Written by Steve Kirkpatrick | Former primary headteacher and co-founder, Intelligent Evidence

Let’s be honest: AI isn’t a distant future anymore. It’s already woven into the tools we use and the conversations shaping education’s future.

As a former primary headteacher, I understand the unease that comes with that shift. AI can feel like something that belongs in tech teams or data departments, not in classrooms or SLT meetings.

But here’s what I’ve learned: AI isn’t really about data, it’s about decision-making. The best AI tools don’t replace what we do, they help us do it with more clarity, insight, and confidence. And if we lead that process with care and strategic intent, AI can become a powerful support, not a threat.

From reports to real insight

My view of AI changed when I started using it to help make sense of the data we already had – not to collect more, but to make better use of it.

Take reporting to governors, for example. We’d spend hours preparing charts and summaries from different systems. Now, with the help of AI, we can clean that data and turn it into clear, structured reports in minutes.

But here’s the point: AI can organise the numbers but only leaders can tell the story. It can highlight patterns, but it can’t explain context, intention, or impact. That still comes down to professional judgement. AI sharpens our decisions, it doesn’t make them for us.

Spotting patterns that we miss

What stuck with me early on was how AI helped us ask questions we didn’t think to ask.

One time, our anonymous behaviour data flagged that a particular pupil was having more incidents on every third Monday. No one had spotted the pattern, but when AI looked at the long-term patterns, it became clear. This led to a crucial chat with our pastoral team, where we found out the child had contact with a family member that weekend which was a source of big stress for them. That insight changed how we supported them on Mondays. The AI didn’t solve it – it just helped us notice.

In another situation, we used AI to track pupil’s Key Stage 2 results from Year 3 all the way through to Year 6. The pattern was clear: kids who were doing well in Year 3 usually stayed on track if they stayed with us. That told us something powerful about the consistency of our curriculum – something we’d felt, but couldn’t previously show.

In both these examples, AI didn’t give us the answers. Instead, it asked better questions. The real work, the human work, was understanding what mattered and deciding what to do next.

With AI, we can now ask things like:

• What does a classes attendance on a Tuesday mean for their maths progress, especially if that’s when they have their toughest maths lessons?
• How do different things – like a group’s history of extra help, their pastoral support, and their past results – all connect to affect how well they achieve?

This pushes us past just checking off boxes and into real strategic thinking. Our staff aren’t just looking for who’s “behind” in their achievement; they’re asking, “What’s the pattern? What’s causing it? What needs to change?”.

This kind of deep questioning helps us make better plans for students and tweak our curriculum.

Leading with professional judgement

Here’s the caution: when AI works well, it’s easy to trust it too much. We must never hand over professional thinking to a system. AI can support our view, but it must never replace it.

That means:

• Always checking outputs
• Always owning the story
• Always challenging what doesn’t feel right

If we expect AI to think for us, we lose what makes leadership valuable. It’s our lens, not the tech that brings decisions to life.

In my time leading in schools, we found it crucial to put clear principles in place to protect professional judgement and to help staff trust the process:

• Try before you buy: If it doesn’t save time or support your core purpose, you shouldn’t ask staff to use it.
• Staff time is gold: Any new system must be easy to learn, reliable in use, and genuinely worth the effort.
• Privacy is non-negotiable: All data analysis should use groups and codes, never names. Protecting privacy isn’t optional, it’s a leadership responsibility.
• Always explain the why: Staff need to understand the reason behind every tool, and how it links back to the work they care about.

This approach builds trust. When changes feel less forced and more logical, our staff can actually see the benefits, even if it pushes them a bit.

A fairer system for all schools

This isn’t just about individual schools… AI has real potential to make the system fairer.

Imagine national education bodies using AI to look not just at results, but at the full picture: mobility, deprivation, access to support, attendance patterns. We could ask bigger, better questions about what really drives outcomes and what context schools are working in.

For schools in high-need areas, that shift could be transformational. It might finally give us a way to explain not just the what – but the why – behind pupil journeys. That’s not just better data. That’s better understanding.

A leader’s role in the age of AI

The simple truth is: we have to embrace AI. In what we teach, in how we do our jobs and in our national plans. It’s already here – to ignore it is to put ourselves at a disadvantage, as individuals, as institutions, and as a whole system.

But we must do it with care, clarity, and guts. AI doesn’t take away our responsibility; if anything, it makes it even bigger.

So, the real challenge isn’t whether we use AI. The real challenge is whether we have the honesty and smarts to use it well. Are we ready to lead this change with the confidence it demands?