Office for Students Urges AI-Free Assessment to Safeguard Degrees

England’s Office for Students said on November 11, 2026, that universities must ensure assessments measure what students know and can do, often by using secure, AI-free formats. It warned that many unsupervised assignments can be completed to a high standard with AI while requiring limited engagement from students.

Alongside a joint research report with Advance HE, the OfS published guidance for universities and colleges applying its existing quality conditions to AI rather than creating a new AI-specific registration condition. Those conditions include requirements for up-to-date courses and relevant skills, sufficient student support, and credible awards based on valid, reliable assessment. Institutions that fall short can face specific registration conditions, monetary penalties or suspension of access to student support funding or OfS grant funding.

Josh Fleming, the OfS’s director of strategy and delivery, described AI as both an opportunity and a “generational risk to the system as it stands, threatening to undermine students’ learning and institutions’ ability to assess them.” He called for far greater use of AI-free assessment.

Evidence From Students and Staff

The full report draws on research conducted between June and September 2026 with 244 higher education staff and 91 students or student representatives from at least 127 institutions. Evidence came from live events, 64 responses to online prompts and 22 interviews. Participants were self-selecting and may not represent wider student and staff populations.

Students told researchers that peers sometimes completed assessments with large language models in just a few minutes and received grades similar to those earned independently. Some said those peers could not recall basic details of their submissions. Staff reported high volumes of submissions sharing the same style and references, while remotely submitted essays were identified as especially vulnerable.

The report concludes that human reviewers cannot reliably identify AI-generated text and that detection tools do not consistently identify AI use. Consequently, policy declarations and retrospective misconduct proceedings cannot substitute for structurally sound assessment design. Detector outputs should be at most one piece of evidence in a fair process, and suspicion without strong evidence should not justify a lower mark.

Secure Assessment in Practice

The guidance defines secure assessment as a format designed to prevent AI use, including in-person exams, presentations, oral examinations, performances and practical or applied tasks. Where AI is permitted, students must still demonstrate the intended learning outcomes, which can include effective AI use. An assessment should be replaced if it can be completed with AI without the knowledge or skills it is meant to test.

One case study illustrates the design choice. The University of Bath adopted a two-lane model in September 2026 after finding that the middle category in its previous traffic-light system, which allowed specified AI uses, could not be policed reliably and equitably. Closed-lane assessments prevent access to AI; open-lane assessments permit it and must be designed on that assumption. Both lanes still need to measure the intended learning outcomes.

Secure assessment also has costs. Participants cited the resources required for exams and oral tests, concerns that closed-book exams may not reflect professional practice, and the possibility that some formats may put disabled students at a disadvantage. Institutions retain a legal duty not to discriminate and may need reasonable adjustments, including changes to assessment methods, while ensuring those adjustments do not create an unfair advantage.

AI Skills and Accessibility

The report does not recommend removing AI from education. Students use it to explain difficult concepts, summarise documents, generate practice questions and revise, with potential benefits for disabled and neurodivergent students and those whose first language is not English. It distinguishes those activities from cognitive offloading, where AI replaces reading, research, problem-solving or other demanding work and can bypass the productive struggle needed to develop knowledge and skills.

Many students see AI literacy as important for employment and want more subject-specific training, yet provision is uneven and staff training is often voluntary with low take-up. The OfS’s guidance calls for clear rules on permitted AI use, oversight of AI-generated teaching materials and feedback, and steps to mitigate disparities created by unequal access to paid tools and training. Relatively few participating institutions had embedded institution-wide AI strategies.

The OfS plans further structured research into the scale and nature of the change, while Advance HE will launch an AI-focused Change Academy for member institutions early in 2027. For institutions, the immediate compliance question is whether a qualification still demonstrates what a student knows and can do when AI assistance may be undetectable. The same regulatory response also demands relevant AI skills and accessible design, making assessment security one part of protecting degree value alongside teaching and student support.