an organisation where upskilling isn’t an afterthought. But sadly, that’s not the norm.
If we’re serious about building an AI-literate workforce, we need to start with clarity. We need to stop pretending there’s a single definition of AI literacy and instead focus on giving people the space, support and practical tools to explore it in ways that make sense for their roles.
It has to be practical, it has to be ongoing, and it has to come from both sides: the individual’s ambition to grow, and the organisation’s commitment to make that growth possible.
