By Stuart Kerr, Technology Correspondent, LiveAIWire
The university degree reimagined is not a slogan; it is what higher education is being forced into by a genuine assessment validity crisis. In December 2025, the Association of Chartered Certified Accountants announced that routine online exams would cease from March 2026. The CEO’s explanation was unambiguous: cheating technology had outpaced existing safeguards, undermining academic integrity within credentialing pipelines. What was being described is not a cheating problem. It is an assessment validity crisis: when the tools available to students can produce work that passes the tests institutions use to certify competence, the tests no longer certify what they are designed to measure.
92 percent of UK undergraduates reported using generative AI tools for assessments in 2025, up from 66 percent in 2024, according to the Higher Education Policy Institute and Kortext survey. In the United States, 88 percent of college students reported using AI for assessments in some form. AI-related misconduct cases rose from 1.6 per 1,000 students in 2022 to 7.5 per 1,000 in 2026, a 400 percent increase over three academic years. These numbers do not represent a moral failure by students. They represent a rational response to the availability of a tool that makes the existing form of assessment trivially easy to game.
What AI Can Now Do in Academic Domains
The university degree reimagined begins with capability: the scope of AI performance in academic tasks has expanded substantially faster than higher education’s assessment frameworks have adapted. GPT-4 passed the Uniform Bar Examination with a score in the top 10 percent of human test-takers in 2023. Later models have extended that performance across professional certification exams in medicine, accounting, and finance. AI systems can now complete approximately 94 percent of theoretical computer science tasks, according to capability assessments conducted by AI labs and independent researchers. Multiple independent studies have found that AI-generated essays are rated as highly by instructors as human-written equivalents when the rater does not know which is which.
The implications for the credentialing function of higher education are serious. A university degree in law, accountancy, business, or the social sciences has historically certified that the graduate can perform specific analytical and written tasks at a defined standard. If AI can perform those tasks at the same standard, the degree no longer certifies what it says it certifies, and employers who hire graduates based on their degree credentials are making an increasingly uncertain inference about the actual capabilities those credentials attest to.
The University Degree Reimagined Through Assessment Reform
The institutions generating the most credible responses to AI’s challenge to higher education are those that have started from the question of what they are actually trying to certify, rather than from the question of how to stop students using AI. The answer points toward assessment formats that AI cannot currently replicate: oral examination in which the student must reason in real time in response to probing questions from an examiner who can follow unexpected threads; project-based assessment evaluated against criteria that require contextual knowledge specific to the course; portfolio assessment that tracks development of thinking over time rather than measuring a point-in-time product; and clinical or practical placement assessment that observes performance in real-world application.
In the UK, 59 percent of undergraduates said the way they are assessed has changed significantly because of generative AI. The proportion of students saying university staff are well-equipped to work with AI doubled in twelve months, from 18 percent in 2024 to 42 percent in 2025. That is genuine progress. It is also evidence that 58 percent of students still do not believe their institutions are ready. The institutions that are moving fastest on assessment reform share a characteristic: they have made the redesign a strategic priority rather than a departmental problem, investing in professional development for assessment design and creating shared frameworks for AI-appropriate assessment across programmes.
The Credential Inflation Question
For the university degree reimagined, the widening availability of AI tools for academic work creates a credential inflation dynamic analogous to what happens to any certificate when it becomes easier to obtain. If the effort required to pass a degree falls because AI can do the work, and if institutions do not redesign their programmes to maintain the genuine challenge of learning, the degree’s signal value as an indicator of capability decreases.
The PwC 2026 AI Jobs Barometer found that AI-exposed entry-level roles are seven times more likely to demand traditionally senior skills like leadership and strategic thinking compared to the least exposed roles. That finding has a corollary for the university degree reimagined: the degree programmes most directly threatened by AI’s displacement of assessment tasks are those whose credentials most closely map to the tasks AI handles best. Programmes that certify the ability to exercise professional judgement, navigate genuine ambiguity, and synthesise knowledge across domains are most capable of maintaining their credential value in an AI environment, a distinction that connects to LiveAIWire’s coverage of what the IMF’s AI exposure figures actually mean for workers.
The Return on Investment Question
The economic case behind the university degree reimagined is being scrutinised more intensely in the AI era than at any previous point. The AI skills wage premium, 56 percent higher wages for roles requiring AI skills, has emerged faster through employer-delivered training and self-directed learning than through formal university programmes. Coding bootcamps, professional certification programmes, and online learning platforms have demonstrated that specific technical capabilities can be acquired in months rather than years, at costs a fraction of a university education.
The degrees that will maintain their return on investment are those that genuinely develop the capabilities that neither AI nor cheaper alternatives can replicate: deep disciplinary reasoning, professional judgement, ethical practice, and the interpersonal capabilities required to lead complex organisations. The degrees that will struggle to justify their cost are those that primarily certify task performance that AI has made automated and therefore less scarce, a pressure that echoes LiveAIWire’s broader coverage of the AI automation divide.
What Employers Are Starting to Do
The employer response to credential uncertainty is beginning to shift the hiring landscape in ways that reinforce the pressure driving the university degree reimagined. Skills-based hiring, evaluating candidates on demonstrated capability rather than degree credentials, has been growing as a trend for several years, and AI’s disruption of assessment validity is accelerating it. McKinsey’s research on AI and employment found that employers in AI-exposed sectors are increasingly requiring portfolio demonstrations, practical assessments, and case studies rather than relying primarily on degree class as a signal of capability. IBM, Google, and Apple have notably removed degree requirements for specific roles.
The Global Dimension and What It Means for Access
The AI challenge to the university degree reimagined is not uniformly distributed globally, and the pace of reform varies sharply by resource level. Elite universities in high-income countries have the resources to redesign assessment, invest in oral examination infrastructure, and develop AI literacy programmes. Universities in middle-income and lower-income countries, which educate the majority of the world’s university students, face the same challenge without the resources to respond at equivalent pace or scale. The result is a risk that AI disrupts credential value most severely in the institutions least equipped to respond.
The counter-argument is that AI tools are also equalising access to educational quality in ways that benefit students in lower-resourced institutions. An AI tutoring system available on a smartphone can provide personalised learning support at a level that only the best-resourced institutions could previously offer through human tutoring, a possibility LiveAIWire has explored in our coverage of why students are quietly replacing search with generative AI. Whether AI in higher education net-widens or net-narrows educational equity is an empirical question that will be answered differently in different institutional contexts and national systems over the next decade.
About the Author
Stuart Kerr is Technology Correspondent at LiveAIWire, covering artificial intelligence, cybersecurity, and the social impact of emerging technology. He publishes daily at LiveAIWire.com.