AI What happens with your data when you use AI?
TIM HANDLEY, former teacher, data lead and primary headteacher and now a certified Google AI practitioner and developer of Edu Intelligence’s sector-leading 22 specialist agent education- specific AI, tells us more.
The National Education Union’s State of Education 2026 survey, published in April, reported that 76% of teachers are now using AI tools for day-to-day work. A year earlier, the figure was 53%. The same survey found that 49% of teachers say their school has no AI policy at all, while two-thirds (66%) have no student- specific policy.
Teachers are using AI because it works. Lesson planning that took an hour takes fifteen minutes. Data analysis that took
a day can take minutes. Reports, letters and meeting summaries are being handled, at least in part, by tools that didn’t exist in classrooms two years ago.
Most use is in resource creation (61%), lesson planning (41%) and administrative tasks (38%). The time-saving is significant – but the key question is whether the tools teachers have reached for are safe for the data those tasks involve.
The two problems of ‘Shadow AI’
‘Shadow AI’ is the term used when AI tools are being used inside an organisation without the knowledge, approval or oversight of its leadership. There are really two shadow AI issues facing schools: The first is personal-use AI: staff pasting reports, behaviour notes, parent emails or pupil information into public tools on their own accounts. Many of these tools, on their free or consumer tiers, may use the input to train future models. Information about a child could become part of a model accessed by anyone.
The second is institutional. AI is being added to tools schools already use: your assessment platform, your behaviour tracker, your MIS, your communications system. Many have added AI features in the last 12
months. These additions didn’t go through fresh procurement. They didn’t trigger a new Data Protection Impact Assessment.
Both these shadow AI issues carry the same potential risk of identifiable pupil data flowing into AI systems that schools haven’t sanctioned, vetted, or even necessarily noticed.
Banning or reducing AI use isn’t the answer. The best response is to: • Give staff safe, school-approved AI tools, so they don’t have to reach for public versions. Personal-use AI drops sharply when there are credible internal alternatives that have been vetted, that don’t train on school data, and that staff trust to do the job.
• Audit the tools you already have. Ask every supplier the same question: have you added AI features since we signed? If so, what does it do, what data does it see, and is our DPIA still valid?
• Write a policy that distinguishes clearly between what’s allowed, what’s prohibited and what needs leadership sign-off. The 49% with no policy at all are exposed in a way that few outside the leadership team appreciate. A short, practical policy is significantly better than a perfect one that never gets written.
Whether the AI is one you’re buying, one your staff are quietly using, or one that’s been added to a tool already on your network, the questions are the same. Does it process identifiable pupil data, or only anonymised information? Is your school’s data stored separately from other clients? Is it used to train models for anyone else? Is it GDPR-compliant and UK-processed? Can the supplier explain how the AI it uses reaches its conclusions?
The answers will tell you whether the AI in your school is working for your pupils, or, quietly, against them.
Mind the gap: why more girls belong in cyber and AI
If the UK wants a future digital workforce that is innovative, ethical and representative, CyNam’s Skills Growth Lead, CHARLOTTE SMITH, says we need to do far more to encourage girls into computing, cyber security and AI from an early age.
Many UK schools now offer some form of computing, yet a glance through the classroom door can still reveal a familiar imbalance. Despite years of progress in subjects such as maths and science, girls remain under- represented in computing and in newer frontier fields such as cyber security and AI.
If schools have worked hard to improve gender balance elsewhere in the curriculum, why has computing proved more difficult to shift? The reasons are about opportunity, perception and encouragement. Too few girls are shown that coding, cyber security and AI are spaces where they can thrive. Girls who enjoy science, maths, problem-solving and building things need to see, from an early age, that technology is for them, too. Many schools are already responding creatively. Storytelling, collaborative projects and real-world problem-solving can present technology as imaginative, purposeful and socially relevant rather than narrowly technical.
That matters because cyber and AI are too often framed as purely technical disciplines. In reality, they also involve ethics, psychology, teamwork, communication and creativity. They are about how people solve problems and shape society – not just how machines work. For many girls, the chance to use technology to solve meaningful problems and improve lives is a powerful motivator. Competitions, creative challenges, Capture the Flag activities and girls-only opportunities can help build confidence, curiosity and a stronger sense of belonging. Visibility matters too. When girls encounter female role models through visiting speakers, alumni and industry professionals, they are more likely to
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www.education-today.co.uk imagine themselves succeeding in these fields.
At CyNam and CyberFirst South West, that visibility is built into events and school engagement. Panels and workshops include both women and men, so students meet female ethical hackers, AI designers, penetration testers and digital creatives alongside their male counterparts. At school, lunchtime cyber clubs, after-school workshops and girls-only coding or cyber sessions can remove social pressure and give students space to explore freely.
Girls-only events are not about division; they are about access, confidence and creating a safe space to try something new. Initiatives such as the annual Empower Cyber event for 1,000 Key Stage 3 students show how targeted opportunities can widen participation while building excitement around the sector.
Mentoring matters as well. Workplace visits, female mentors and interactive programmes for teachers and governors can all help build stronger pathways into cyber and AI.
Families remain one of the strongest influences on young people’s career decisions. That is why parents, carers, teachers and careers leaders all need clear, accessible information about pathways into digital careers. Without that knowledge, unconscious bias can still shape which roles are seen as suitable for girls and which are not.
Encouraging girls into cyber and AI is about removing barriers and widening opportunity. When classrooms better reflect the diversity of the world beyond them, the technology we create is more robust, more ethical and more inclusive. That is not just good for girls; it is good for education, industry and society as a whole.
June 2026
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