SRA's Risk-Based Supervision Framework Will Treat AI Governance Failures as Evidence of Systemic Control Failure, Not Isolated Technical Errors

Analysis published on 27 October 2026 sets out how the Solicitors Regulation Authority (SRA) is likely to approach AI-related supervision in practice under its existing risk-based regulatory model, without the need for new rules or formal prohibitions. The core argument is that AI does not introduce a new category of professional obligation for solicitors. Instead, it intensifies scrutiny of whether firms can demonstrate they were in control of the systems through which legal services were delivered. Where an AI-related failure occurs, the SRA is unlikely to treat it as a discrete technology problem. It will treat it as a proxy for broader governance failure, examining whether the firm had any structured basis for relying on the AI system at all. Multiple routes into supervision are identified beyond client complaints: thematic reviews focused on technology-enabled practice, intelligence from insurers and litigation, whistleblowing by staff, and routine supervisory engagement with higher-risk firms. Critically, supervisors will not be primarily interested in whether a specific AI output was checked. Output checking is characterised as a reactive control rather than evidence of structured risk management. What supervisors will actually examine is whether firms can produce documented evidence of governance: ownership of AI systems, written policies, documented assumptions about risk, and structured procedures for validating AI-assisted work. The SRA's own 2024/25 annual summary confirms it is significantly increasing investment in data, intelligence, and risk-scanning capabilities, and has already developed an AML (anti-money laundering) model using machine learning to predict money laundering risk among regulated firms.