Dr Inga Olari, Programme Leader in Law, explores how AI reshapes lifelong learning, inclusion, academic judgement and equity in universities.
AI and lifelong learning: promise or risk?
Artificial intelligence is no longer a future possibility for higher education; it is already reshaping how learners’ access, experience, and continue their education throughout life. The question is not simply whether universities should adopt AI, but whether they can do so responsibly without reproducing existing inequalities in new and more technical forms. The need for lifelong learning is increasing as automation, digital work, and professional change require adults to refresh their knowledge and skills throughout their careers. However, technology does not automatically create opportunity. Its value depends on how wisely institutions govern it, how inclusively they design it, and how carefully they protect the learners who may otherwise be left behind.
What AI can make possible
Thoughtfully, AI can be applied to an open learning process. Adaptive systems can accelerate things, propose resources, and provide quicker formative feedback. Learning analytics would help the employees to observe the student when he or she might need something, and when they were about to engage in non-confrontation by isolating themselves. Online micro-credentials and daily online modules may also help working adults, carers, and distance learners further their studies without quitting their jobs and family responsibilities. This is where AI can play the most significant part: it does not shut down universities but just frees the process and makes it more appropriate, timely, and personal. Having an immediate answer and convenient online support, out-of-school learners may reduce the amount of anxiety and support perseverance. In terms of institutions, they can reveal trends that would almost go undetected in cohorts that are large or dispersed.
Why inclusion cannot be assumed
The danger is that access can be mixed up with inclusion. Online and off-limits courses can occur when the students lack reliable devices, connectivity, quiet places to study, self-confidence, or computer skills. Students who are already prepared to navigate through academic and technological systems may be the ones who are most likely to benefit from AI-supported learning. In the absence of special focus, AI is more likely to increase than reduce gaps in participation. Beneath there are greater ethical issues. The algorithms that are trained using historical data can replicate prejudiced assumptions concerning ability, risk, and progress. Surveillance becomes possible when learning analytics are not in the eyes of the students, what information is captured, how it is processed, and by whom the action can be taken based on this information. Another domain that Generative AI is upsetting is assessment because low-understandable work can be obfuscated by the final products. That is why UNESCO (2023) believes that regulation ought to be people-centred and must engage in capacity-building and educational governance, rather than simply following.
The educator still matters
AI will not reduce the role of the educator but transform. Automated systems can facilitate routine feedback, whereas academic judgement, dialogue, ethical reasoning, or relationship building process to build confidence cannot. Learning throughout life cannot be a kind of funnel of competencies badges, which are labour-market oriented. Critical thinking, disciplinary depth, and civic purpose must still be guarded by universities. This means that the key one is staff development. To believe in AI, lecturers must be AI literate, but to distrust it. They must know what systems help to promote the learning process, where it is deformed, and they must know when they must analyse accepted human signals. Students should also be taught to use AI responsibly, as a ban on technologies does not contribute much to developing judgment; a properly designed interaction does.
What universities should do now
The moral is evident in the practical lesson. The institutions will have clear data practices, an open digital base, open design that is open-ended, employee training, and evaluation models that will pay off application, introspection, and resolution. The questions that they need to ask themselves when considering AI tools are: who wins and who loses; what is the evidence, and what human protections are provided? The concept of AI-assisted lifelong learning can be transformed into the direction towards a more balanced form of participation, which, nevertheless, remains not a priority among universities as an educational, rather than a technical, skill. Platforms are not going to be the future. It will be impacted by institutional choices on equity, trust, and purpose. So, how can higher education play a role in unlocking lifelong learning and protecting those learners whose lives are most negatively affected by the threat of being left behind by AI?
Dr Inga Olari is Programme Leader in Law for the Law Undergraduate Programmes with St Mary’s University Twickenham, and Fellow of the Association of Higher Education Professionals (AHEP). Her work focuses on legal education, inclusive pedagogy, AI in higher education, student success, and academic leadership. She has presented internationally on digital learning, lifelong learning, and culturally inclusive teaching practices
