AI-powered learning is a story about people, not machines

In the ever-evolving development of education, we are now crossing another critical threshold – one defined not merely by digital tools or online platforms but by the convergence of human intellect and machine intelligence. Artificial intelligence (AI) is no longer confined to the realm of speculative fiction; it has become a transformative force in reimagining what learning can and should be.

As with previous paradigm shifts – such as the printing press, the industrial revolution, the democratic revolution, universal public schooling and the internet – AI holds the potential to reshape education for the 21st century and beyond.

This transformative potential, however, is not automatic. It must be intentionally cultivated. For AI-powered learning to truly elevate K-12 and higher education, it must be implemented ethically and inclusively, and be pedagogically sound. This article explores the contours of this unfolding educational landscape, reflecting on how AI might reframe our notions of teaching, learning and human development.

From static to dynamic learning environments

Traditional classrooms tend to be, to a large extent, siloed environments which can emphasise rigid disciplinary learning at the cost of more fluid, interdisciplinary learning. With AI, learning has the potential to become a more dynamic, adaptive and personalised process.

Intelligent tutoring systems (ITS), for instance, can now analyse student performance in real time, adjust feedback and offer personalised learning pathways based on individual learning trajectories. ITS is reported to have an effect size of 0.48.

AI can also improve teaching through automated feedback, for instance. Feedback has an effect size of 0.70.

These systems help identify where and why students are having difficulties, enabling instructors to have a clearer vision to intervene. For instance, programmes like Carnegie Learning and Squirrel AI use algorithms to identify reading and math gaps and subsequently design targeted, specially crafted activities to remediate the gaps. The result is a higher quality of differentiation – one rooted in the learner’s unique learning context and cognitive profile.

In higher education, similar systems are beginning to scale. Georgia State University, for example, has pioneered the use of predictive analytics to increase student retention by identifying early signs of disengagement and triggering timely academic support.

Evolution of professional development

AI is redefining the classroom. It is also reshaping the identity of teachers. Rather than acting as the sole purveyor of knowledge, educators become much more than this; they become learning architects who guide students through experiences that blend human judgment and creativity with machine intelligence and efficiency. This means repositioning the teacher as a master mentor who helps students build digital literacy and cultivate meta-cognitive skills (an effect size of 0.60).

AI can perform certain tasks – grading repetitive assignments, monitoring patterns of engagement, recommending learning materials. It cannot, however, equal the human capacity to move, to be present, to recognise affective nuance or to lead students through uncertainty and ambiguity.

AI cannot build essential human qualities like empathy, integrity and humanistic values which are crucial to becoming good humans. Only teachers can model these qualities and foster social and emotional learning. Only humans can look at a student and pick up subtle emotional and social cues and respond appropriately to motivate students to continue to learn.

As such, professional development must also evolve. Teachers need training not only in how to use AI tools but in how to embed them ethically and effectively within broader pedagogical frameworks. Organisations like UNESCO are already developing guidelines to support educators in this endeavour.

Building AI literacy

Among the most critical requirements for AI-enriched learning is AI literacy, not just for educators, but for learners as well. For learning at K-12 levels, this involves teaching basic concepts around how AI operates, its limitations and properties, as well as its overall societal impact. Just as digital literacy has become a core competency in the last two decades, AI literacy has also become part of the new educational landscape.

MIT’s RAISE (Responsible AI for Social Empowerment and Education) is teaching students how algorithms function, how bias can be embedded in training data and how to critically evaluate AI-generated content. These efforts are crucial in a world where deepfakes, misinformation, scams and fraud are increasingly prevalent.

AI literacy also entails fostering what educational philosopher John Dewey might have called reflective intelligence – the ability to not just use tools but to understand their ethical and civic implications. In this way, education can become not just a pathway to employment but also a tool to improve society.

Ethics are not an afterthought

While AI holds with it the potential for personalisation, it can deepen discrimination if not properly controlled. Algorithms are only as good as the data upon which they are trained. When datasets are biased, AI systems may re-enact stereotypes and exclude already marginalised populations.

Firstly, student populations with limited resources may not be provided with advanced AI technologies, worsening existing digital divides. Second, if these students are subject to poorly designed systems, they may be miscategorised, under-served or even excluded from enrichment opportunities.

The ethics of AI in education should not be an afterthought. They should be foundational. As with any technology, AI should be human-centred – transparent, accountable and designed with input from diverse communities.

Higher order capacities

Another profound shift brought by AI is the redefinition of educational outcomes. Rather than measuring learning solely in terms of content mastery, AI has the potential to cultivate higher- order capacities – creativity, critical thinking and collaboration – critical skills for the 21st century.

While some fear that AI will make students lazy or plagiaristic, which is a very legitimate concern, others see an opportunity to use it to enhance the learning process. Students can use these tools to brainstorm ideas, conduct research and receive real-time feedback, for example.

The same fears that educators have now with AI are, by and large, the same fears they had with the internet 30 years ago. Yet, we have learned how to put in place policies and protocols on how to use the internet appropriately for education because it is infused in virtually every aspect of life. AI and other technologies will likely follow a similar path.

Visual AI tools like DALL·E allow learners to generate art with minimal technical training, fostering new forms of creative expression. AI development is moving so fast that it can be difficult to keep up with all the changes. It is becoming a part of every aspect of life, faster than the internet did 30 years ago. We have only scratched the surface of what AI can and will do. As with other technologies, it will fundamentally reshape how we live and how we learn.

It’s about people

AI-powered learning is not a story about machines. It is about people. It is about how we use technology to foster human agency, to promote inclusion and to cultivate a more capable learning ecosystem. It will continue to reshape how knowledge is produced and consumed and it will continue to reshape teaching and learning processes.

We have to embrace new concepts while remaining committed to those core values that make education the driving engine of progress: advancing inquiry, expanding knowledge, fostering creativity and enhancing the quality of life for all.

We are not simply training the workers of today – we are nurturing the citizens, artists, scientists and leaders of tomorrow. And in doing so, we are called to ask not just what AI can do for education but what education can do for humanity.

Patrick Blessinger is president and chief scientist for the International Higher Education Teaching and Learning (HETL) Association in the United States. Abhilasha Singh is professor of organisational behaviour and human resource management in the College of Business Management at the American University in the Emirates in Dubai, United Arab Emirates. James Brown is an adjunct professor at the City University of New York, US.

This article is a commentary. Commentary articles are the opinion of the authors and do not necessarily reflect the views of University World News.