In an Information Week article titled “The Multi-AI Model Stack Is Here. Now Someone Has to Manage It,” Michael Adler, Akerman’s director of AI governance and data protection, discusses how organizations should establish clear accountability and governance as they deploy multiple AI models. He emphasizes that while technical, legal, privacy, and risk teams may all contribute to model-selection decisions, one person should ultimately be accountable for each deployment and empowered to pause it if problems arise. Michael also advocates evaluating models based on their specific use case rather than simply choosing the highest-performing model, with baseline requirements for confidentiality, data retention, and contractual protections established first. He further highlights the governance challenges created by fragmented vendor logs and recommends continuous, scheduled, and event-driven reviews as models, risks, and circumstances change — underscoring that “newer is a reason to test, not a reason to switch.”