Guidance

Legal services advisory AI Growth Lab: case studies

Published 3 August 2026

Case study 1: Garfield.Law Ltd

The AI Growth Lab for legal services provides a streamlined opportunity to support innovative law firms to navigate the regulatory system and operate effectively within existing regulatory frameworks.

One example of an innovative firm that has already been authorised by the Solicitors Regulation Authority (SRA) is the AI-driven firm, Garfield.Law Ltd. This firm delivers legal services primarily through AI, specialising in supporting small and medium-sized businesses to recover unpaid debts through the small claims court, where the cost of pursuing low-value claims can often outweigh the sums involved.

Garfield.Law Ltd approached the SRA with an ambition to provide a lower cost service using AI. The company sought support to better develop its understanding of how its AI-driven model could work in practice in line with SRA rules. The firm distilled core regulatory requirements through engagement with the regulator, building in controls that demonstrated compliance and managed risks. The regulator agreed monitoring arrangements to maintain a clear understanding of how the business model and AI tool were operating in practice.

Although the service is AI-enabled, it is delivered under the supervision of a regulated solicitor who remains fully accountable for the service delivered to consumers. The firm put in place safeguards to manage risks such as inaccurate outputs, alongside clear user disclosures about how the service operates and its limitations.

The legal services AI Growth Lab provides a structured environment for legal services firms and LawTech companies to explore how innovative models, such as this example, can be compliant with regulatory rules, and overcome any concerns or assumptions that rules may be more rigid or restrictive than they are in fact. The lab aims to give innovators greater confidence to develop AI-enabled services that are both compliant and capable of significant benefits to both consumers and business, improving their access to justice.

Case study 2: coordination between regulators on client data

A large law firm is working with a LawTech company to develop an in-house AI tool to support its work in areas such as conveyancing and family law. The tool is intended to improve efficiency and consistency by drawing on information and data from the firm’s existing and historical client files, including:

• correspondence
• matter records
• transaction data

As development progresses, the firm identifies a number of questions relating to its proposed approach, such as what steps they would need to take should they seek to use client data to train or fine-tune its AI systems. It has engaged with relevant guidance from each regulator but is uncertain how the distinct regulatory requirements align in practice, and the timing of different regulatory processes.

Through the legal services AI Growth Lab, the firm is able to bring these questions to the SRA, CLC and ICO in a co-ordinated way, rather than engaging with each organisation separately. The regulators work together to:

• discuss the firm’s proposed approach
• discuss how the different regulatory frameworks and processes fit together
• clarify and resolve any areas of apparent uncertainty

This structured interaction with each of the regulators gives the firm greater confidence that it can continue working with the tech company to develop and use its new AI tool in compliance with its regulatory obligations.

Case study 3: analysis of sales packs in conveyancing

A conveyancing firm has developed a concept for an AI tool that analyses sales packs provided by sellers of residential property to identify issues that require closer examination by the conveyancer.

The tool highlights potential problems or inconsistencies so that the conveyancer can decide whether:

• further information is needed
• the buyer needs to be advised immediately or at a later stage
• an inconsistency within the information in the sales pack can be addressed easily

The firm wishes to use the sandbox to test the tool and find ways to demonstrate to the end user:

• why it has decided to highlight the issues that it has
• whether and how to provide assurance that other common issues not identified in a particular case do not arise in the data provided

The firm hopes users can trust the tool during development, testing and normal operation. The tool helps conveyancers identify potential risks to clients so they can take appropriate action.

Such an approach would provide assurance to other firms that might potentially use the tool without requiring a technical understanding of the AI approach.