AI x Dispute Resolution: collective & consumer actions – quick guide

What do we mean by AI collective and consumer actions, and why now?

Collective and consumer actions enable consumers to enforce rights collectively when individual claims are too small to pursue alone economically.

Certain structural characteristics of AI systems, or “aggravating factors”, can create a perfect storm for group claims:

• Scale: AI systems apply the same model to very large user populations; a single flaw or bias can affect huge groups, easily satisfying “common issues” requirements and making claims attractive to funders.
• Black box: It is hard to explain individual AI decisions; this information asymmetry supports narratives of unfairness and lack of control.
• Built-in evidence: AI systems create their own evidence of potential wrongdoing in the form of the underlying algorithm, model, training data, weights and logs.
• Marketing vs reality: Overstated claims (“98% accurate”, “AI with human review”) versus actual performance are powerful evidence of misleading practices.
• Superficial human oversight: Over-stated oversight (“human in the loop”) can be an aggravating factor increasing the risk of regulatory non-compliance and civil liability.

These dynamics, combined with expanding collective redress tools in the UK and EU, make AI a priority area for claimant firms and litigation funders.

What are the main collective action routes for AI in the UK?

In the UK, collective redress relies on several procedural tools, including:

• Group Litigation Orders (GLOs): Court managed multi party claims, with common issues resolved together under CPR Part 19.
• Representative Actions (High Court): One party represents others with the “same interest” in the claim; effectively opt in in practice.
• CAT Collective Proceedings (competition only): Opt out available for UK consumers, but only for competition law claims; no general opt out regime yet for AI/consumer harms.

This fragmented landscape creates a less claimant-friendly environment than in many EU jurisdictions.

How does the EU Representative Actions Directive change the landscape?

The Representative Actions Directive (RAD) creates an EU wide mechanism for collective consumer redress, which requires Member States to put in place legislation which:

• Lets “qualified entities” (consumer organisations or public authorities) seek injunctions and redress (e.g. compensation, repair, replacement, refund) for infringements of a wide range of EU laws, including product safety rules and the GDPR.
• Allows domestic and cross border actions in any Member State where affected users are located.
• Makes it easier to package AI related harms (privacy, discrimination, digital harms) into representative actions, often drawing on alleged breaches or findings under the EU AI Act.
• Creates claimant “hot spot” jurisdictions and forum shopping opportunities due to differing national models (opt in vs opt out, procedures).

Taken together, the RAD lowers the barriers to bringing coordinated, cross border consumer claims relating to AI systems in the EU.

What we expect to see next

• Growth in AI related collective and consumer actions in Member States with claimant friendly RAD implementation and established collective redress regimes.
• More hybrid class actions combining AI specific rules (such as the EU AI Act) with GDPR, the Digital Services Act and consumer protection law, following the model of the TikTok and X cases.
• An increase in follow on collective actions based on regulatory findings by data protection authorities (and, from August 2026 onwards, in relation to the AIA) Market Surveillance Authorities or the AI Office.

Practical steps for organisations

• Map and preserve evidence: Map your AI systems, understand how they make decisions, and know what logs and documentation exist and how to access them quickly.
• Strengthen governance and human in the loop oversight: Robust governance evidence will be central to your defence, including having clear internal response plans for regulatory enquiries and letters before claim.
• Identify jurisdictional hot spots and monitor emerging claimant theories (including online) to anticipate future claims.
• Develop a dual regulatory / civil defence strategy

This webinar series

This session forms part three of an eight part AI x Dispute Resolution webinar series running from February to December 2026, covering:

• Overview of AI disputes
• Regulatory enforcement
• Collective and consumer actions
• Negligence
• Intellectual property
• Product liability
• AI incident response
• Evidentiary issues
• Future proofing against AI risk