Responsible AI in education: Why understanding, governance, and global frameworks matter

Artificial Intelligence has rapidly moved from the realm of innovation to an integral part of everyday school life. From adaptive learning platforms and behaviour analytics to AI-powered administrative assistants, education technology has embraced AI’s potential to improve teaching efficiency and learning outcomes. As schools and Multi-Academy Trusts adopt these tools, the need for responsible, transparent, and well-governed AI usage has never been more critical.

Over the past few years, we have seen an explosion in educational AI tools worldwide. In the United Kingdom, platforms such as Century Tech and Atom Learning personalise student learning pathways by identifying knowledge gaps and adjusting content in real time. In the United States, our partner Toddle employs adaptive algorithms to enhance teaching strategies and assessment design. Across Asia, tools like Classera are pioneering AR visualisation with their C-Reality app, bringing students into immersive scenes to enrich their learning. Our own education product, Deesha AI, is an AI-enabled analytics platform designed specifically for educational leaders, giving intuitive insights that help drive data-informed decisions.

These solutions offer huge benefits: reduced workload, targeted interventions, and highly individualised learning experiences. Yet the opportunities come with equally significant risks. AI systems rely on extensive, often sensitive data. For schools, this raises questions around safeguarding, ethics, explainability, and long-term sustainability. School leaders are increasingly expected to understand the technology that underpins the tools they purchase. Vendor assurances are no longer enough.

A tale of two schools: The cost of ignoring AI governance

Consider two schools adopting the same AI-driven assessment tool.

The first rolls it out quickly and sees immediate gains in marking efficiency and personalised pupil recommendations. But by the end of term, concerns arise about how students with additional learning needs are being assessed. The system’s training data had not been adequately representative, a problem discovered only after parental concerns were raised.

The second school moves more cautiously. It conducts a Responsible AI review, asks what data the tool accesses, how recommendations are generated, and how algorithmic fairness will be monitored over time. With these AI governance frameworks in place, the school deploys the tool with confidence and can demonstrate clear oversight when questions arise.

The lesson is clear: AI can be transformative, but without AI governance and understanding, it can undermine trust.

You’ve seen the risks of reactive deployment in the ‘Tale of two schools.’ If you’re serious about shifting from historical reporting to proactive, responsible AI deployment, it’s time to see the solution in action. Book a demo today to explore how Deesha’s AI governance features protect your students and empower your leaders.

The growing influence of global AI governance frameworks

Part of understanding AI in education means recognising the global frameworks that increasingly shape how AI must be built, deployed, and monitored.

The European Union’s AI Act represents one of the most comprehensive approaches to AI regulation. It classifies many education-facing systems as high-risk and places strict governance and compliance responsibilities on providers. Exploring how the EU AI Act views education providers gives valuable insight into what may emerge in the UK’s own regulatory landscape - and how student and staff protections may evolve. This will be the focus of Blog 2 in this series.

Meanwhile, EU schools are already embedding responsible AI usage into their curriculum, preparing students to become “multiliterate”—critically evaluating and analysing AI-generated content. 

Intergovernmental frameworks also play a major role. UNESCO’s Recommendation on the Ethics of AI and the OECD’s AI Principles emphasise fairness, transparency, human rights, and education’s special duty of care. These are not laws but global standards shaping what responsible practice should look like, and will be explored in Blog 3 of this series.

Voluntary frameworks, such as the NIST AI Risk Management Framework, provide practical tools for assessing risks, guiding procurement decisions, and establishing internal governance processes. In 2024 and early 2025, I worked across Canada, Australia, and the UK implementing variations of NIST’s framework in higher education settings - helping colleagues confidently use AI tools while ensuring robust oversight. These experiences will be discussed in Blog 4.

AI Governance in education requires leadership from experts who understand both policy and the classroom. Meet the Deesha founders to learn about the educational strategy and ethical principles guiding our platform's development.

Why responsible AI matters for UK schools (and global educators)

The UK government’s “pro-innovation” stance aims to balance economic opportunity with AI safety. The country is positioning itself as a global AI exporter, while simultaneously building regulatory and standards-based infrastructure to ensure responsible AI usage. This is not without tension: how do we encourage innovation and international trade without exposing young people to untested or unsafe EdTech systems?

Local regions are stepping up too. Liverpool’s ambitious AI plans, discussed at the November 2025 Brilliant Festival, highlight the momentum behind AI-driven growth. The appointment of Tiffany St James as the UK’s first regional Chief AI Officer marks significant progress not only for responsible AI leadership but also for visibility of women at senior levels in STEAM. Her commitment to responsible implementation was particularly encouraging to me but as I glanced around the keynote auditorium, looks of fear or boredom were common when discussing this far more serious side to AI. The crowd were keen to get back to the video of school children speaking to how their newly tested AI tools had help them with their expanded noun phrases.

But because responsible AI doesn’t have a glossy video testimonial, it doesn’t mean that we shouldn’t pay attention, and it doesn’t mean that student’s lives won’t be positively impacted by its implementation. As the UK accelerates its AI capabilities, the education sector must ensure that young learners remain at the heart of every AI-driven decision.

Responsible AI in Education is more than just compliance; it’s about institutional values. Learn more about the experienced educational strategists who founded Deesha. Visit our About Us page to discover our commitment to EdTech ethics and how our platform is built on principles of algorithmic fairness and transparency.

Building trust through responsible AI: Practical questions for leaders

Responsible AI usage ultimately comes down to trust: between institutions, educators, learners, and the technologies they rely on. Key questions educators should be asking during AI procurement include:

• How is student data collected, stored, and protected?

• Are algorithmic decisions transparent, explainable, and fair?

• Does the technology reflect our educational values and safeguarding expectations?

• Can we evidence oversight, AI governance, and accountability?

Practical next steps for school leaders include mapping which global AI frameworks affect your suppliers, asking vendors for evidence of risk-based assessments, and embedding student-centred impact reviews into procurement. These actions will be explored in more depth in the final blog of this series.

What to Expect in This Series

Over the coming months, this series will dive deeper into:

• The EU AI Act and its implications for education

• OECD’s AI Principles – a question of ethics

• NIST AI Risk Management Framework

• AI intention-setting for staff and students and How to establish a Responsible AI Framework in your setting

The journey to proactive AI governance and ethical EdTech starts with the right platform. If these governance challenges resonate with your leadership team, take the definitive next step. Book your personalised Deesha demo today to see our Responsible AI features, unified data, and predictive insights in action.

While you wait for the next post in this series, continue to build your expertise. Discover our other blogs on achieving data maturity, closing the attainment gap, and simplifying data infrastructure for MAT leaders.