Artificial Intelligence (AI) has quickly moved from science fiction to everyday reality, transforming how industries work - and higher education is very much part of that change. Universities and colleges around the world are now bringing AI into their classrooms, research, and daily administration.

A UNESCO report of 2023 indicated that by the middle of the year, almost 89% of colleges and universities were already engaged in some sort of AI project. The World Economic Forum even goes as far as estimating that AI's contribution to the global economy in 2030 would be roughly $15.7 trillion, and education would be the area that has a big share in it.
In the US, the market for AI in education was evaluated at $4 billion in 2022, and it is projected to grow to $20 billion by 2027 (HolonIQ).

The applications of AI in education are very significant - personalized learning, management that run smoothly, and research that flourish but at the same time, they bring up the need for serious discussions about ethics, fairness, and the overall quality of education. The article presents both sides of the debate: the ways AI are proving helpful to higher education and the areas that still pose difficulties.

The capability of AI to personalize learning is one of its key features. AI-powered platforms can monitor a learner's progress in real-time and change the lessons accordingly to fit his/her learning speed rather than applying a general approach like before.

Research at Arizona State University (ASU) with 12,000 students found out that the use of AI-assisted adaptive tutoring raised the passing rates by 11% and brought down the number of students leaving the courses by 14% (ASU EdPlus, 2022). The worldwide demand for adaptive learning tools has increased by twofold from $1.3 billion in 2020 to $3.1 billion in 2023 (MarketsandMarkets).

AI has made it possible to narrow the educational gap in third-world countries. The NPTEL (National Programme on Technology Enhanced Learning) project in India, for example, recommends courses to over 1.5 million students each year by using AI. A 2024 study revealed that the use of personal AI tutoring led to an increase in the course completion rates in online learning from 5% to 18% for students coming from disadvantaged backgrounds.

Universities spend a huge amount of time on administration - from handling student queries to processing admissions. AI is now helping reduce that load. An AI chatbot at Georgia State University handles more than 200,000 student inquiries every year. The implementation of this straightforward innovation brought about a 22% reduction in summer "melt" (students who do not enroll after being accepted) and consequently saved the university almost $1 million on a yearly basis as per the sources from Educause Review, 2023.

Artificial Intelligence is also being applied to forecast the possibility of a student dropping out. The University of Maryland came up with a system that was able to identify at-risk students with an accuracy of 85% and this eventually led to a retention increase of 5% (WEF, 2024). In the meantime, the University of Michigan is applying machine learning to evaluate over 70,000 applications every year, thus speeding up processing time by 40%. As per the projections from McKinsey (2023), the adoption of AI-based automation in the higher education sector could eventually result in a total of $100 billion savings for universities across the globe by the year 2030.

AI has become a powerful research partner in universities. Tools like IBM Watson and Google Scholar’s AI engine can scan thousands of academic papers in seconds, helping researchers find patterns or gaps in existing knowledge. A Nature study (2024) showed that AI-assisted literature reviews helped PhD students cut research time by 60%. In the sciences, AI is now being used to simulate lab experiments - for example, MIT’s AI drug discovery system identified new compounds 50 times faster than traditional methods.

Collaborative programs such as the EU’s Horizon Europe initiative have also shown results: AI-supported research teams produced 15% more publications per euro invested than those using traditional methods (European Commission, 2025).
AI is also improving access for students with disabilities or limited resources. Microsoft’s Immersive Reader, integrated into systems like Canvas, offers real-time translation, text-to-speech, and visual support - helping the 15% of U.S. college students with disabilities (NCES, 2023).

In Bangladesh, the 10 Minute School app has brought AI-powered micro-lessons to over 500,000 tertiary-level learners, many in areas with limited internet access. Similarly, the Open University UK found that using voice-assisted AI increased participation among visually impaired students by 28%.

AI systems depend heavily on student data - which raises legitimate privacy and security worries. A 2024 Ponemon Institute study revealed that 62% of students were concerned about how their data might be used. While Europe’s GDPR sets strong privacy standards, less than half of EU universities are fully compliant. In 2023, a major university data breach exposed 1.2 million student records, showing how vulnerable educational data can be.

AI tools are only as fair as the data they’re trained on. Unfortunately, biases in algorithms can create unfair outcomes. A ProPublica (2022) investigation found that some AI prediction systems labeled minority students as “high risk” more often than others, increasing dropout rates for those groups. A Stanford (2023) study found that AI systems tend to undervalue women and minority students in STEM courses, further widening the gender gap.

Infrastructure is another issue. Only 40% of universities in low-income countries have stable internet for AI use, compared to 95% in high-income nations (World Bank, 2024). In Bangladesh, with tertiary enrollment still around 20% (UNESCO, 2023), inadequate connectivity limits how effectively AI can be used.

An excessive dependence on AI will have a negative impact on true learning. An OECD (2024) study determined that students using AI for essay writing got 15% lower scores in their analytical skills. On the other hand, plagiarism detection software such as Turnitin reported detecting AI-produced texts in 10% of student papers in 2023, which was an increase from just 1% two years ago. 

The opinions of the teachers varied greatly. As per a Times Higher Education (2024) poll, 58% of the professors are concerned that AI might take over some of their roles. Even though AI systems for grading are quicker, they continue to face difficulties with assignments that require subjective judgment, particularly in the fields of arts and humanities, where the error rates may be as high as 20% (Inside Higher Ed, 2023).

Setting up AI infrastructure is expensive. A mid-sized university might spend $500,000 to $2 million just to launch an AI-enabled learning system (Gartner, 2024). Faculty training adds another layer - a UK study found upskilling teachers for AI integration costs around £5,000 per instructor. According to the Asian Development Bank (2023), only one in four institutions in Asia currently have the budget for full AI implementation.

Some success stories stand out. Carnegie Mellon University (USA) improved computer science grades by 12% using AI tutors. Strathmore University (Kenya) saw graduation rates rise by 9% with AI-based mentoring.

But not every experiment has gone smoothly. In India, AI-powered online exam monitoring during COVID wrongly flagged 15% of students for cheating because of poor lighting or internet issues — even leading to legal disputes. Such examples remind us of that technology alone isn’t enough, context matters. Similarly, at Yonsei University in South Korea, around 600 students in a “Natural Language Processing and ChatGPT” course was suspected of using AI tools such as ChatGPT to cheat during their online midterm, despite strict monitoring.

A student poll showed 190 out of 353 admitted to using unfair means, suggesting over half the class was involved. The case highlights how AI misuse is rising faster than institutional readiness — with 91.7% of Korean university students using AI for coursework, yet 71.1% of universities lacking clear policies (Korea JoongAng Daily, Nov 9, 2025).

AI has the power to transform tertiary education - from boosting learning outcomes by nearly 18%, to saving billions in costs, and making education more accessible to millions. But it also brings serious challenges related to bias, privacy, and affordability. To move forward in a responsible way, universities must first establish ethical guidelines and then invest in teacher training and infrastructure. The IEEE's AI Ethics Guidelines (which are now followed by 40% of the best universities) highlight the importance of transparency, accountability, and fairness among the main principles.

The role of AI in education should be to support human teachers rather than to supplant them. By taking precautions and implementing a well-balanced integration, the higher education system can use the potential of AI to make students ready for the future - the future in which 85 million jobs will be shifted or transformed by 2030 (WEF). The goal should not be just smarter technology, but smarter, more inclusive learning for everyone.

Writers: Dr. Carmen Z. Lamagna, Member, Board of Trustees & Former Vice Chancellor, AIUB; Prof. Dr. Dip Nandi, Associate Dean, Faculty of Science and Technology, AIUB.