The graduates entering the workforce in 2030 will encounter a world of work that is difficult to predict with any certainty. The technologies they use, the tasks they perform and even some of the roles they enter may look very different from those we recognise today. That creates a fundamental challenge for higher education.
Preparing students for 2030 cannot simply mean teaching them to use the AI tools available today. The graduates who thrive will not necessarily be those who know the most about today's technologies, but those who are equipped to adapt as technology and work continue to change. For me, this is one of the most important points in the conversation about AI and employability. As technology becomes more capable, human skills do not become less valuable. In many situations, they become more valuable. Communication, collaboration, curiosity, creativity, empathy and problem-solving skills allow people to interpret information, challenge assumptions, work with others and make decisions when there is no straightforward answer.
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The scale of that change is already becoming clear. The World Economic Forum's Future of Jobs Report 2025 estimates that 39% of workers' core skills will change by 2030. While AI and big data are among the fastest-growing areas of skills demand, employers also expect analytical and creative thinking, resilience and flexibility to remain important. This has implications for what students should experience during their degrees. Universities need to prepare students for careers in which the skills required, working practices and routes into employment will continue to evolve.
{{/usCountry}}The scale of that change is already becoming clear. The World Economic Forum's Future of Jobs Report 2025 estimates that 39% of workers' core skills will change by 2030. While AI and big data are among the fastest-growing areas of skills demand, employers also expect analytical and creative thinking, resilience and flexibility to remain important. This has implications for what students should experience during their degrees. Universities need to prepare students for careers in which the skills required, working practices and routes into employment will continue to evolve.
{{/usCountry}}AI is already reshaping some of the entry-level tasks through which graduates traditionally developed professional skills and learned how organisations operate. If those opportunities change, universities will have an even greater role in creating meaningful ways for students to develop professional judgement and workplace confidence.
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Students need opportunities to apply what they learn in the classroom to problems that don't have textbook answers. They should be able to work with employers, collaborate across disciplines and engage with people from different cultures and perspectives. They also need opportunities to deal with ambiguity, make decisions, learn from mistakes and understand how their knowledge can be applied in real working environments.
This is why employability should not suddenly become a priority in a student's final year. It needs to run through the university experience from the first week. Students should have opportunities throughout their degrees to explore careers, build professional networks, gain work-based experience and reflect on the skills they are developing.
The recent Future Jobs Roadmap from Universities UK reinforces this direction, including an ambition for all undergraduates to have access to meaningful work-based learning, AI tools, closer employer involvement and careers support beyond graduation. The underlying message is important: the transition from education to employment is not a single event at the end of a degree. It is part of a longer process of learning and career development.
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AI literacy will matter across disciplines, not only in computing or other technical subjects. Graduates entering business, healthcare, communications, finance, education, creative industries and public services are likely to encounter AI in different forms. Being AI-literate does not mean becoming an AI expert. It means understanding what these systems can and cannot do, knowing how to use them appropriately, questioning their outputs and recognising issues around accuracy, bias, privacy and ethics. Just as importantly, graduates need to know when technology can support a decision and when human judgement needs to remain central.
AI is also changing how graduates are recruited, with tools supporting application screening, candidate assessment and interviews. Careers practitioners have an important role in helping students navigate this environment and use AI ethically and tactically: to research opportunities, interpret job requirements, refine applications and practise interviews. This includes supporting students to question AI-generated suggestions, follow employers’ guidance and ensure their applications accurately reflect their experience.
Where AI-generated language risks making applications increasingly similar, practitioners can help students identify the specific experiences and strengths that distinguish them. Through reflection, encouragement and constructive challenge, they can help students retain their own voice and develop the judgement to decide when and how AI can support them.
The future of employability, therefore, should not be framed as AI versus human skills. The two are increasingly interconnected. A graduate who can use AI to analyse information but cannot communicate their conclusions effectively may be limited. Equally, a graduate with strong communication and critical-thinking skills who does not understand how to work with emerging technologies may find it harder to operate effectively in some workplaces.
Universities cannot prepare students for this changing environment alone. Employers can help education providers understand how roles and expectations are evolving and create opportunities for students to engage with authentic workplace challenges. Alumni can provide insight into changing career pathways and the skills being used in practice. Careers services can help students make sense of these experiences and connect them to their longer-term development.
Ultimately, the task is not to predict exactly what the workplace of 2030 will look like. It is to prepare graduates for a future we cannot fully predict.
For the Class of 2030, that means more than knowing how to use the latest technology. It means having the confidence to learn new tools, the critical thinking to question them, the adaptability and curiosity to keep developing and the human skills to work effectively with others. Those capabilities can help graduates navigate not just their first job, but a career shaped by continued change.
(Author Matthew Howard is the Deputy Head of Student Careers, University of Leeds)