The rapid ascent of Artificial Intelligence from a niche technical field to a pervasive societal force has triggered a predictable response from higher education. Across the UK and Europe, universities are scrambling to offer programmes in AI, responding to soaring student demand and the promise of a lucrative job market. Data from the UK’s Higher Education Statistics Agency (Hesa) reveals a dramatic surge, with the number of students enrolled in AI courses trebling since 2019-20 to reach 10,825 in the 2024-25 academic year [1]. This represents a 19 per cent increase in a single year, making it one of the fastest-growing subject areas in the country.

This boom, however, raises critical questions about the nature and quality of the education being offered. Is this a necessary and agile response to a profound technological shift, or is it a market-driven gold rush that risks prioritising enrolment numbers over educational rigour? The conversation is fraught with complexity, mirroring the broader paradoxes of AI's impact on the workforce. While the demand for AI skills is undeniable, the challenge of designing and delivering curricula that can keep pace with a field in constant, rapid flux is a formidable one for educational institutions.

The UK's AI Degree Boom

The growth in the UK is particularly pronounced. The 19 per cent year-on-year increase is the largest by a significant margin for any subject with over 1,000 students [1]. Universities such as Hull, Edinburgh, and Robert Gordon are leading the charge, hosting the largest cohorts of AI students. A notable characteristic of this trend is its reliance on international students, who constituted 56 per cent of the AI student body in 2024-25, with two-thirds of all students enrolled in postgraduate taught courses. This has led some observers, like Professor Simon Sweeney at the University of York, to suggest that universities are pitching these courses to international consumers who are seeking qualifications they believe will lead directly to employment, while UK students may remain more sceptical, preferring traditional degrees in computer science or mathematics [1].

This rapid expansion has prompted warnings from academics. Professor Leo McCann, also from the University of York, draws a parallel to the explosion of forensic science courses following the popularity of television shows like"CSI", cautioning that such programmes can sometimes lack sufficient depth and criticality [1]. The concern is that in the rush to capitalize on a trend, the academic rigour and capacity to deliver high-quality teaching and research may be compromised.

The core of the issue lies in the very nature of Generative AI itself. As Dr. Nisreen Ameen from Royal Holloway, University of London, points out, it is such a fast-moving area that traditional degree structures may struggle to remain relevant [1]. She argues for a fundamental shift in pedagogical approach, where the priority is not just to teach the current state of AI, but to cultivate resilience, adaptability, and the capacity for self-learning in students. This sentiment is echoed by the call for more flexible, modular, and regularly updated programmes that can respond to the evolving needs of employers and society. The alternative is a curriculum that is perpetually out of date, producing graduates whose skills may be obsolete before they even enter the workforce.

A Broader European Perspective: Beyond the Degree

While the UK grapples with the explosion of university-level AI degrees, a recent report from the European Centre for the Development of Vocational Training (Cedefop) offers a wider and perhaps more nuanced perspective on the skills required for the AI revolution [2]. The Cedefop survey, a comprehensive analysis of AI in European workplaces, shifts the focus from the production of elite AI developers to the much broader challenge of upskilling the entire workforce. This is a critical distinction. While specialized degrees are important, the Cedefop findings suggest that the most pressing need may be for widespread AI literacy and the integration of AI competencies across all levels of education and training, particularly within the Vocational Education and Training (VET) sector.

Interestingly, the Cedefop report reveals a more diverse educational profile for the existing AI workforce than one might expect. While many AI developers do hold degrees in computer science, engineering, or mathematics, there is also a significant and growing contingent from business studies backgrounds. Furthermore, the AI workforce has a higher proportion of graduates from medium-level education compared to the rest of the ICT programming workforce (43% versus 40%) and a lower proportion of employees with bachelor's or master's degrees [2]. This suggests that the pathway to a career in AI is not, and should not be, exclusively through a traditional university degree. It underscores the vital role that VET and other forms of training can play in equipping individuals with the necessary skills.

The Skills Gap and the Mandate for VET

Both the UK-focused news and the pan-European research highlight a significant and worrying skills gap. The Cedefop report is stark in its findings: 61 per cent of European workers believe they will need to acquire new skills to cope with AI, yet only 15 per cent have participated in any AI-related training in the past year [2]. A concerning 44 per cent believe it is unlikely their employer will provide the necessary training. This points to a massive deficit in continuous learning and a failure to prepare the current workforce for the transformations already underway.

This is where the direction for for the VET community becomes clear. The conversation cannot be confined to the ivory towers of university computer science departments. The reality of AI's impact is being felt in workplaces across every sector, reshaping tasks and requiring new competencies. The challenge is not just to train a new generation of AI specialists, but to foster what the Cedefop report terms "AI literacy" for all. This means providing accessible, high-quality training that enables workers at all levels to understand, evaluate, and use AI tools effectively and critically.

The proliferation of AI degrees is a clear signal of the technology's economic and cultural significance. However, it is important that this trend does not obscure the broader and more complex educational challenges that AI presents. A flexible, multi-faceted approach is required, one that values vocational training alongside academic degrees, and prioritizes lifelong learning and widespread digital literacy. The future of work in the age of AI will not be shaped by a small cadre of elite developers alone, but by the ability of the entire workforce to adapt and thrive in a world increasingly intertwined with intelligent systems.

References

[1] Jack, P. (2026, February 12). ‘Flexibility needed’ to keep AI degrees relevant as demand soars. Times Higher Education. https://www.timeshighereducation.com/news/flexibility-needed-keep-ai-degrees-relevant-demand-soars

[2] Cedefop. (2026). Skills empower workers in the AI revolution: First findings from Cedefop’s AI skills survey. Policy Brief. https://www.cedefop.europa.eu/files/en_9201.pdf