Law firm content is increasingly being created and managed outside the repositories and workflows firms intended. Sometimes that means entirely new platforms; just as often, it means familiar tools being used in unexpected ways, such as OneDrive instead of the DMS, OneNote as informal case management, collaboration spaces becoming working files, or AI platforms developing into new content repositories. This session will examine content sprawl as an Information Governance challenge, including how sanctioned technology can create unsanctioned or “off-label” information practices, why IG needs visibility before those practices become embedded, and where IG should have a role in technology selection, pilots, SDLC, vendor review, and implementation. The discussion will focus on the growing need for IG to understand not only what technology a firm has, but how lawyers and staff are actually using it to create, store, and manage information.

Matter closure is one of the most persistent challenges in law firm information governance, and one of the most consequential. Unclosed matters create retention exposure, complicate conflicts analysis, inflate storage costs, and leave client materials in repositories that were never designed for long-term governance. This session explores the full arc of matter closure: how to influence attorneys to actually close matters, how to engage financial services partners to establish auto-closure policies, and how to govern client materials responsibly once a matter is closed. Practitioners will share real approaches to balancing firm efficiency, client obligations, and defensible retention across document management systems, collaboration tools, and hybrid environments.

Organizations are rapidly adopting AI, but information governance teams are being asked to solve new challenges while maintaining compliance, defensibility, security, and trust. This session moves beyond theory and explores real-world examples of how legal and information governance professionals are leveraging AI to address practical governance problems. The session will begin with a brief TED-style overview of emerging AI opportunities in information governance, followed by a panel discussion featuring professionals who are actively developing or implementing AI solutions. Panelists will share their use cases, lessons learned, governance considerations, and recommendations for organizations evaluating similar initiatives.

In this interactive workshop, we’ll explore how AI is changing the way organizations measure, monitor, and demonstrate information governance effectiveness, as well as how IG teams can measure the effectiveness of AI governance itself. We’ll begin by examining practical approaches to defining meaningful IG metrics and KPIs, using AI and automation to improve data analysis and reporting, and identifying metrics that help organizations understand AI-related information risks, including data quality, provenance, retention, and access. Attendees will then break into small working groups focused on three areas: defining meaningful IG metrics, measuring AI governance and information risk, and translating metrics into executive-level reporting and action. Each group will develop practical recommendations and report its findings back to the larger group. Attendees will leave with actionable approaches that can be adapted to IG programs at varying levels of maturity.