Graduate skills and education in an AI-enabled economy

Economists have been trying to predict how Artificial Intelligence (AI) will transform the world of work. Not surprisingly, there are widely varying views on the skills which graduates of the future should develop to augment AI adoption in businesses. This is the backdrop against which AI is changing how business schools develop the skills and employability of our graduates.

There is a fear that AI will destroy graduate jobs. US graduate unemployment hit 5.7% in late 2025, well above the 4.2% rate for the workforce overall, with 43% of new graduates underemployed. These are the worst figures since the pandemic. The National Association of Colleges and Employers (NACE) Spring 2026 survey shows the share of entry-level jobs requiring AI skills has nearly tripled since autumn 2025, to over a third.

As some leading economists have noted, the impact of a new general-purpose technology like AI will also play out gradually and will vary markedly between graduate roles. Tera Allas, Senior Adviser at McKinsey & Co notes that the recent reductions in job openings in the UK for graduates seemed higher in some sectors exposed to AI, but not in others such as Finance, ICT, Engineering and health professionals. Overall, there is little evidence in UK data that AI adoption has already filtered through to changes in employment or productivity. However, change is coming. Nick Bloom, of Stanford, at a recent conference at the San Francisco Fed, notes that the use of AI is higher in younger, larger, and more productive firms. One would therefore expect the impact of AI to accelerate fast.

And whilst the impact is heterogenous between jobs, employers' and students' expectations are already changing. The university sector, and business schools within it, face a key strategic problem: a growing gap between the demand for substantive AI training and what the higher education sector currently offers.

Business schools must shift their pedagogy rapidly. Accreditation bodies have played a very helpful role here. For instance, the Association to Advance Collegiate Schools of Business (AACSB) published a major report from 50 schools on how business schools are scaling AI pilots rapidly. The key developments include ensuring that the ability to understand and use AI is seen as a core competency for business school graduates. The report also covers important areas such as assessment integrity and the ethics of AI usage. The Chartered Association of Business Schools (CABS) is contributing to CPD for educators in business schools on AI literacy.

This demonstrates the ability and willingness of business schools to adapt to the realities of AI. Accreditation bodies and employers also note the importance of combining training of AI use in thinking, analytical abilities, and emotional intelligence. All elements - from learning to assessment - must be aligned to both these dimensions.

From the perspective of graduate employability, the evidence is quite clear. McKinsey reports that the demand for AI literacy and fluency has increased seven-fold since 2023. The ability to use AI critically and ethically and to deploy them to enhance management tasks will be key to the employability of future business school graduates. A key question, however, is how this will impact on hiring practices. There is some evidence that companies hiring may wish to shift to skills-based hiring rather than just on the basis of educational qualifications.

This in turn will impact greatly on how business schools will demonstrate how they are adapting to the AI revolution when attracting potential students. To date, student demand for business school courses has been driven mainly by reputation: both of the global ranking of the university where the school sits, and the league tables based on specific Masters by specialist publications such as the Financial Times. It is rare for student applicants to investigate the details of each course component and the nature of assessment when applying for a course and deciding where to study. But that is likely to change as students perceive the importance of the skills they will learn in their chosen business school and university destination.

This raises the question of whether 'signalling behaviour' will continue to shape employer hiring decisions and, consequently, prospective students' choices of universities and business schools. It is here that economic theory intersects with marketing. In labour markets, hiring is an investment under conditions of uncertainty. Because employers cannot perfectly observe a graduate’s true productivity prior to hiring, so they rely on observable signals – such as degree classification, institutional reputation and university rankings to infer underlying ability and potential. If it wasn’t costly to acquire this information about all graduates, companies would place less emphasis on qualifications or the reputation of the institution where a graduate has studied.

In practice, however, signalling is unlikely to disappear from graduate labour markets. While employers may increasingly value AI literacy and fluency, these capabilities will represent only one component of a broader skills portfolio. Information acquisition will remain costly and employers will continue to rely on reputation-based markers when making hiring decisions. Indeed, marketing and brand development may become even more important for business schools as they seek to communicate how AI has been embedded within curricula and how graduates are being prepared for an evolving world. Traditional approaches to reputation management, such as accreditation and rankings, will continue to persist. In our view, the need for business schools to demonstrate and communicate graduate employability will make marketing, brand development and reputation management increasingly central to strategy and to the future competitiveness of the sector as a whole.