Agents are ready but your architecture probably isn't

This article discusses how most enterprises generate AI activity without creating value because their architecture is not prepared for agentic systems.

• •Model selection is easy; the real challenge is infrastructure: integrating fragmented data sources, implementing governance frameworks, and providing semantic understanding of business context
• •Data silos, skipped governance, and organizational misalignment are the primary causes why agentic systems fail in production
• •Traditional dashboards and batch pipelines cannot support the real-time responsiveness and rapid decision cycles that autonomous agents require
• •Agents need transactional databases built for high concurrency and low latency, not analytical data warehouse systems designed for human-driven queries
• •