AI-Generated Complaints – a New Big Problem for the Higher Education Sector

Higher education, like other public services, is seeing a surge in complaints drafted with AI. While data from HE is scarce, indicators from other sectors show this is a serious and growing problem. Institutions need a proportionate response that protects fairness and due process while remaining manageable in practice and this piece aims to outline the problem and suggest practical steps.

The nature of the challenge

Most so‑called “AI‑generated” complaints are in fact AI‑assisted. AI tools help collate facts, map timelines and frame issues against legal or regulatory criteria, influencing both wording and structure.

This is happening widely. Research published by the Legal Ombudsman in October 2026 found AI indicators in 51% of a sample of complaint files, and over half of surveyed complainants reported using an AI tool. Guidance on declarations relating to AI use from the Planning Inspectorate illustrates how far-reaching the issue has become.

Evidence within HE is limited. The Office of the Independent Adjudicator (OIA) has published AI casework focused on complaints arising from academic misconduct rather than AI‑drafted complaints. Its approach mirrors other misconduct processes, placing emphasis on awareness of acceptable AI use.

Where difficulties can arise

Accuracy is the first risk. Generative AI can invent facts, authorities, quotations and policy wording, creating plausible but inaccurate claims that can be time consuming to investigate.

Authenticity is another concern. Templated language can displace the complainant’s own account and. repeated prompting may create inconsistencies Institutions may receive polished submissions that the complainant neither fully understands nor entirely owns, making resolution more difficult.

AI changes pace and volume of complaints. It lowers the effort required to submit and escalate concerns, improving accessibility for those facing language, disability or confidence barriers. However it can also amplify unreasonable behaviour and place pressure on staff who receive lengthy responses generated in minutes.

Verifiability presents further challenges. AI can fabricate or alter text, images and audio while summaries may omit important context. Detection tools remain unreliable and may create fairness concerns, particularly for multilingual, disabled or neurodivergent users.

Privacy is also an issue. Complainants may input sensitive personal information into public AI tools tools with unclear retention policies while institutional use of AI for triage or summarising material can create risks relating to personal data, safeguarding and accountability.

What not to do

While it is tempting to consider adopting a policy of considering any complaint which has involved assistance from AI as invalid, this is not recommended. Institutions should not designate AI-Assisted complaints as inherently less credible. Many complainants reasonably use AI to articulate legitimate concerns and what appears to be AI‑generated may in fact be well‑written or professionally supported.

The other path to avoid is fighting fire with fire. Institutions should resist the temptation to respond to AI-generated complaints with AI-generated decisions. Lengthy automated submissions are unlikely to be resolved by equally lengthy automated responses. Human judgement remains essential.

The goal is not to police AI use but to keep complaints accessible, evidence trustworthy and decisions fair, explainable and sustainable.

A proportionate approach

A blanket ban is unlikely to work and may indeed be discriminatory. An AI-neutral approach permits assistance while keeping the complainant responsible for facts, evidence and the remedy sought, focusing institutions on substance rather than writing style or length.

Institutions should require complaint submissions to be more structured. Template forms should ask separately

What happened?

When did it occur?

Who was involved?

What evidence exists?

What was the impact?

What remedy is sought?

Institutions should also consider sending a summarised and numbered list of these issues for confirmation by the complainant. This can reduce ambiguity, minimise overlap, limit scope creep and make case management more efficient.

Verification of claims or evidence should depend on consequence, not suspicion of AI use. Fact checking should be pursued thoroughly where the issues are material particularly where they could affect disciplinary, safeguarding or employment issues. AI summaries should be navigation aids, not substitutes for evidence.

For repetitive correspondence, which does tend to come with the territory here, institutions need a disciplined case management approach to ensure they answer each substantive point once and distinguish genuinely new evidence from reworded allegations. Existing policies in relation to unreasonable behaviour should be applied to conduct and impact, not to AI use.

Where institutions use AI themselves, controls should be clear and robust. AI may assist with classification or summaries, but final decisions must be human, with clear ownership, privacy and equality assessments and training.

Suggested actions for institutions

1. Clarify the complaints policy, adopt an AI‑neutral stance that permits assistance, requires accuracy and commits to judging on the merits.
2. Develop a template (for example the Parliamentary and Health Service Ombudsman’s) that sets out helpful advice and prompts on chronology, allegations, evidence, impact and desired outcomes.
3. Add an early step of sending a concise, numbered issues list for complainant confirmation to reduce ambiguity and scope creep.
4. Adopt a consistent protocol for duplicate, repetitive and rapidly escalating correspondence.
5. Strengthen privacy and accessibility guidance, warning against entering identifiable or sensitive data into public tools and suggesting safer prompts.
6. Govern any institutional casework AI with accountable ownership, assessments, training and meaningful human oversight.

If you or your institution is looking for support or advice on the approach to take in relation to complaints procedures and related AI issues then please do get in touch with our education team.

This content is provided for general informational purposes only and does not constitute legal advice. It is not intended to address the circumstances of any individual or entity, nor should it be relied upon as a substitute for specific advice from a qualified solicitor. The information reflects the legal position as at the date specified and may be subject to change. If you require advice on a specific matter, please contact us directly.