P2P

P E E R T O P E E R M A G A Z I N E · S P R I N G 2 0 2 6 77 of a gym membership in January: lots of sign-ups, not many toned abs. In other words? AI maturity should no longer be measured by how many people have access to or use the tools. It should be measured by how deeply AI is integrated into standardized, enterprise- wide workflows. Real, measurable ROI will only happen when AI shifts from one-off experiments to repeatable workflows. While we are seeing this clearly in legal today, the shift to workflow-driven ROI is applicable to nearly every industry. WHY EXPERIMENTATION AND ADOPTION ARE NOT ENOUGH Many organizations have built a strong foundation through experimentation. Leaders have empowered employees with AI tools and encouraged creative exploration. This investment has built muscle memory. The next step is channeling that energy into repeatable workflows. What many have found, however, is that individual users or groups create little islands of productivity that never quite scale to the mainland. Output quality varies widely. Teams are solving the same problems in parallel without realizing it. This is a clear opportunity. However, there is good news. Many organizations are closer to AI maturity than they realize. Employees have access to advanced AI tools, usage metrics look strong, and experimentation is widespread. The underlying processes simply have not caught up, and that is where the real opportunity lies. In conversations with legal teams across the industry, I keep hearing the same thing: "We've got the tools, we know how to use them, and our people are getting better at using them, but we just don't know what good looks like at scale." That question is the real starting point for workflow maturity. Without enterprise-wide alignment, organizations face inconsistent outputs, duplicated efforts, and growing governance risk. In this setting, AI is more of a helpful sidekick than a structural force. It helps individuals knock out individual tasks, but it does not fundamentally change how work gets done across the organization. So how do organizations move to AI maturity? DEFINING AI MATURITY: FROM ONE-OFF TASKS TO EMBEDDED WORKFLOWS Shifting to workflow-driven AI maturity starts with reframing how organizations conceptualize AI. Leaders must stop thinking primarily about singular tasks and start visualizing end-to-end workflows. They must focus on what repeatable steps will drive operational efficiency. How can those improve results for your teams and your clients? Understanding the difference between tasks and workflows is a helpful place to start. Tasks are isolated actions team members can take, such as summarizing, drafting, or extracting materials. Workflows, on the other hand, are multi-step, repeatable processes, many of which require agentic AI to orchestrate. Instead of responding to a single prompt, these workflows support sequenced reasoning across multiple steps, integrating internal documents and authoritative sources while producing consistent outputs. Think of it this Real, measurable ROI will only happen when AI shifts from one-off experiments to repeatable workflows.

• Cover