Case Study: NRMA’s In-House Legal Team Embraces AI

The NRMA’s in-house legal team is emerging as a leading example of how artificial intelligence can be embedded into everyday legal practice. Operating within a large, complex organisation, the team supports a broad range of business functions, each of which requires timely, accurate, and commercially relevant legal input.

Recognising the growing demands on its legal function, the NRMA sought to evolve its operating model. Working with Thomson Reuters, the organisation has taken a structured approach to integrating AI into its workflows—moving beyond experimentation and into operational deployment.

The Challenge: Managing Scale, Complexity, and Time Pressure

Like many in-house legal teams, the NRMA faced increasing pressure to deliver more with limited resources. The volume of legal work—particularly research, document review, and knowledge retrieval—was expanding, while business expectations continued to rise.

Lawyers were required to navigate large volumes of information across multiple matters, often under tight time constraints. This created a risk of inefficiency, where significant time was spent locating and synthesising information rather than applying legal judgement and strategic insight.

At the same time, the organisation needed to ensure consistency and accuracy in its legal outputs, particularly in areas involving regulatory and operational risk. The challenge was clear: how to scale legal capability without proportionally increasing workload or headcount.

The Solution: Deploying Thomson Reuters AI Across Core Workflows

To address these challenges, the NRMA implemented an AI-enabled solution through the Thomson Reuters platform. Rather than adopting AI as a standalone tool, the legal team focused on embedding it directly into its core workflows.

The platform was deployed to support key activities, including legal research, document summarisation, and drafting assistance. By integrating these capabilities into daily processes, the NRMA ensured that AI became a natural extension of legal work.

This approach reflected a deliberate strategy: to treat AI as an operational layer within the legal function, enhancing existing processes rather than replacing them. The technology was introduced in a way that complemented legal expertise, enabling lawyers to work more efficiently while maintaining control over outputs.

The Impact: Productivity Gains and Enhanced Legal Insight

The adoption of Thomson Reuters AI has delivered measurable benefits for the NRMA’s legal team. One of the most immediate impacts has been a significant reduction in the time required to conduct research and review complex materials.

By automating the initial stages of information gathering and analysis, the platform allows lawyers to access relevant insights more quickly. This not only improves efficiency but also enhances the quality of legal work, as professionals can focus on interpretation and strategic application rather than manual processing.

The solution has also contributed to greater consistency across the legal function. With AI supporting the identification and summarisation of key information, outputs are more standardised, reducing variability and improving overall reliability.

Importantly, these gains have translated into a shift in how the legal team engages with the business. With more time available for advisory work, lawyers are better positioned to provide proactive, commercially aligned guidance.

Stakeholder Perspective: Building Confidence in AI-Enabled Legal Work

A critical factor in the success of the NRMA’s initiative has been stakeholder engagement. Both legal professionals and business stakeholders have needed to build confidence in the use of AI within legal processes.

The NRMA’s approach emphasises that AI is an enabler rather than a replacement for legal expertise. As highlighted in the original discussion of the initiative, the technology supports lawyers in delivering faster, more informed advice, while final judgement remains firmly with the legal team.

Stakeholders have recognised the value of this model. By combining Thomson Reuters AI with human oversight, the NRMA has struck a balance between efficiency and trust.

The broader implication for legal teams is clear: successful AI adoption in legal contexts depends not only on technology, but on how it is positioned and governed. At the NRMA, this has meant embedding AI within an accountability framework, ensuring that all outputs are reviewed and validated by qualified professionals.

A Blueprint for Operational AI in Legal

The NRMA’s experience demonstrates how in-house legal teams can move from experimentation to execution in their AI strategies. By focusing on integration, capability building, and governance, the organisation has successfully embedded AI into its legal operating model.

The use of Thomson Reuters AI has enabled the NRMA to address core challenges around scale, efficiency, and consistency, while also enhancing the strategic role of its legal function.

For legal and IT leaders, this case study offers a clear takeaway: AI is no longer a future consideration. It is a practical tool that, when implemented thoughtfully, can transform how legal services are delivered.