Sarah Tyler

Implementing artificial intelligence in a legal practice demands more than enthusiasm and budget—it requires systematic planning across technology, operations, ethics, and change management. Whether you're a general counsel considering AI for your corporate legal department or managing partner evaluating options for your firm, the complexity can feel overwhelming. Over hundreds of implementations across practices ranging from boutique IP firms to multinational litigation powerhouses, a clear pattern emerges: successful deployments follow a structured approach while failures typically skip critical steps in their rush to realize benefits. This comprehensive checklist distills those lessons into actionable items, each with the rationale explaining why it matters for sustainable AI adoption. The legal industry's adoption of artificial intelligence has accelerated dramatically, driven by client pressure for cost reduction, competitive intensity, and the technology's proven capa...

Corporate legal departments face mounting pressure to control costs, manage increasing regulatory complexity, and deliver faster turnaround times on critical legal work, all while maintaining the precision and risk management that defines effective legal practice. Traditional approaches—hiring additional staff, implementing basic automation tools, or outsourcing routine work—provide only incremental improvements and often introduce new challenges around quality control, knowledge retention, and technology integration. The result is a persistent set of pain points that limit the strategic value legal departments can deliver to their organizations and create bottlenecks in business execution. Addressing these challenges requires solutions that fundamentally change how legal work is performed rather than simply making existing processes marginally faster. Generative AI Legal Operations offer multiple distinct approaches to solving the core problems facing corporate legal departments, fro...