ILTACon Day Two: AI's Early Impact on Legal KM and Billable Hour
Day two of ILTACon brought into sharp focus the transformative yet complex relationship between artificial intelligence and the legal profession, with deep dives into its impact on knowledge management, the venerable billable hour, and the strategic deployment of human capital.
A significant roundtable on knowledge management (KM) revealed a prevailing sentiment of skepticism regarding AI tools, reflecting an industry still in its early stages of adoption. Many firms expressed hesitation to invest heavily in solutions whose long-term viability remains uncertain, leading to what some termed “pilot program fatigue” as KM teams juggle evaluating numerous tools alongside their regular duties. Despite this, firms that have begun integrating AI are reporting tangible value. This isn’t just about saving time, but more crucially, about reallocating it to higher-value activities. Lawyers, for instance, are leveraging AI to generate initial drafts or disclosure schedules, freeing them to focus on strategic analysis rather than painstaking editing or starting from a blank page. The adage, “lawyers prefer a red pen to a blank page,” resonated deeply, underscoring AI’s utility in providing a starting point for refinement.
A significant challenge highlighted was the disarray of internal knowledge. Many law firms do not consistently store all documents within their document management systems (DMS), leading to scattered information across various platforms like OneDrive, SharePoint, and personal folders. This fragmentation impedes efficient search, raises security concerns, and complicates version control, often leaving even original lawyers uncertain of the final document. The advent of AI tools like Copilot, which can surface previously obscure documents, is bringing these access-control issues into stark relief, revealing deeper security vulnerabilities. For AI adoption to scale, seamless integration across systems is paramount; a fragmented user experience, more than imperfect AI outputs, is proving to be the biggest barrier to uptake. This evolving landscape is also reshaping KM roles, shifting them from mere knowledge base maintenance to orchestrating AI workflows, ensuring data quality, and even assisting clients with their own AI implementations, potentially necessitating an increase in KM staffing. Ultimately, the consensus was clear: successful AI adoption hinges on robust processes and a healthy organizational culture; without these, even the most advanced tools become expensive distractions.
The heated “Bill(AI)ble Hours” debate explored whether AI will fundamentally alter the traditional legal service model. The discussion on alternative fee arrangements (AFAs) saw more audience support for their benefits—such as predictability for clients, a focus on value, and freeing lawyers for strategic work—despite concerns about pricing accuracy and re-scoping difficulties. When asked what clients truly desire from firms using AI, the consensus leaned towards enhanced quality and more effective use of spend, rather than just lower costs, though cost efficiency remains a key performance indicator for legal departments.
A compelling point emerged regarding AFAs’ impact on junior lawyers. Proponents argued that AFAs reduce the fear of write-offs, encouraging partners to involve and train junior associates, viewing it as a valuable long-term investment. The audience largely agreed that AFAs benefit junior lawyers. The debate also touched on whether traditional law firm revenue structures impede innovation. A majority felt that partner compensation tied to client relationships can indeed create resistance to new approaches, suggesting that AI could be a tool to demonstrate greater value and attract new clients. Furthermore, the role of allied professionals is expected to grow significantly due to AI’s influence, though not necessarily creating entirely new revenue streams. However, despite the rapid pace of change, both the panel and the audience largely agreed that the billable hour is unlikely to become obsolete within the next five years, as client needs continue to evolve.
Finally, a master class on “Mapping Time to Outcomes” underscored a critical oversight in AI adoption: firms often measure adoption rates instead of the true metric of value—time spent. A striking example cited one firm’s experience with Copilot, which reduced a task from 100 hours per month to just 20, a saving only apparent through diligent before-and-after measurement. The central takeaway was that firms operate blindly on their “human capital supply chain” without mapping time inputs to outcomes through proper data collection. While AI excels at automating research and generating suggestions, strategic thinking and persuasion remain uniquely human domains. The legal industry is moving towards an “agentic-first” model for routine tasks, emphasizing that better measurement directly improves realization rates. The core principle is simple: you cannot optimize what you do not measure, and adoption metrics alone fail to reveal actual time savings or value creation.