Agentic AI: Build vs. Buy in Regulated Industries

Many organizations are encountering hidden costs when building their own agentic AI platforms, especially in regulated industries. This mirrors past experiences with DevOps toolchains. Here's the thing: when AI coding tools emerged, many teams started creating individual solutions. This leads to managing numerous tools not designed to work together, with more time spent on integration than on actual results. What's interesting is that while building can foster expertise, divergent experimentation often doesn't serve the whole organization. Companies want consistent, governable, and scalable AI enablement for everyone. The bottom line: building an agentic AI platform means becoming a platform vendor, assembling frameworks, governance, and infrastructure. Buying means adopting a unified platform. This distinction is crucial in regulated environments, where the complexity of the orchestration layer demands a significant, multi-year engineering commitment.