AI agents performing live orchestration for integration are exciting and can be a game changer.
Until you start considering mission-critical use cases, such as financial transactions, purchase order workflows, and regulatory compliance, these are high-stakes, heavily governed processes where reliability is non-negotiable. In these scenarios, the same autonomy that drives innovation elsewhere can become a liability. A misinterpreted compliance rule, a hallucination, a failure to complete the task, and suddenly, the benefits of autonomous systems are eclipsed by the cost of failure.
But it doesn’t have to be this way. What if, instead of letting AI agents improvise at runtime, you had them design, build, and evolve integrations “as Code”, leveraging existing DevOps processes companies already have in place and trust?
This represents a different expression of autonomy—one that happens before execution, not during it. And it’s this distinction that unlocks a systematic way to scale agentic workflows across the enterprise.
The Use Case Reality: Different Business Scenarios Have Different Needs
Not all integration problems are created equal. Use cases in real world environments vary widely in