Enterprise AI Architecture: Centralized vs. Distributed Models for Legal Teams
Legal departments investing in artificial intelligence face a foundational choice that will shape their capabilities for years: should they adopt a centralized Enterprise AI Architecture where a single platform and governance team controls all intelligence capabilities, or pursue a distributed model where individual practice groups and matter teams deploy specialized AI tools? This decision carries profound implications for speed to value, cost structure, risk management, and competitive differentiation. Yet most legal leaders lack a systematic framework for evaluating these architectures against their specific organizational context, regulatory constraints, and strategic priorities. The stakes have never been higher. As Enterprise AI Architecture matures from experimental pilots to mission-critical infrastructure supporting Contract Lifecycle Management, litigation support, and compliance monitoring, the wrong architectural choice creates technical debt measured in millions and oppor...