Legal Services Board: AI in Legal Services
Background and context
The Legal Services Board commissioned M·E·L Research to explore how consumers might respond to future developments in artificial intelligence within legal services. The research was designed to support the Legal Services Board’s wider strategic focus on encouraging innovation in legal services while ensuring that consumers remained protected from potential harm.
The wider context was a legal services market in which AI-enabled tools were becoming increasingly visible to consumers. General-purpose AI assistants, such as chatbot-style tools, were already being used by some people as an initial source of legal information, while more specialist legal AI tools were emerging to support activities such as small claims, debt recovery, will writing, employment issues, housing matters and other legal needs. These developments were seen as having the potential to improve access to justice by reducing cost, increasing convenience and helping people to understand their rights. However, they also raised important questions around accuracy, accountability, transparency, privacy, redress, consumer protection and the risk of harm, particularly in high-stakes or complex legal situations.
The Legal Services Board wanted evidence on how consumers understood, experienced and expected AI-enabled and online legal tools to behave across common legal problems. It also wanted to understand where consumers drew the line in terms of what was appropriate, what transparency and accountability they expected, what redress they felt should be available when things went wrong, and where expectations diverged from current regulatory protections or market practice. The research also needed to include a focus on people who may be vulnerable, or who may face complex and high-stakes legal circumstances.
A key challenge for the research was that the subject matter was complex, emerging and unfamiliar to many participants. The research therefore needed to create space for participants to build their understanding, reflect on realistic future scenarios and consider trade-offs between innovation, access, affordability, protection and regulation. Another challenge was that legal services can be low salience for consumers until they are facing a significant life event, while AI can feel technical, abstract or difficult to assess. The design therefore needed to make future possibilities tangible and accessible without leading participants towards a particular view.
Download the report here
Approach
M·E·L Research delivered a multi-stage programme of qualitative and quantitative research with legal service users, drawing primarily on the Legal Services Board’s Public Panel. The Public Panel consisted of around 13,000 individuals across England and Wales who had experience as legal service users. The overall design combined expert input, deliberative engagement, an online community and a representative quantitative survey.
The methodology included:
- Foundational expert interviews: M·E·L Research conducted five interviews with experts working in legal services, technology, regulation and AI-related roles. These interviews explored the current AI landscape for consumers, the likely future trajectory of AI in legal services, risks, responsibilities, regulation, ethics and feasible future scenarios. The expert interviews helped shape the consumer research phases by identifying the types of AI use cases and risks that were most relevant to explore.
- Face-to-face deliberative workshops: M·E·L Research delivered three in-person deliberative events with 48 legal service users in London, Manchester and Cardiff. These workshops enabled extended dialogue, reflection and information sharing. Participants had time to discuss their existing perceptions of AI, consider how AI could be used in legal services, respond to future scenarios and explore trade-offs around fairness, transparency, reliability, accountability, accuracy, human oversight and regulation. The workshop sample was designed to include a diverse mix by age, gender, ethnicity, health and disability, legal service experience and perspectives on AI.
- Online community: Following the deliberative workshops, M·E·L Research ran a two-week online community with 40 legal service users. This stage tested instinctive and reflective responses to a range of scenarios and allowed participants to engage with the topic over time. The sample was again designed for diversity, including by age, region, gender, ethnicity, health and disability, legal service experience, views on AI and views on consumer protection regulation.
- Quantitative online survey: M·E·L Research then conducted an online survey with 1,000 consumers with experience of using legal services. The survey was designed to be nationally representative of the adult population of England and Wales by age, gender, ethnicity and region, with small corrective weightings applied. The survey quantified the key questions, principles, red lines and trade-offs that had emerged from the qualitative research.
- Scenario-based research design: Across the qualitative and quantitative stages, M·E·L Research used future-facing scenarios to make the implications of AI in legal services tangible. These included scenarios covering anO AI assistant that monitored a tenant’s situation and acted without consent, a free employment rights AI tool that gave inaccurate and jurisdictionally inappropriate advice, and a two-tier future in which paid AI tools offered stronger protections than free tools
Outputs and analysis
M·E·L Research analysed the qualitative findings thematically, identifying the core patterns in how consumers thought about AI in legal services. This included analysis of expert interviews, workshop discussions, online community responses and reactions to the scenarios. The quantitative survey data was analysed to validate and quantify these themes, including subgroup differences and statistically significant variations by age, ethnicity, digital confidence, AI use and attitudes towards regulation.
The final output was a written research report for the Legal Services Board. The report included an executive summary, background and objectives, methodology, expert context, findings on the expected future role of AI in legal services, consumer expectations about AI’s impact, views on consumer protection, implications of red lines for AI in the legal sector, conclusions and methodological appendices. It combined narrative analysis, survey findings, scenario responses, participant quotations, subgroup analysis and clear conclusions about the expectation–reality gap facing consumers, regulators and providers.
The research found that consumers were pragmatic about AI in legal services. They recognised its potential to improve access, reduce cost, simplify processes and make legal support easier to use. Public Panel members were particularly optimistic about AI improving ease of use, accessibility and affordability. However, this optimism was balanced by strong concerns about privacy, accuracy, accountability, redress and the possibility that AI tools could expose users to harm, particularly if tools were free, unregulated, inaccurate or difficult to challenge.
The research identified a set of core trade-offs shaping consumer views. These included expanding access to justice through low-cost or free tools versus protecting consumers from harm; encouraging innovation and availability versus enforcing minimum standards; providing fast, automated support versus maintaining user control and consent; and allowing differences in service quality versus preventing unfair or harmful outcomes. Consumers accepted that paid and free tools may differ in terms of convenience, features or user experience, but they strongly rejected the idea that lower-cost or free tools should expose people to greater risk of harm. Safety was viewed as a non-negotiable baseline rather than a premium feature.
M·E·L Research also identified five clear consumer “red lines” for AI in legal services. Participants expected AI tools to protect user safety, provide minimum guarantees for accuracy, avoid taking consequential action without informed prior consent, take adequate responsibility for harm caused, and ensure some level of human oversight. The report showed that these expectations often exceeded what may be realistic under current regulatory arrangements, creating an expectation–reality gap. This gap was particularly significant around accuracy, accountability and consumer protection, where current tools and regulatory structures may not provide the safeguards consumers expected.
The findings provided the Legal Services Board with an evidence base to inform its thinking on AI, innovation and consumer protection in legal services. The work helped clarify the conditions under which consumers were willing to accept AI-enabled legal support, the safeguards they expected, and the risks that could undermine trust. It also gave the Legal Services Board insight into how different groups responded to the issue, showing that younger, more digitally confident users, ethnic minority participants and those with AI experience tended to be more optimistic, while older and less digitally confident users placed greater emphasis on regulation and protection. However, the overall pattern was one of broad consensus around safety, accountability and user control.
M·E·L Research also created a concise infographic to accompany the report for external publication.
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