University AI Policies for Academic Writing: What You Need to Know

University AI policies have changed rapidly since ChatGPT was released in late 2022. What began as a largely reactive landscape of blanket bans has evolved into a more nuanced environment where most institutions permit some AI use with conditions and disclosure requirements. Understanding exactly what is and is not permitted at your institution is a professional skill, not just an ethical nicety.

The policy landscape: 2023 to 2025

The research by Cotton, Cotton & Shipway (2024) in Innovations in Education and Teaching International captured the early phase of the policy response: widespread prohibition, significant uncertainty among students about what was permitted, and detection-based enforcement approaches that the research found to be unreliable. Lodge et al. (2023) in Educational Philosophy and Theory argued that blanket bans were unsustainable given AI's trajectory, and predicted a shift toward policies that distinguish between AI use types rather than prohibit AI wholesale.

By 2025, this shift has largely occurred. The dominant policy framework at major UK and US institutions distinguishes between:

1. Prohibited use: AI generates the intellectual content of assessed work that the student presents as their own
2. Regulated use: AI is used in specified ways with required disclosure
3. Permitted use: AI use that does not affect the authorship of the intellectual content

The spectrum of current institutional approaches

Restrictive policies

Some institutions, particularly for specific assessment types, maintain close to a blanket ban on AI use in assessed work. This is most common for:

• Essay-based assessments intended to evaluate analytical thinking
• Closed-book examinations
• Assessments described as "individual unaided" or similar
• First-year assessments intended to establish baseline academic writing skills

Under restrictive policies, using AI in any substantial way — even for brainstorming or feedback — may be considered a violation. The reasoning is that these assessments are specifically designed to evaluate skills that students need to develop through practice, and any AI assistance compromises the validity of the assessment.

Conditional permission frameworks

Most major UK and US research universities have adopted conditional permission frameworks that permit some AI use with required disclosure. These policies typically specify:

• What is permitted: brainstorming, literature searching with AI tools, grammar checking, getting feedback on drafts, generating code (in computing courses)
• What is restricted: generating essay content, generating research analysis, using AI in closed-book conditions, using AI to produce substantial portions of assessed work
• Disclosure requirements: a declaration within the submission describing how AI was used, referencing the AI tools used in the reference list
• Disciplinary variation: many frameworks give individual faculties or departments discretion to impose stricter requirements

Active integration approaches

A small but growing number of institutions and modules actively integrate AI use into assessment design — setting tasks that explicitly involve using AI tools, evaluating students on how critically they engage with AI outputs, or designing assessments that are resilient to AI (oral examinations, in-class work, iterative portfolio submissions).

Bozkurt et al. (2023) in the Asian Journal of Distance Education argued that this approach — designing for AI rather than against it — is the most educationally coherent long-term response, because it assesses the skills that matter in an AI-mediated world rather than attempting to artificially recreate pre-AI conditions.

How to find out what your institution permits

Step 1: Check the module handbook. Module-specific guidance takes precedence over general institutional policy for that assessment. If the module handbook specifies restrictions on AI, those restrictions apply regardless of what the general policy permits.

Step 2: Check your institution's academic integrity policy. Most universities have a published AI policy as part of their academic integrity framework. Search your institution's website for "AI policy," "artificial intelligence assessment," or "ChatGPT guidance."

Step 3: Check the assessment brief. Many institutions now include an explicit AI use statement in assessment briefs, specifying what is and is not permitted for that specific task.

Step 4: Ask your tutor if unclear. If the policy does not clearly address your specific intended use, ask the module tutor before using AI — not after. "I wasn't sure if this was permitted" is not a defence after submission.

The disclosure question

Many students who use AI do not disclose it — either because they are uncertain whether it was permitted, because the use feels minor, or because they assume it will not be detected. This is a significant risk:

Declaration requirements are binding even for minor use. If your institution requires disclosure and you used AI in a way that falls within the disclosure requirement, failing to declare it is itself a violation.

Detection risk is increasing. AI detection tools are unreliable today (Cotton et al., 2024), but assessment design is evolving: oral examinations, in-class writing, iterative submissions, and portfolio approaches are harder to complete with AI assistance. Assessments will increasingly be designed to verify that the submitted work reflects actual student knowledge and capability.

The safer default is transparency. If you are uncertain whether your AI use requires disclosure, declare it. A brief note in the submission ("I used [tool] to [purpose]") protects you against the more serious charge of undisclosed use.

Skills that are robust to AI policy changes

Regardless of how AI policies evolve, some academic skills remain central to academic success:

• The ability to construct and defend an argument
• The ability to read critically and synthesise sources
• The ability to identify the limits of evidence
• The ability to write clearly in your disciplinary register

These skills are assessed in ways that AI cannot fully replicate (oral examinations, in-person writing, viva voce), and they are the skills that graduate employers and higher-level academic programmes are looking for. Developing them through genuine practice — even when AI shortcuts are available — is the most durable investment you can make in your academic career.

The Academic Writing Fundamentals course builds the analytical essay-writing skills that are both assessed and needed. See Using AI for Academic Writing Ethically for detailed guidance on ethical AI use in writing practice.