I Tracked Why AI Agent Projects Fail. 80% of the Time, It's Not the Agents.

A recent study found that 80% of AI agent project failures are due to operational issues, not the agents themselves. This is a common problem in enterprise IT, where teams struggle to operationalize multi-agent systems. To succeed, teams need to focus on building robust infrastructure, including routing logic, retry policies, and cost tracking. This requires a declarative approach to routing constraints, allowing the system to adapt to changes in provider pricing, outages, and model deprecation. By prioritizing operationalization, teams can avoid common pitfalls and ensure the success of their AI agent projects.