This episode of “The Geek in Review” explores MinterEllison’s strategic adoption of Microsoft Copilot, delving into the practical implications and challenges of implementing generative AI within the legal industry. Guests Amber O’Meara, Head of Innovation, and Tim Andrews, Director of IT Operations, discuss the firm’s multifaceted approach to generative AI, emphasizing its potential to enhance client experiences, boost productivity, and empower their legal professionals by automating mundane tasks and allowing them to focus on more complex legal work. This strategic vision, endorsed by the firm’s leadership, drove their decision to participate in the Copilot Early Access Program, providing valuable insights and shaping their implementation strategy.
One of the key takeaways is MinterEllison’s measured and strategic rollout of Copilot. Rather than a firm-wide deployment, they opted for a phased approach, prioritizing specific personas and departments that would benefit most from the technology. Initial challenges included data jurisdiction limitations, the inherent “fear factor” of adopting new technology, and user inertia stemming from unmet expectations. The firm addressed these obstacles through a comprehensive training program, incorporating a dedicated “Gen AI Time” initiative, collaborative sessions with Microsoft, and a “reverse mentoring” program for partners. This multifaceted approach, coupled with internal communication and a knowledge-sharing platform, fostered enthusiasm and addressed concerns, leading to impressive user satisfaction and reported time savings.
MinterEllison’s training program played a crucial role in the successful adoption of Copilot. Combining internally developed resources with vendor-provided training, the program addressed both the technical aspects of using Copilot and the art of prompt engineering. The firm’s innovative approach of dedicating fee-credited time for generative AI training proved highly effective, incentivizing participation and demonstrating leadership commitment. This investment in their people, combined with gamification elements like their internal “Mint Coin” cryptocurrency, fostered a competitive spirit and encouraged active engagement in the learning process.
The podcast highlights the importance of prompt engineering in maximizing the effectiveness of Copilot. While initial user expectations often fell short due to simplistic prompts, the training program emphasized the need for detailed and nuanced prompts to achieve optimal results. This understanding, coupled with the recognition that Copilot excels at content generation rather than computational tasks, significantly improved user satisfaction. The firm also acknowledges the importance of maintaining a “human in the loop” to validate outputs and mitigate potential inaccuracies or “hallucinations” generated by the AI. They anticipate the future ability to share custom prompts within the firm, further streamlining workflows and enhancing collaborative efforts.
Finally, the conversation touches on the broader impact of generative AI on the legal industry. MinterEllison envisions a future where AI tools are widely adopted, reshaping traditional law firm models and creating new roles focused on innovation and technology. They emphasize the importance of ongoing collaboration, both internally and within the legal community, to address client privacy concerns, share best practices, and navigate the evolving landscape of AI in law. The firm’s commitment to responsible AI usage, guided by their “Lighthouse Principles” and an AI steering committee, underscores their dedication to ethical implementation and client data security. They also see the potential for generative AI to contribute to access to justice initiatives and support social impact work, highlighting the transformative potential of these technologies beyond the traditional boundaries of legal practice.
Links:
Amber (Burgess) O’Meara | LinkedIn
Tim Andrews | LinkedIn
MinterEllison: Overview | LinkedIn
MinterEllison – MinterEllison
Listen on mobile platforms: Apple Podcasts | Spotify | YouTube
Twitter: @gebauerm, or @glambert
Email: geekinreviewpodcast@gmail.com
Music: Jerry David DeCicca
Transcript
Of course, GenAI does a lot more than order or sort text. It translates. It rewrites. It summarizes. It clarifies. It extracts. It interpolates. It expounds upon. It combines THIS and THAT into one thing. It re-imagines THIS, as if it were actually THAT. It recontextualizes THIS as if THAT didn’t exist. Its capabilities go well beyond simply sorting a list. In fact, it often gets simple sorting wrong, because it doesn’t use a hard-coded algorithm to produce it’s text transformation. Instead, GenAI uses vast troves of written example language to determine the probability of the next word it should write, and then the next, and the next… until it reaches it’s maximum output or it runs out of space.
