AI in all its multitudinous forms is here, it is here to stay, and its impacts are accelerating.
At a basic level, we see shifts in personal office practices with the tentative, steady adoption of large language models. We see AI being used alongside MS Teams or its equivalents to quickly produce summary transcripts of meetings or to generate starting places for documents which are then reworked.
As university educators and researchers, we also see debates regarding the ethics of AI adoption and a splintering ability of the collective and the individual to be able to discern fact from fiction. We are at the start of a long and unpredictable trajectory of impacts.
But, as we shape the skills, knowledge and abilities in our students that will see them thrive in an increasingly disrupted future world of work, where that track takes us is a subject of debate. What is consistently clear across various predictions is that the adoption of AI and increasing automation will deliver seismic changes to the world (of work).
Machine meets human
86 per cent of employers surveyed for the World Economic Forum’s 2025 Future of Jobs Survey saw AI and information processing technologies as being the dominant technology driver for workplace change through to 2030, affecting workplaces across all sectors, not just those welcoming students from STEM disciplines. Similarly, the same survey indicates the greatest rise in demand in the workplace through to 2030 is for the ability to work with AI and big data.
Noting the dominance of AI in the WEF survey findings, we are reminded of the 1998 interview between Jeremy Paxman and David Bowie, happening just as the internet was forming. Paxman queries the internet as being anything more than a “different delivery system,” while Bowie asserts that it is an alien life form:
I don’t think we’ve even seen the tip of the iceberg – the things it will do, both good and bad are unimaginable right now. I actually think we’re on the cusp of something exhilarating and terrifying…
Looking back at what has happened to society in the quarter of a century since that interview, Bowie is unnervingly accurate in his foresight.
It seems that right now we are navigating similarly uncharted territories of an epoch-defining transition as the world starts to play in earnest with the next gen version of Bowie’s “alien lifeform.” Higher education is not immune – it is grappling with the challenges across its core activities.
However, what is of particular interest beyond the specific AI skills is the other in-demand skills that occupy the places immediately following the top three noted above. Fourth is creative thinking, followed by resilience, flexibility and agility, curiosity and lifelong learning and leadership and social influence. These skills are high value cognitive competencies inherently human in their nature – an equalising “soft” counterbalance to the “hard” technological literacies of the top three.
Reflecting on the duality between technological literacy and social, emotional and cognitive skills in this overall picture, it is clear that AI is not a replacement for the work of thought, deduction, critical reasoning and curiosity. Instead, it is a powerful augmentation to the already formidable arsenal of technological capability at our fingertips.
From efficiency to co-creation
With education and the student experience in mind, we see two AI “swim lanes” forming out of the early stages of ubiquity ushered in by the popularisation of ChatGPT and other LLMs. These swim lanes should also acknowledge the broader mix of new and emergent technologies at play in tandem with AI – for instance AR/VR and data visualisation.
The first swim lane speaks to the need to optimise the complex wiring behind the institutional operations of higher education which provide our students with a world class experience. With efficiency, effectiveness and scale in mind, adoption of AI to underpin the crucial in-person experience with wider algorithmic personalisation becomes a highly desirable direction of travel. For instance, we can easily envisage a world in which AI is used to aid student navigation of module choice, tailoring the availability of elective courses and complementary extra-curricular and developmental activities.
The second swim lane is one of invention and co-creation, arguably pushing AI and the wider ecosystem of technological innovation to be the best it can be – far beyond the deployment of convenience or efficiency. At its best, AI can become a partner in creativity: an inspirer and a critical collaborator offering new perspectives. We are seeing promising points of innovation and departure in the early work at Loughborough as the range of technological capabilities within our DigiLabs continues to be adopted at pace.
However, to swim confidently in this lane we must dispel myths and fears with rigour and a critical navigation of AI as a co-creator. Scaffolding and skills development for staff and students are essential in order that we all might partner effectively with our new playmate.
Thinking together
Two points of skills development show themselves as a useful starting place towards consistency, innovation and collaboration in AI partnership. First, a good place to start would be recognition and development of prompt engineering as a fundamental digital skill and a shared structured practice. Second, it would be useful to focus on development of a consistent and structured means to better understand, interrogate and critically evaluate what the AI has generated in response to our prompting.
With frameworks for these two essentials of effective AI partnership in place, we can move beyond the cut-and-paste AI-as-shortcut, and beyond the simple fact checking of generated material. These two skills move us towards conversing and exchanging perspectives with AI, making content better together. The vantage point of having embedded these two AI partnership skills helps us then systematically inculcate the true value of AI by recognising the human skillset with which to strategically cocreate with it, rather than shortcut with it.
As our use of AI evolves, we should continually remind ourselves that understanding is not gained in the endpoint, but in travelling to that place (no student learns that much in the moment of a final assessment). AI becomes a meaningful companion on that journey, not a replacement for the experience of travelling. To shortcut the pleasure and frustration of our own creative and critical journeys by virtue of AI laziness is to deny ourselves the experience of our own essence – the struggle and the unknowing of what it means to question, to be alive and to be human.
