Faced with rising costs and shifting student demands, universities are embracing AI and digital innovation to transform learning, operations and funding in an evolving higher education landscape
In response to rising costs, declining public funding and shifting student expectations post-Covid, higher education institutions are increasingly adopting AI and technology-driven learning models while exploring alternative funding strategies. This article explores these evolving dynamics and highlights examples of how higher education institutions have adapted.
Traditional higher education models
Traditionally, higher education institutions have functioned within a predominantly campus-based framework, characterised by face-to-face instruction, print-based resources and structured curricula delivered within fixed academic calendars. Teaching and learning were centred on in-person lectures, seminars and tutorials, supported by access to physical libraries and textbooks. The pedagogical approach emphasised direct engagement between faculty and students, fostering academic discourse within classroom settings and through formalised institutional structures.
This model positioned the university as both a site of knowledge transmission and a social space, with education largely accessible only to those able to be physically present on campus. Technological integration was minimal and academic content was primarily disseminated through traditional means.
Rising costs
Over the past decade, government expenditure on education as a percentage of GDP against the demand of higher education. This downward trend has compelled higher education institutions to seek alternative sources of funding beyond the public sector, leading to a notable shift from public to private financing models.
Key private funding sources include tuition and student fees, with some institutions introducing tuition fees where education was previously free and others increasing existing fees to compensate for reduced public support. Philanthropic contributions – from alumni, charitable foundations and private donors – have become increasingly important, particularly for research-orientated universities. Corporate partnerships and sponsorships also provide revenue through the commercialisation of services, including consulting, products and patented innovations.
Furthermore, in response to public funding cuts, many institutions have turned to international markets for financial support. Under policies promoting internationalisation, universities have increased their efforts in recruiting foreign students, who are often charged significantly higher tuition fees than domestic students, thereby generating additional income.
Apart from external funding, higher education institutions have begun to reflect on how they can operate more efficiently while adapting to the evolving needs and expectations of students.
The Covid-19 pandemic significantly reshaped the needs and expectations of higher education students. The rapid shift to online learning highlighted the demand for greater flexibility, accessibility and digital competence in educational delivery. Students increasingly value blended learning models, combining in-person and virtual components to accommodate diverse learning styles and life circumstances.
Moreover, there is a growing expectation for institutions to provide personalised learning pathways and technology-enhanced experiences.
Leveraging AI and technology
At the opening ceremony of the 2025 International Day of Education, Mario Delgado, Mexico’蝉 secretary of public education, addressed the value of AI in higher education. “This new tool [AI] offers possibilities for optimising teachers' time, designing better pedagogical strategies and focusing on the human and socioemotional factors,” Delgado said.
The integration of AI and emerging technologies has the potential to profoundly reshape the higher education landscape, transforming pedagogical practices, institutional management and research capabilities.
These technologies have been increasingly applied in a number of areas:
- Personalised and adaptive learning
AI enables personalised instruction by analysing student performance data and dynamically adjusting content delivery. Such systems – including intelligent tutoring systems – foster improved engagement and outcomes by addressing diverse learning paces, styles and competencies.?
- Digital learning environments
Tools such as learning management systems, video conferencing platforms and immersive technologies like virtual augmented reality enrich student experiences and extend learning beyond traditional classroom settings.
- Data-driven institutional decision making
Learning analytics and predictive modelling allows institutions to monitor student engagement and performance. Analysis of large-scale institutional data supports strategic planning in areas such as curriculum development, resource allocation and student support services.
- Administrative efficiency and student services
Chatbots and virtual assistants streamline administrative workflows by automating tasks related to admissions, course registration and student inquiries. This enhances operational efficiency while improving responsiveness and user experience for students.?
- Enhancing research capabilities
In the domain of academic research, the ability to analyse complex datasets, accelerate discovery processes and facilitate comprehensive literature reviews through natural language processing are particularly valuable in data-intensive disciplines and interdisciplinary research.
Case studies of successful implementation
While the benefits of AI and technology are substantial, their implementation raises important concerns regarding data privacy, algorithmic bias, digital equity and faculty readiness. The implementation of AI is rarely straightforward and requires careful consideration.
The following institutions exemplify the successful implementation of AI and technology to advance instructional practices, enhance student learning experiences and optimise administrative operations within higher education institutions:
Georgia State University implemented an AI-driven chatbot named Pounce to provide personalised support to students. In 2016, during the first summer of implementation, Pounce delivered more than 200,000 answers to questions asked by incoming students, and the university by 22 per cent.
This translated into an additional 324 students sitting in their seats for the first day of classes at Georgia State University rather than missing out on the college experience.
At the University of Oxford’蝉 , researchers are utilising AI-powered databases to expedite the discovery of drugs to treat Alzheimer’蝉 disease. By employing knowledge graphs – a technology that connects diverse data sources – the institute has significantly reduced the time required to evaluate gene properties, accelerating the identification of potential drug targets.
This process helped the institute’蝉 biologists reduce the time it took to evaluate 54 genes from a few weeks to a few days. With a subset of the genes it has prioritised, the team plans to perform more experimental validation.
In the face of rapidly evolving student expectations and intensified global competition, higher education institutions are compelled to adapt to remain relevant and competitive.
Increasingly, students today demand flexible, personalised and technology-enhanced learning experiences that reflect the digital environments they navigate daily. Compounding this is the widespread availability and rapid advancement of AI and digital technologies, which have already been embraced across many industries – from healthcare and finance to manufacturing and creative sectors.
As digital transformation becomes the norm rather than an exception, higher education can no longer operate in isolation. Institutions must leverage AI and emerging technologies, not only to enrich teaching and learning quality but also to modernise operations, enhance student services and position themselves as future-ready in a globalised education marketplace.
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