LIDW24 – AI in the Afternoon: Lessons in Adoption

AI in the Afternoon: Practical Lessons in Adoption

The “AI in the Afternoon” event, part of London International Disputes Week, brought together experts from Simmons & Simmons, Therme Group, and TrialView to discuss the practicalities of AI adoption in law firms. The discussions focused on AI’s transformative potential, practical strategies for implementation, and strategies for its adoption.

1. Current AI Tools for Legal Practice

• Custom LLMs: Law firms are implementing large language models (LLMs), and examining how to use them for legal tasks, implementing them in ways with more control and security compared to publicly available AI tools like ChatGPT. These internal implementations of these models are designed to address the specific needs of legal professionals, ensuring appropriate use and confidentiality.
• Integrated AI in Existing Software: AI functionalities are being incorporated into widely used tools like Microsoft Office (using Copilot), enhancing efficiency in tasks such as email drafting, generating starting points for documents in word or presentations in powerpoint, translations, search and data analysis.
• Generative AI for Research: Legal knowledge providers are integrating AI to streamline research processes, allowing lawyers to generate comprehensive and grounded responses to prompts and to produce initial drafts of legal documents quickly.
• Specialised AI Applications: AI is increasingly utilised in specialist areas such as e-Discovery and document management, significantly reducing the time required for reviewing and organizing large volumes of documents.

2. Practical Applications of AI in Legal Work

• Summarisation: AI tools can generate first drafts of document summaries, aiding lawyers in quickly understanding and conveying complex information to clients.
• Data Extraction: AI can be used to extract key information from long documents, and produce it in useful formats (e.g. chronologies, dramatis personae).
• Content Evaluation: AI assists in comparing and analysing semantic differences between legal documents, such as witness statements, and identifying inconsistencies or areas of concern.
• Document Management: Advanced AI applications facilitate efficient management and retrieval of information from large datasets, using natural language queries to provide answers more quickly, and with references cited where techniques like Retrieval Augmented Generation are used.

3. Security and Confidentiality Concerns

A major focus of the discussion was on the importance of maintaining security and confidentiality when using AI in legal contexts. Custom implementations solutions are essential to ensure that sensitive legal data is handled appropriately, mitigating many of the risks associated with general AI tools.

4. AI Adoption Strategies

Adopting AI in legal practice requires a strategic approach. Law firms must:

• Start with AI Literacy: progress and sensible decisions will only be possible with a good level of understanding of how the technology works, the risks and available mitigations
• Define Clear Objectives: Identify specific goals and challenges that AI can address before implementation.
• Leverage Existing Knowledge: Apply lessons from past technology adoptions to streamline AI integration.
• Balance Innovation and Caution: Avoid rushing into AI adoption without thorough planning and understanding of its implications.

5. Implications of AI Adoption

The potential impacts of AI on legal practice are significant:

• Pricing Models: As AI automates more tasks, clients may come to expect outcome-based pricing models, and law firms may need to find ways to recover technology investment costs. The billable hour was justifiable when it was hard otherwise to find a basis for charging and measure the work done but now pricing for legal services will have to evolve.
• Skill Sets: New expertise will be required, both by upskilling existing lawyers and hiring new talent with relevant skills.
• Risk Appetite: Firms must balance cost efficiencies with risk management, aligning client expectations with realistic service delivery.
• Market Differentiation: Larger firms may benefit from scale in investing in AI, while smaller firms might leverage agility for faster adoption. Firms with deep knowledge assets could create barriers to entry for others, solidifying client relationships.
• Competitive Edge: The knowledge of ‘the law’ is already an assumed baseline. Quality of service, encompassing speed, efficiency, and commercial awareness, will drive competition.

6. Skills and Team Structure for Effective AI Use

Successful AI adoption depends on multidisciplinary teams that combine legal expertise with technological proficiency. Essential skills include:

• Technical Literacy: Basic understanding of AI tools and their applications in legal work.
• Data Science Knowledge: Ability to analyse and interpret data generated by AI tools.
• Project Management: Effective coordination and management of AI projects to ensure they meet legal and business objectives.

Speakers included: Emily Monastiriotis, Jonathan Schuman, Stephen Dowling, Nicholas Cranfield and Eimear McCann

With thanks to Simmons and Simmons, who drafted this post, and who kindly granted us permission to share. The original post can be found here.