How AI is improving school and MAT operations 

As someone working in education leadership, I don’t have the luxury of extra hours and neither do my colleagues. The admin burden can be relentless and is often the work that gets done on evenings or weekends just to stay on top of it all. But in the last year, we've found something that genuinely helps: AI.

We’re using AI across the Trust to tackle some of our most time-consuming administrative work, to improve communication, and to free up time to focus on what really matters — improving outcomes for children.

Here’s how we’re doing it in 5 specific areas.

1) Research

When it comes to researching a potential project or gathering technical information, for example to brief Trustees, AI provides a massive head start. It can draft papers, pull case studies or provide additional context. For a recent decision on investment in solar panels, we used AI in “research mode” to help prepare the first draft of a business case. We were able not only to provide information on the financial and environmental benefits but also citations and concrete examples that gave our Trustees both confidence and context, allowing them to see the project as achievable rather than abstract. What could have taken weeks of manual research and drafting was condensed into a single, well-structured document that enabled informed discussions and decision-making.  

2) HR tools 

Another area where we are seeing tangible benefits is HR. A large proportion of HR queries are about interpreting policies — repetitive, time-consuming, and often delaying staff from getting clear answers. To tackle this, we developed a HR bot, trained to respond directly to these common questions. Instead of staff waiting on emails or digging through policy documents, the bot could provide tailored answers instantly, even suggesting draft follow-up emails. Early results showed it freed up significant time for the HR team, reducing their workload while giving colleagues faster, clearer guidance. We are now exploring different models to make the tool sustainable, but the impact so far has been obvious: less back-and-forth admin, more time for HR staff to focus on the issues that really matter.

3) Collaborative report writing

Co-producing documents - another laborious task often involving multiple drafts and lots of different inputs - is a further area that we have transformed by using AI. Instead of starting with a blank page, we record discussions of team meetings and use AI to produce a first draft document that everyone can refine together. This means the heavy lifting — structuring the document, capturing key points, and ensuring flow — is already done, leaving staff free to focus on sharpening the substance. What once took weeks of back-and-forth has become a smoother, faster process, and the quality of reports has improved because contributors spend their time debating ideas rather than formatting text.

4) Smarter policy comparison 

We have also used AI to cut through the complexity of policy management. Traditionally, comparing policies meant line-by-line reviews, a slow process that often missed subtle but important differences. With AI, we are able to generate side-by-side summaries that highlight key discrepancies and suggest specific amendments. This doesn’t just save hours of manual effort — it gives a clearer view of where policies align and where they need updating, ensuring consistency without drowning staff in detail. The result is a faster, sharper policy review process that enables a focus on substance rather than syntax.

5) Meetings and emails

The time taken to prepare and follow-up meetings has also been reshaped by AI. Instead of staff spending hours compiling notes, and writing-up minutes, AI now generates accurate drafts in minutes. These can then be quickly checked, refined, and shared, giving a clear record of challenge and actions without the usual delay. The shift has taken much of the drudgery out of meetings, freeing staff to focus on meaningful discussion rather than admin. We’ve also been using AI to help with emails, providing summaries of weekly briefings and sector updates, distilling key points that can then be circulated to senior leaders. 

Final thoughts

We’re careful with what tools we use. Confidentiality matters, especially in our sector. So we stick to platforms that meet our compliance standards and we often run the same task through different tools to see what gets the best results. 

Looking forward I am keen to start exploring how to use AI as a leadership coach, for example by helping staff to troubleshoot technical tasks or explore options they hadn’t considered.  I also think we need to talk more about the bigger picture. There is a risk that AI could deepen inequalities in education. Particularly where families opt for AI based learning over being in school which is where relationships are built and compound learning happens. We need to make sure AI in education doesn’t become a dividing line between haves and have-nots and that it is used well to save time and let people focus on what matters most.

It’s early days,  but it’s already hard to imagine going back.