Higher education needs structural changes to flourish in the AI era
Universities need to adapt if they want to thrive in the fast-paced digital world, according to Melissa Loble, chief academic officer at educational technology company Instructure. “Higher education continues to respond to the rise of AI, but has yet to make the structural changes required to fully harness its potential,” she says.
Digital tools, from virtual learning environments to AI, have disrupted higher education. At the same time, digital transformation in the workforce has altered the skills that employers expect graduates to possess and has instilled a desire for lifelong learning.
Institutions that adopt processes to cultivate digital maturity and meet student needs will flourish, Loble says. These structural changes affect all tiers of higher education, including assessment, data management and the curriculum, through offerings like microcredentials.
“The year 2026 must be the year of structural reconfiguration in which educators redesign teaching and assessment, unite their fragmented technological systems, and respond to the needs of the labour market and prospective students,” she says.
A new path for assessment and academic integrity
The use of AI is a controversial issue in academia. A recent study by plagiarism checker Turnitin found that 95 per cent of academic administrators, educators and students surveyed believed that AI was being misused in higher education.
Although more than three-quarters of participants thought it could have a positive effect on education, a similar percentage said they were overwhelmed by the volume and availability of these tools. “AI keeps advancing, and students learn to use it faster than many of their teachers,” Loble says.
A common concern around AI in higher education is plagiarism and academic integrity. However, Loble warns that being in “police mode” would not address the underlying problem. “There are so many ways in which students can access AI to cheat,” she says. “The solution is not only in the technology, but in the pedagogy.”
It can be more beneficial for educators to design assessments that illuminate the learning process rather than just the final output. This approach can help students see the purpose of their learning and assessment. Additionally, Loble recommends that curricula should include modules on the ethical use of AI.
These are skills that the graduates of the future will need. The rapid march of technology is continuing in the labour market, and university leavers must meet these challenges – both in terms of technological proficiency and ethical use.
Responding to student needs
Shifting skills requirements, combined with the digital revolution, are changing the demographics of higher education and the demand for courses and degrees.
Universities in the United States, for example, are concerned about an upcoming enrolment cliff, with fewer first-year students interested in college degrees. Loble says that the real issue was an “enrolment shift”. “There is a change in who studies, where they do it, and what they are studying,” she says.
She points to Spain’s vocational education sector, which is experiencing unprecedented growth, with more than 1.2 million students enrolled. The sector’s enrolment numbers have increased by a third in the last six years.
“Universities cannot compete for the same students as before,” Loble says. “The key in 2026 is how to open new, more flexible learning routes that accompany people throughout their entire working life and also fit into multigenerational classrooms.”
According to Instructure’s The State of Higher Education 2025 report, more than half of the students surveyed (54 per cent) said they would choose more flexible modes of studying in the future. These options included blended learning, microcredentials and short courses.
Microcredentials are an important way for universities to diversify their offerings while attracting professional students. These shorter, flexible modules can be aligned with employer and employees’ needs to attract learners.
“In the era of lifelong learning, the big global challenge for microcredentials to fulfil their promise is not just multiplying the offering but also making sure they truly support the progression and mobility of students and employees,” Loble says. “Universities have the responsibility to show that the teaching they provide and the credentials they award are credible and meaningful for the labour market.”
An integrated ecosystem
The digital transformation extends beyond the student into the architecture that underpins universities’ operations. “Many universities continue to work with self-managed platforms and learning systems that were originally designed to handle simple, linear processes,” Loble says.
However, these legacy systems can’t keep up with the pace of technological development, and higher education institutions are forced to patch their systems with technological fixes and by adding superficial AI functions.
Machine-learning and agentic AI have the potential to streamline university operations, integrate learning systems and drive smart automation. To harness these opportunities, universities need an underlying AI-friendly architecture, Loble says. This includes flexible and transparent interfaces and unified access to data.
Higher education is at a turning point, Loble says. If institutions want to remain relevant, they need to focus on raising course quality, redefining assessment and building coordinated technological ecosystems.
Find out more about Instructure.
