UK: Generative AI in Employment Disputes – Managing Workplace Complaints, Tribunal Proceedings and Legal Risks

Generative artificial intelligence (AI) is changing how employees raise workplace complaints, exercise their data protection rights and pursue employment disputes. While AI can help individuals organise information, prepare correspondence and formulate legal arguments, it can also produce lengthy, repetitive or inaccurate material that creates additional challenges for employers.

HR teams, in-house legal departments and employment advisers are increasingly encountering detailed grievances, whistleblowing complaints, data subject access requests (DSARs) and tribunal submissions prepared with AI assistance.

The central issue for employers is not whether AI has been used, but whether the information presented is relevant, accurate and legally significant. Existing employment law obligations continue to apply, and employers must respond fairly, proportionately and consistently.

Recent judicial decisions and Employment Tribunal guidance reinforce the importance of maintaining human oversight, verifying legal submissions and ensuring that witness evidence reflects an individual’s genuine recollection.

1. AI-Assisted Workplace Grievances

Generative AI has made it easier for employees to produce sophisticated grievance documents containing extensive factual allegations, statutory references and requests for formal investigation.

Although these documents may appear legally complex, their presentation does not necessarily reflect the substance or seriousness of the underlying concerns.

Employers should continue to assess grievances in accordance with their internal procedures and the ACAS Code of Practice on Disciplinary and Grievance Procedures.

The immediate priority should be identifying the issues that genuinely require investigation.

Structured grievance forms, preliminary discussions and initial scoping meetings can help establish the nature of the complaint, the key events involved and the outcome sought by the employee.

Employers should avoid challenging or dismissing a grievance simply because AI may have assisted in its preparation. Instead, they should focus on the facts, evidence and relevant employment obligations.

Practical implications: Employers should review grievance procedures to ensure they can accommodate increasingly detailed submissions without creating unnecessary administrative burdens or compromising procedural fairness.

2. Whistleblowing: Assessing Substance Rather Than Legal Labels

AI tools can assist employees in presenting workplace concerns using the language of statutory whistleblowing protections.

Complaints may contain references to protected disclosures, regulatory breaches, financial misconduct or workplace health and safety concerns, even where the legal position is uncertain.

However, describing a complaint as a protected disclosure does not automatically establish that it qualifies for protection under whistleblowing legislation.

Employers must consider the substance of the information disclosed, the relevant circumstances and whether the statutory requirements for protection are satisfied.

They should also consider whether the worker has subsequently experienced any alleged detriment connected with raising the concern.

A prompt and objective assessment is particularly important where complaints concern regulatory compliance, financial irregularities, health and safety or other matters potentially falling within whistleblowing protections.

Practical implications: HR and legal teams should have clear procedures for identifying potential protected disclosures, assessing the underlying allegations and escalating matters appropriately, regardless of whether a complaint has been prepared using AI.

3. Data Subject Access Requests: Managing Scope and Compliance

Generative AI can help individuals formulate broad and detailed DSARs covering multiple systems, extensive periods and substantial categories of personal information.

For employers, responding to these requests can involve significant document searches, internal coordination and legal review.

Nevertheless, AI-assisted DSARs must be considered under the same statutory framework as other requests.

Early engagement with the individual can help clarify the information being sought and improve the efficiency of the response.

Employers should consider:

• Involving legal or data protection advisers where requests are complex or sensitive.

• Seeking appropriate clarification about the personal information requested.

• Identifying and preserving potentially relevant records at an early stage.

• Establishing proportionate and defensible search procedures.

• Documenting the scope, methodology and rationale for searches undertaken.

• Monitoring statutory response deadlines and any applicable extensions.

Under applicable data protection rules, employers may seek clarification where appropriate, but should not assume that a broad request can simply be refused or that the individual must agree to narrow its scope.

Practical implications: Employers should establish consistent DSAR procedures covering information searches, preservation, internal responsibilities and legal review. Clear audit records can help demonstrate compliance if the response is subsequently challenged.

4. Workplace Communications: Avoiding Unnecessary Escalation

AI-generated correspondence can sometimes adopt an unnecessarily formal, adversarial or confrontational tone.

Lengthy communications containing extensive legal arguments may make it harder for employers and employees to identify the genuine disagreement and work towards a resolution.

Where appropriate, direct discussion can help clarify the individual’s concerns and establish whether the tone of the correspondence accurately reflects their position.

An illustration can be found in the Australian Fair Work Commission decision concerning De Bruyn v Sanctuary at Buderim (AB2025/973).

The Commission commented on the unhelpful nature of correspondence that appeared to have been prepared with AI assistance, highlighting how the style and volume of communications can contribute to difficulties in resolving disputes.

Although the decision is Australian and does not establish a binding precedent for UK employers, it provides a useful reminder of the importance of measured communication.

Practical implications: Employers should maintain clear, professional and proportionate correspondence. Where possible, direct engagement may help prevent an AI-assisted exchange from becoming an unnecessarily prolonged dispute.

5. Employment Tribunal Proceedings: Increasing Complexity and Procedural Challenges

AI is also influencing the preparation and presentation of Employment Tribunal proceedings.

Employers may receive increasingly lengthy pleadings, procedural applications, document requests and legal submissions, sometimes incorporating substantial volumes of statutory references and case law.

This can increase management time, legal expenditure and the administrative burden associated with disclosure and case preparation.

However, the existence of extensive AI-generated material does not mean that every argument is legally relevant or requires an equally detailed response.

Employers and their advisers should concentrate on the substantive issues, applicable procedural rules and evidence necessary to address the claim.

6. Interim Relief Applications: The Importance of Immediate Action

Interim relief is an emergency remedy available in certain categories of automatic unfair dismissal claims, particularly where an employee alleges dismissal because of a protected disclosure.

On 22 June 2026, joint Presidential Guidance concerning applications for interim relief took effect across Employment Tribunals in England, Wales and Scotland.

The Guidance addresses the management of these urgent applications and recognises the challenges presented by lengthy or unfocused supporting material, including material prepared with AI assistance.

The use of AI does not remove the obligation to provide accurate, relevant and appropriately focused submissions.

Interim relief applications can move quickly, and employers may receive only limited notice of a hearing.

Practical implications: Employers should have an immediate escalation procedure for interim relief applications, ensuring that HR, senior management and legal advisers can respond promptly.

Relevant dismissal documentation, communications and witness evidence should be identified and preserved without delay.

7. AI-Generated Legal Submissions: Accuracy, Relevance and Accountability

Courts and tribunals have become increasingly alert to the risks associated with AI-generated legal documents.

Generative AI can produce convincing legal arguments containing fabricated authorities, inaccurate quotations or incorrect statements of legal principles.

Consequently, apparent legal sophistication should not be mistaken for reliability.

The Employment Appeal Tribunal’s decision in Hancox v Sutherland and Others [2026] EAT 139 provides an important illustration.

In that case, a litigant in person submitted a 300-page skeleton argument created using ChatGPT and asked the opposing parties to identify inaccuracies.

The Employment Appeal Tribunal criticised the submission for its failure to comply with procedural requirements and its lack of appropriate verification and focus.

The judgment reinforced that litigants remain personally responsible for the accuracy, relevance and procedural compliance of documents submitted to a tribunal, regardless of whether AI was used in their preparation.

The wider principle is that AI may support the preparation of legal materials, but it cannot replace legal judgment or remove responsibility for the contents of a submission.

Practical implications: Employers and their advisers should verify AI-assisted legal research, statutory references, quotations and cited judgments against authoritative sources.

Where opposing parties rely on extensive AI-generated submissions, responses should focus on material legal and procedural points rather than attempting to address every assertion individually.

8. Witness Statements: Preserving Authenticity and Reliability

The use of AI in preparing witness evidence presents particular risks.

Witness statements must accurately reflect the witness’s own recollection and account of relevant events.

Although technology may assist with spelling, formatting or presentation, extensive rewriting can create uncertainty about whether the statement genuinely represents the witness’s own evidence.

In Godwin v Godwin [2026] EWHC 923 (Ch), the High Court considered witness statements that had been prepared with assistance from ChatGPT.

The individuals concerned stated that AI had been used for grammar, spelling and presentation. However, the original drafts were not produced, leaving the court unable to establish whether the statements remained in the witnesses’ own words.

The court consequently approached the relevant evidence with caution.

Although the case did not concern an employment dispute, its implications are relevant to the preparation of witness evidence in employment litigation.

Employers should ensure that:

• Witness statements are based on the witness’s own recollection and expressed in their own words.

• AI is not used to invent, embellish or materially alter factual evidence.

• Original drafts are retained where limited technological assistance is used.

• The preparation process is transparent and consistent with applicable procedural requirements.

• Appropriate assistance is available where a witness has a disability or does not use English as their first language.

• AI is not used to generate rehearsed answers or responses to anticipated cross-examination questions.

Practical implications: Employers should establish clear expectations concerning the preparation of witness statements and ensure that witnesses understand the importance of authenticity, accuracy and personal responsibility.

9. Digital Evidence: Establishing Authenticity

Generative AI can create or manipulate documents, photographs, audio recordings and video material.

As these technologies become more sophisticated, questions concerning the authenticity and reliability of digital evidence may become increasingly important in workplace investigations and tribunal proceedings.

Where authenticity is disputed, employers should take appropriate steps to preserve original material.

This may include retaining original files and devices where appropriate, preserving relevant metadata, documenting how evidence was obtained and maintaining a reliable chain of custody.

Specialist forensic advice may be necessary where a dispute involves potentially manipulated audio, video or electronic records.

Practical implications: Employers should incorporate digital evidence preservation into investigation and litigation procedures, ensuring that relevant material can be assessed without undermining its integrity.

10. Confidentiality, Legal Privilege and Disclosure Risks

AI use can create additional risks where employees or advisers enter workplace information into generative AI platforms.

Prompts and outputs may contain confidential business information, personal data, legal advice, litigation strategies or sensitive employment records.

Depending on the circumstances, the use of AI tools may raise questions concerning confidentiality, legal professional privilege, disclosure obligations and compliance with data protection legislation.

Employers should distinguish between approved enterprise systems with appropriate contractual and technical safeguards and publicly accessible AI tools that may not provide equivalent protections.

Practical implications: Organisations should establish clear restrictions on the information that may be entered into AI systems.

Particular care should be taken with legally privileged material, sensitive personal information, confidential investigations and documents relevant to ongoing litigation.

Legal and data protection advice should be obtained where necessary to determine whether appropriate safeguards are in place.

11. AI Governance: Strengthening Employment and Litigation Readiness

AI governance should form part of an employer’s wider approach to employment risk management and litigation preparedness.

Policies should address how AI may be used in HR processes, internal investigations, legal correspondence, document preparation and tribunal proceedings.

Key considerations include:

• Approved AI systems: Identifying authorised tools and setting restrictions on the use of unapproved platforms.

• Data protection and confidentiality: Establishing clear rules for handling personal, sensitive and privileged information.

• Human oversight: Requiring appropriate review of AI-assisted decisions, communications and legal documents.

• Verification: Ensuring that legal authorities, factual assertions and quotations are checked against reliable sources.

• Record retention: Maintaining appropriate records of original documents, prompts and outputs where necessary and lawful.

• Escalation: Establishing procedures where AI materially influences investigations, evidence or litigation submissions.

• Training: Providing practical guidance for HR professionals, managers, in-house legal teams and witnesses.

Policies should be supported by clear internal responsibilities and periodic reviews to reflect technological developments and emerging judicial guidance.

Conclusion

Generative AI is reshaping the way workplace concerns are presented and employment disputes are conducted, but it does not change the fundamental legal obligations governing employers, employees or tribunal participants.

Employers must continue to assess grievances fairly, identify potential protected disclosures, comply with data protection requirements and ensure that legal submissions and witness evidence are accurate and reliable.

Recent judicial decisions underline the importance of human accountability, procedural compliance and careful verification of AI-assisted material.

For businesses operating in the UK, the most effective response is not to discourage all AI use, but to establish proportionate governance arrangements, train relevant personnel and maintain robust employment and litigation procedures.

AI can be a valuable tool for improving efficiency, but it remains a support mechanism rather than a substitute for professional judgment, reliable evidence or sound legal advice.

By Burness Paull LLP, Scotland, a Transatlantic Law International Affiliated Firm.  

For further information or for any assistance please contact ukscotland@transatlanticlaw.com

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