At the end of last year, Professor Becky Francis published her long-awaited Curriculum and Assessment Review for England, accompanied by the UK government’s official response. Buried within that response — and not actually proposed in the Review itself — was a notable commitment: to “explore introducing a new Level 3 qualification* in data science and AI, to ensure that more young people can secure high-value skills for the future and that we cement the UK’s position as a global leader in AI and technology.”
This announcement reflects a growing global recognition that young people need more than basic digital literacy — they need a deeper understanding of data, automation, and the rapidly evolving capabilities of AI. Countries around the world, from Singapore to the United States, are already wrestling with how to embed AI education into secondary schooling. England now joins that international conversation.
Why AI education matters
AI is an everyday technology now. Young people interact with AI systems constantly, often without realising it. Whether they pursue careers in medicine, engineering, the creative industries, or public policy, they will need a foundational understanding of how AI systems work, what their limitations are, and the ethical implications around them.
Yet in England — and in many education systems globally — very few students receive formal teaching about AI. The English national curriculum makes no explicit reference to AI, and specifications for exams taken at the end of high school include only scattered mentions. This gap leaves young people navigating one of the most transformative technologies of their generation with limited guidance.
Exploring a qualification: Opportunities and challenges
In 2025, we joined forces with Professor Lord Lionel Tarassenko, one of the UK’s foremost researchers in AI and machine learning, and Simon Peyton Jones, a world-renowned computer scientist and long-time champion of computing education. Together with teachers, school leaders, universities, industry specialists, and exam boards, we have been exploring how we might begin to close the emerging gap in AI and data science education for 16- to 18-year-olds.
Over the past eight months, this collaboration has allowed us to refine our shared thinking and gather insights from a wide network of experts and practitioners. We are delighted that England’s Department for Education has recognised the potential of this work by appointing us to draft the subject content for a possible new A level in Data Science and AI.
We are delighted that England’s Department for Education has recognised the potential of [the work we have done] by appointing us to draft the subject content for a possible new A level in Data Science and AI.
Designing a qualification of this kind raises important questions — not just for the UK, but for any country considering a similar path.
What knowledge and skills should young people gain from the qualification?
A meaningful qualification must go beyond the use of tools. It should help students understand data literacy, model behaviour, bias, ethics, and the societal implications of AI. Balancing technical understanding with critical thinking is challenging but essential.
How do we ensure the qualification is accessible and inclusive?
AI should not become the preserve of already-advantaged students. Any qualification must be designed with equity in mind, recognising differences in school capacity, teacher expertise, and students’ prior experience.
How do we support teachers to deliver the qualification?
Teacher professional development is a major challenge worldwide. Delivering a qualification in AI will require confidence with concepts that are not yet common in teacher training. Sustainable delivery models — supported by high-quality resources and professional development — will be crucial.
What form should the qualification take?
There is an active debate about whether the best route for students in England is a high-stakes qualification or a supplementary course that broadens a core programme of study:
- An A level provides structure, national recognition, and clear progression into higher education or employment.
- An Extended Project Qualification (EPQ) may offer more flexibility, allowing students to explore AI through research or practical investigation without requiring schools to timetable a full qualification.
Different countries will make different choices based on their systems, but the underlying questions are the same: how do we create something rigorous, scalable, and future-proof?
What we’ve learned so far
In October, the Foundation hosted a workshop with representatives from schools, industry, universities, exam boards, and the Department for Education. Together, we explored key questions including:
- How do we make a qualification compelling – both for students who choose it and for schools that offer it?
- What delivery models will genuinely support teachers to succeed?
The feedback we received has been invaluable and will continue to shape the next stage of development. We believe the UK has a significant opportunity to contribute meaningfully to the global conversation about AI education. You can read the latest version of our discussion paper here.
A global call for insights
Although the current proposal focuses on England, the underlying challenge is international: how do we prepare young people everywhere to engage thoughtfully and confidently with AI?
We would love to hear from educators, researchers, and policymakers across the world:
- Do you know of any successful qualifications or programmes for 16- to 18-year-olds that centre AI or data science?
- What lessons should countries learn from each other?
To share your ideas or feedback, please get in touch. We’d be delighted to learn from your experience as this important work progresses.
* Level 3 in England is the stage of learning for 16- to 19-year-olds, typically ending in qualifications that pave the way for higher study or advanced apprenticeships.
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