The legal profession has reported broad uptake of artificial intelligence tools, with around two-thirds of lawyers using AI in some form as of 6 September 2025, yet many remain unconvinced about reliability and risk management in daily practice. The findings underscore the sector’s cautious posture: adoption has accelerated, but confidence, governance, and training have not kept pace, raising implications for clients and case outcomes.

Context and Background

According to the report, legal professionals are embracing AI for research, drafting, and summarisation to improve efficiency and manage rising workloads across firms and in-house teams. The survey points to widespread experimentation with generative systems and productivity assistants, though use is often confined to low-risk tasks and closely supervised workflows. Organisations increasingly emphasise acceptable-use policies and approval processes whilst exploring secure, enterprise-grade deployments.

The data highlights persistent anxieties about hallucinations, confidentiality, and client exposure, with many respondents flagging accuracy checks and human oversight as essential safeguards. Practical hurdles include uneven tool performance, integration gaps with document management systems, and the need to optimise prompts and review protocols. Several examples cite measurable time savings on first drafts and discovery triage, but note that quality assurance and sign-off remain firmly human-led.

The trend aligns with broader UK digital transformation: firms are piloting AI to stay competitive while balancing Solicitors Regulation Authority expectations and client duty of care. With London’s legal market a global centre, the shift matters beyond the UK, influencing cross-border workflows and vendor roadmaps. As the profession tests AI at scale, standard-setting, training programmes, and evidence-based best practice are becoming differentiators.

Looking Forward

The report suggests firms will prioritise structured training, clear governance, and role-based permissions to build confidence, alongside red-teaming and benchmark evaluations tailored to legal tasks. Expect moves toward private models, retrieval-augmented workflows, and auditable review trails to address confidentiality and provenance. Procurement criteria are likely to sharpen around accuracy metrics, data handling, and integration with precedent banks and knowledge systems.

Stakeholders anticipate AI augmenting, not replacing, practitioners—shifting junior workloads toward higher-value analysis and client engagement—with new competencies in prompt design, validation, and risk assessment. For the AI ecosystem, the legal sector’s rigorous standards could drive safer-by-design tools, while in the UK, targeted skills programmes and industry partnerships may help narrow the confidence gap and realise trustworthy productivity gains.

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