Executive Summary: Beyond the Hype

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This report examines the findings from 256 schools and colleges across England who completed a comprehensive self-assessment of their AI preparedness and use between February and May 2024. It follows on from 'The Shape of the Future' report, published in September, and reveals a sector poised for transformation yet struggling with the practicalities of harnessing AI's potential.

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To provide deeper context, we have integrated findings from complementary research, including Jisc's survey of 600 participants, HMC's study of 88 institutions, and two recent government reports about AI in Education. We also examine how other leading nations are tackling the AI 'Gold Rush'.

 

If you would like to know more about what other countries are doing with AI in Education, you can register your interest in the Educate Ventures Research new international AI review service.

 

Key Findings from Our Benchmarking Data

1. Institutions Face an Awareness-Implementation Gap: Whilst 87% of respondents reported understanding general AI concepts, only 38% felt confident using AI in the classroom, highlighting a significant disparity between theoretical knowledge and practical application (Figure 4, page 13).

2. Independent Schools Outpace State Schools in AI Readiness: For example, Independent schools scored more highly in implementing safeguards (3.10 vs 2.51) and bias awareness (3.62 vs 2.99 ), see Table 4, on page 25. They demonstrated clearer educational goals (3.09 vs 2.44) and impact assessments for AI use (3.09 vs 2.51), Table 5, page 29, and clearer approaches to AI piloting (2.91 vs 2.24), Table 3, page 21.

3. Too Few Have AI Policies in Place: Only 30% of institutions report having an AI policy or strategy in place, underlining a critical lack of formal AI guidance (Figure 12, page 23).

4. Training and Continuing Professional Development (CPD) are Key: Institutions with AI-focused CPD programmes are positively correlated with the clearer identification of educational goals for AI use and higher AI use by teachers, for example (Table 4, page 25).

5. The Sector is 'Grappling' with the Ethical Challenges of AI: While 75% of respondents were aware of potential AI biases, few reported having concrete strategies to mitigate these risks, highlighting a gap between awareness and action (Figure 15, page 28).

6. Common Use Cases: Creating resources and materials emerged as the most prevalent AI application, aligning with findings from both Jisc and HMC surveys (Figure 7, page 18).

7. Students Embrace AI at Home, Schools Play Catch-Up: Pupils are more likely to use AI tools for learning at home than in the classroom, highlighting potential opportunities and challenges for schools. While this trend could enhance learning, it also raises concerns about widening the digital divide (Table 2, page 16; see also Section 8, page 30).

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Additional Insights

The combined evidence from our research, alongside Jisc and HMC surveys and the two recent government reports, highlights a critical gap: whilst awareness of AI's potential is growing, implementation remains patchy and inconsistent. This disparity must be urgently addressed to ensure equitable and effective AI adoption throughout the nation's schools and colleges.

 

It is also clear that schools and colleges need:

• Comprehensive professional development;

• Evidence to support an evidence-informed approach to AI adoption;

• Robust safeguarding measures;

• Strategies tailored to different educational contexts;

 

The two recent government reports reveal a complex landscape of AI adoption in UK education, which also highlights disparities between independent and state schools, and evolving public attitudes. They too underscore the need for clear policies, and ethical guidelines to address concerns about overreliance on AI, data privacy, and educational equity.

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International Comparisons

Our international analysis reveals that whilst schools and colleges across England share common AI challenges with their global counterparts, several nations have made greater strides. Singapore and Estonia demonstrate more advanced strategic planning and implementation, whilst Finland offers a model of integrating AI considerations into a holistic educational philosophy, potentially reducing some of the disparities seen in England.

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England also has strengths: a widening recognition of AI's transformative potential, and the positive impact of professional development programmes where they exist. As we navigate this rapidly evolving landscape, collaboration and knowledge-sharing will be crucial for collective success.

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Conclusion

Overall, the findings reported here underscore the importance of a coordinated, strategic approach to AI integration that considers both institutional readiness and public acceptance.

 

Priorities should include:

1. Developing robust professional development programmes

2. Establishing clear AI policies

3. Addressing ethical concerns systematically

4. Developing an evidence base about the impacts of AI applications

5. Bridging the widening gap between well-resourced and under-resourced institutions to prevent AI from exacerbating existing educational inequalities

 

As the education sector navigates this transformative period, collaboration among educators, administrators, policymakers, and technology providers will be crucial. By addressing these challenges head-on and learning from international best practices, we can harness AI's potential to create more personalised, effective, and equitable learning for all students across England.