Architecture Review Boards (ARBs) have traditionally evaluated application architectures against key enterprise criteria such as security, scalability, integration, resilience, supportability, and compliance. With the rapid adoption of artificial intelligence (AI), machine learning (ML), and generative AI technologies, organizations are increasingly deploying intelligent solutions that introduce new architectural, operational, ethical, and regulatory challenges.
As a result, ARBs must expand beyond traditional review dimensions to assess AI-specific considerations, including data governance, model lifecycle management, explainability, bias mitigation, AI security, operational monitoring, and responsible AI practices. The evolution of ARBs is essential to ensure AI solutions deliver business value while maintaining trust, compliance, accountability, and enterprise risk controls.
Article URL: https://www.jamiecadvisory.com/perspectives/your-ai-governance-problem-is-probably-an-architecture-problem/ Comments URL…
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