As Keir Starmer announced ambitious plans for UK AI growth at London Tech Week, and Rachel Reeves outlined £86 billion in the Spending Review for tech funding, British policymakers and institutional leaders must ensure that AI skills investment accompanies infrastructure investment.
Generative AI has been transforming how businesses operate and changing the skills most valued by employers. Institutional leaders must react to attract, develop, and retain top talent in the AI age. There is a huge emphasis on retraining and recalibrating business priorities around AI skills. Learners are responding accordingly: AI essentials, prompt engineering, machine learning and LLM knowledge have all skyrocketed in popularity over the past three years among British learners.
The pace of AI-related change is unprecedented. ChatGPT reached 100 million monthly active users in just two months after its launch, making it the fastest-growing application to achieve that milestone at the time. This is significantly faster than the internet, which took about 7 years to reach 100 million users. AI is not just on par with the internet or pandemic for its impact on the future of work – it’s greater by several orders of magnitude.
Its impact is being felt keenly across the business world. It is creating new economic opportunities for scaleups and startups, empowering tech providers to integrate new capabilities, and allowing companies of all sizes to implement AI tools for productivity and efficiency. Skill development trends are reflective of this opportunity. In 2025, nearly 700 GenAI courses averaged 12 enrolments per minute – a dramatic increase from 1 per minute in 2023, and 8 in 2024 – making GenAI the fastest-growing skill category on Coursera.
While there have been drastic changes in the past three years, it’s important to remember we are still in the infancy of modern AI. Many companies are still experimenting with emerging technologies and their applications. But we’re gradually moving out of the sandbox towards mature real-world AI integration. To ensure that the UK’s businesses can do so effectively, we need a workforce equipped with the necessary skills.
AI skills challenges in the UK
On the global AI leaderboard, the UK’s rank, ahead of some major European peers (including Germany (14th), France (23rd), and Spain (28th)) and China, indicates that it is well-placed to become an AI leader. This is according to our inaugural AI Maturity Index, which measures a nation’s strength in AI research, innovation, and learning.
With this insight, we can see that while the UK is placed competitively – 13th out of 109 countries – it is still lagging behind European leaders and the United States. There is intense regional competition as nations strive to attain AI maturity – of the top ten in this Index, seven are European. The UK is having to vie with its close neighbours for AI superpower status. To achieve its ambitions, it must pair bold infrastructure investment with equally bold skills development.
In 2023, in the wake of the ChatGPT boom, the UK’s AI sector grew 30 times faster than the wider economy. We’re now operating in an AI-driven economy, with individual British learners seeking to meet a 99% surge in employer demand for AI and ML skills. This urgency is reflected in a 118% spike in GenAI course enrolments among UK learners, a solid leap – but still trailing the global average growth of 195%.
However, the distribution of AI skills remains uneven. Just 28% of GenAI learners in the UK are women, and only 34% of women are engaging with STEM courses, risking a gender imbalance that could stall inclusive progress and universal product utility. Meanwhile, cybersecurity – essential to safeguarding a digital AI-powered economy – saw only 6% growth in skills uptake, despite more than 25% of UK businesses hit by cyber-attack in last year, signalling an area needing immediate additional attention as the UK aims to lead in the digital economy.
What needs to happen to prime the UK for AI success?
The UK’s ambition to become a global AI skills hub is just one piece of a much bigger puzzle: closing the digital skills gap that’s draining £63 billion from the UK economy every year. The surge in demand for AI innovation will only accelerate, and it must be matched by a comparable surge in talent supply if the UK wants to lead, not follow, in the AI race.
Any serious claim to AI superpower status relies upon raising AI proficiency across the entire UK workforce, not just a select few. To be an AI innovation leader demands that the country is an AI skills leader. This requires fixing the AI gender skills gap, which already threatens to limit the potential of the sector before it reaches maturity. It means broadening our investment in digital skills, especially in fields like cybersecurity, which are critical to supporting and protecting an AI-powered economy.
We also need to learn from peer nations that currently outperform the UK. Countries across Europe, including Estonia, Denmark and Switzerland, and beyond are making significant strides in closing their skills gaps and preparing their workforces for an AI-driven future. The UK should study and adapt these successes, ensuring we remain competitive and ready, and focus on leadership driving education and skills development programmes, with three key steps focused on this goal.
Three practical steps for the UK’s AI skills strategy
- Embed AI learning across all levels of education
Efforts to equip learners with AI literacy must begin early and continue throughout the lives of UK learners. The UK should integrate AI, data, and computational thinking into primary and secondary curriculums, expand vocational AI pathways, and partner with universities to scale practical, industry-aligned AI modules across disciplines. This builds a broad base of AI familiarity while nurturing deep expertise for advanced roles.
- Incentivise workforce upskilling and employer investment
Keir Starmer committed an extra £1 billion of funding to scale up our compute power by a factor of 20, but skills investment must accompany infrastructure investment. To close the immediate AI skills gap, the UK can introduce tax incentives and funding programmes encouraging employers to upskill workers in AI, machine learning, and complementary areas like cybersecurity and data ethics. Collaboration with industry to co-create AI bootcamps, apprenticeships, and micro-credential courses will ensure training aligns with real-world needs, empowering workers across sectors to confidently use and adapt to AI tools.
- Champion inclusive AI skills development
Advancing AI skills must go hand-in-hand with closing gender and diversity gaps in tech. The UK should invest in targeted scholarships, mentorship schemes, and community-led programmes to encourage underrepresented groups to pursue AI learning. This ensures the UK’s AI workforce reflects the diversity of its population, unlocking a wider range of perspectives and strengthening the ethical, practical, and innovative use of AI across the economy.
Seizing the future of AI
We are at the dawn of a monumental shift in the tech landscape. Modern AI is still in its infancy, and the UK is well- placed to grow into one of the world’s leading AI economies. But this future is not guaranteed. Whether these ambitions flourish or falter will in large part depend on skills development: can we equip our workers with the right skills, at the right scale, at the right time?
A country’s true AI strength isn’t measured solely by the sophistication of its models but also by the readiness of its people to harness those models in economically and socially productive ways. To become the AI leader it seeks to be, the UK must be a nation of individuals equipped not just to use AI as consumers, but to innovate with it, challenge it, and guide its development responsibly.
Nikolaz plays a key role in shaping Coursera's strategic investments and growth initiatives across the region. In this role, he works closely with the global leadership team to define the business strategy and drive progress across Coursera's consumer, degree, and enterprise segments.
Nikolaz brings over 20 years of experience to Coursera. Prior to joining the company, he served as EMEA Cloud and Partner Lead at NetApp, following a 17-year stint at Microsoft where he scaled the company’s EMEA operations. A passionate people leader and innovator, he holds an M.B.A. in Marketing & Finance from ESSEC Business School.
