Strategic Ways to Bring AI into Education

Artificial Intelligence (AI) is reshaping industries across the board, and education is no exception. Recognising its potential to improve teaching and learning, the UK government has introduced initiatives to integrate AI into schools (link). These efforts aim to tackle challenges such as teacher workloads, improving assessments, and creating more inclusive classrooms. However, realising these benefits requires careful planning, strategic investment, and collaborative oversight. By keeping the focus on improving educational outcomes, stakeholders can ensure these technologies deliver meaningful change.

One of the first steps in this journey is choosing the right developers to create AI tools tailored for education. Large tech companies bring significant resources, but smaller, specialised teams often contribute innovative ideas and greater flexibility. Combining the strengths of both can result in tools that address the specific needs of schools while avoiding over-reliance on a single provider. This balanced approach ensures diversity in development and creates a solid foundation for AI solutions that are adaptable and effective. Building on this idea, maintaining a healthy mix of providers also promotes innovation and competition, which are critical for long-term success.

Equally important is ensuring independent oversight to guide the development and implementation of AI tools. Without impartial input, there’s a risk that commercial priorities could take precedence over what truly benefits teachers and students. To prevent this, educators, AI researchers, and educational psychologists should work together to evaluate and refine tools, ensuring they are both ethical and practical. This collaboration guarantees that the tools align with educational goals. Linking back to the central theme, independent oversight is essential to making sure AI tools genuinely support learning and teaching.

To avoid financial and operational difficulties, it’s important not to rely too heavily on “big-name” providers like OpenAI or Google. While these companies offer robust systems, they often come with high costs and limited flexibility. Open-source AI solutions, developed through collaborations with universities or research groups, offer a more sustainable alternative. This approach highlights the idea that autonomy and cost-effectiveness are key to building AI systems that truly benefit education.

To ensure resources are used wisely, efforts should focus on areas where AI can make the greatest impact. For instance, GenAI (generative AI) potentially excels in helping students improve their writing by providing detailed feedback on essays. In contrast, tools for grading maths and science tasks are already highly effective. Concentrating on enhancing existing systems or exploring untapped opportunities ensures that efforts remain targeted and impactful.

Of course, the success of AI in education depends not only on the tools themselves but also on the people using them. Teachers need the right support to feel confident integrating AI into their classroom practices. The rollout of the National Grid for Learning (NGfL) in the late 1990s demonstrated the importance of pairing new technology with proper training. Similarly, AI implementation must include hands-on training, ongoing support, and practical resources.

This is the perfect time to seize this opportunity and create a more dynamic and fair education system. By linking these strategies— diverse development, independent oversight, open-source solutions, and focused implementation—we can ensure that AI serves the real needs of students and teachers. With collaboration and careful planning, AI can potentially enrich classrooms and shape a more inclusive, innovative, and successful future for education.