In his most celebrated poem, Digging, Nobel laureate Seamus Heaney looked back across generations of his family working the land and cutting turf from Ireland’s bogs. In admiring his father’s mastery of the spade, he recognised that his own working life would require different skills. His tool would be the pen: “I’ll dig with it.”
At the time Heaney was writing, the manual work he described was being radically transformed by mechanisation. In 1959, only 13 per cent of turf was mechanically harvested; within a decade, that figure had risen to 93 per cent. Work changed, and people had to learn to use different tools.
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Artificial intelligence may drive a similar transition but at much greater speed. It is changing not only individual jobs but the assumption that education is mostly completed before a career begins. A degree can no longer be the end point of the university-learner relationship. Increasingly, we need to think about a relationship that might last 30 or 40 years.
Making education part of a full career timeline
Universities are very good at educating people for their first career. We are less well designed to help them adapt throughout it. Here are five lessons for extending the education timeline.
1. Make it easier to return
People will return to education from very different starting points. Some might have been away from formal learning for decades; others might have substantial professional expertise without the conventional qualification required for further study.
At Queen’s University Belfast, we have developed bridging short courses and microcredentials to help learners move into new areas, alongside approaches to recognising prior experience and capabilities. AI can potentially help here: mapping capability, identifying gaps and suggesting appropriate bridging learning. Used well, technology can make the route back into education more personalised without lowering the standards needed to succeed.
2. Make learning genuinely flexible
If people are returning to education while working, provision has to fit around their employment, families and caring responsibilities. That might mean intensive blocks for subjects requiring laboratories, a designated day each week or online and hybrid models combining asynchronous material with live teaching.
But flexibility cannot simply mean putting content online and leaving learners to work through it alone. Interaction with academics, practitioners and fellow learners remains part of the value university adds. Technology should increase access to human expertise rather than remove the human experience from education.
3. Build qualifications that are sustainable, scalable and stackable
Flexible learning can be seen through three principles: whether it is sustainable, scalable and stackable. A learner might need only a short course today but might look to accredited microcredentials as a route towards a postgraduate certificate, diploma or master’s over time. That gives immediate value while keeping a visible next step open.
Stackability can also make qualifications more responsive to real-world needs. Flexible umbrella qualifications could allow learners to combine accredited learning from different disciplines as their role and skills needs evolve.
4. Use your networks as a radar – and respond quickly
Universities sit at an unusual intersection of research, innovation, employers, professional bodies, government and learners. That gives us an extraordinary radar for emerging capability needs, if we use it deliberately.
Our Innovation Centres work closely with organisations adopting technologies including AI, advanced manufacturing and cybersecurity. Alongside employer-engaged postgraduate projects, practitioner teaching and curriculum conversations, those relationships can identify changes before a skills gap becomes firmly established.
The challenge is then speed. If identifying a need, developing provision and navigating approval takes 18 to 24 months, the requirement may have changed again. We need proportionate routes that allow a new need to be tested through a masterclass or short course, developed into an accredited microcredential where demand is clear, and ultimately fed into larger programmes. Lifelong learning should help the university learn, too.
5. Make lifelong learning affordable
Shorter courses and stackable microcredentials make returning to education more achievable both financially and in terms of time. But if people are expected to return several times during a career, the cost cannot sit with the individual alone.
Government, employers and learners all have a stake. The Irish government, for example, committed €9.7 million (£8.35 million) in 2024 to subsidise almost 14,000 university microcredential places, while Northern Ireland’s Department for the Economy has funded short courses and microcredentials linked to workforce needs. This support has allowed Queen’s to build and test new forms of provision alongside employer-informed learning.
The future is here already
The question is perhaps no longer whether universities have a role in lifelong learning but whether institutions designed predominantly around a three- or four-year educational experience can redesign themselves around relationships with learners that could last 40 years.
That means changing how people enter university, when and how they study, how qualifications are constructed, how quickly we respond and who pays. AI could help us personalise pathways and scale access but the goal should remain human: helping people continue to learn, adapt and progress throughout their lives.
Heaney’s spade and pen remind us that the tools of work change. AI might mean that they change several times within a single career, and keep changing. Our learners – and our universities – must be able to change with them.
Aidan McGowan is dean of postgraduate studies at Queen’s University Belfast and a national teaching fellow.
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