INTELLIGENT CLASSROOMS


just in one area of school life. Hours spent trying to work out whether there’s a trend – and if there is, what’s driving it.


This is not high-value strategic work; it is administrative friction. Every hour a leader spends analysing data, or cross-referencing a behaviour log with an attendance report is an hour they are not in the corridors, not supporting teachers, not working with a vulnerable family, not building culture, not leading improvement. If we’re serious about the wellbeing and effectiveness of school leadership, we should be reducing the administrative burden of sense- making – not normalising it.


Understanding the ‘why’


The second cost is complexity. When data is siloed, we lose the narrative of the whole child. A truly ‘connected’ approach, one that uses AI not just to generate lesson plans or instructional resources, but to analyse complex relationships, changes this. It allows us to overlay a student’s behaviour incidents with their attendance patterns, their assessment scores, and even the qualitative notes in their pastoral files. Take a simple example: a Year 9 student whose behaviour incidents suddenly spike. In a disconnected system, each role sees a slice of the picture. The behaviour lead sees disruption. The attendance officer sees lateness. The head of department sees a dip in attainment. The SENCO might hold crucial context elsewhere. The pastoral team may have notes that explain the shift – but they’re not visible at the point decisions are being made.


A connected intelligence layer sees the pattern: the behaviour spikes on Tuesdays, which correlates with a specific staffing change recorded in the HR system, or a curriculum shift noted in a department plan.


We move from seeing a ‘difficult’ student to understanding a specific trigger. We move from knowing what happened to understanding why it happened. This is how we support the classroom – by identifying the barriers to learning that human analysis, drowning in spreadsheets, simply cannot spot.


Moving beyond the MIS


To achieve this, we must widen our definition of school data. For too long, we have treated ‘data’ as just the numbers in the MIS. But a school’s intelligence isn’t just rows and columns. It is also in the text.


School improvement plans, Ofsted reports, SEFs, policies, and procedures contain the strategic intent of the school. In a disconnected system, these documents sit in a shared drive, divorced from the daily data. In a connected ecosystem, AI can read and understand these documents alongside the numbers. It can tell you if your attendance data is trending in line with the interventions you wrote into your improvement plan six months ago.


This is where the promise of AI for leadership really lies. It isn’t about asking a chatbot to write a newsletter. It is about having an intelligence layer that sits across your MIS, your assessment tools, your behaviour platforms, and your documents, constantly looking for the connections that human eyes miss.


Data and AI security is key Of course, the moment we talk about connecting 30 www.education-today.co.uk February 2026


data and AI, the red lights of data security, GDPR and safeguarding should – and must – start flashing.


We should also be honest about risk where it most often appears in practice: in the everyday workarounds – downloaded reports, data transferred to personal devices, spreadsheets emailed between teams, and “one-off” uploads to third-party tools. Governance must match reality, not policy documents.


There is a valid concern about feeding sensitive data into public Large Language Models (LLMs). The connected school cannot be built on public platforms where data is used to train models for the rest of the world.


However, the industry has matured. We now have secure, private AI environments – walled gardens where data is processed within the UK, fully compliant with GDPR, and importantly where deep, connected insights can be automatically surfaced without AI ever seeing raw student data.


Crucially, this connectivity must be real-time. The days of downloading a CSV containing sensitive student data, saving it to a laptop, and uploading it to a third-party analysis tool should be over. That ‘data in transit’ is a security risk. Modern systems sync directly and securely, ensuring that what you see is what is happening now, not what happened last week. This aligns with the vision set out by the Education Secretary, Bridget Phillipson, at BETT this year. She spoke of a “data-driven school system” and a new “data spine” designed to unlock insights that were previously “trapped in closed systems.”


The government recognises that we cannot improve standards if our intelligence is locked away in silos. We must be rigorous in demanding that our tools offer this level of sovereignty and connectivity. Innovation cannot come at the cost of privacy, but neither can privacy be an excuse for the status quo.


The final connection


Ultimately, the goal of connecting our school data is the same as the goal of the connected classroom: to improve outcomes for children. When we remove the drudgery of manual analysis, we give leaders their capacity back. We allow them to operate at the top of their skillset. A Director of Education should be analysing the impact of a reading strategy, not fixing formulas in Excel. A SENCO should be designing interventions, not wrestling with reports to prove they are needed.


So, as we embrace the connected classroom, let’s not forget the engine room. What data do we hold that we can’t see together today? Where are leaders still exporting reports and looking across tools to make decisions? Which patterns are visible only to the person with the time – and the data skills – to piece them together?


The technology now exists to turn our scattered data into clear, actionable intelligence. It is time to stop stitching spreadsheets together and start seeing the full picture.


Because when we connect the data, we don’t just save time; we see the child. And that is what matters most.


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