Start the Conversation

Honeypot Field to Catch Bots
Honeypot Field to Catch Bots

Best practices for implementing AI-document review

Anyone responsible for leading large-scale, organizational change, particularly involving new technology tools, is likely familiar with the multifaceted challenges and opportunities that emerge along the way. Surprisingly, the technical and organizational requirements for implementation can sometimes be easier than managing the earlier stages of gaining internal support and building momentum for the change.

To gain insights into the best practices for technological change management, Adam Nguyen, the Co-Founder of eBrevia, a DFIN company, moderated this panel discussion with two business leaders who are tasked with driving the adoption of AI-powered contract analytics within their global organizations.

Nigel Foster, a Programme Director with Capita plc, a British outsourcing giant, presented Capita’s case study on implementing eBrevia’s AI-powered contract analytics. Nigel shared ways to manage stakeholder expectations to ensure successful adoption and lessons learned while introducing the AI tool to centralize disparate contract review processes.

David Wineman, a Product Manager in Legal Technology Innovation with Baker McKenzie, one of the five biggest law firms in the world, provided additional tips from his experience introducing new technology across global offices and different teams. He sees technological change management on three pillars: people, process and tech. Both David and Nigel agreed that of the three pillars, “people,” can require the most time and effort especially in cases where the technology is not fully understood or tested, as if often the case with artificial intelligence.

What the full panel discussion to learn:

1) How to lay the foundation for change: building momentum with early adopters and winning over and managing the expectations of important stakeholders.

2) Best practices during implementation: important aspects and stages with onboarding, training and overseeing adoption of an AI-contract analytics tool.

3) On-going opportunities and challenges: training the AI and users to leverage the full value of AI-powered contract review, expanding use cases, customization, and more.