After months of proof-of-concept work, the enterprise AI industry is reaching an inflection point: AI agents are moving from demonstrations to production deployments.
What's Working
Organizations that have successfully deployed AI agents share several common approaches: human-in-the-loop design, clear boundaries, robust observability, and iterative improvement.
What's Not Working
Common failure patterns include deploying agents where reliability requirements exceed current capabilities, attempting to automate complex workflows without sufficient guardrails, and failing to invest in operational infrastructure.
The Path Forward
Successful agent deployment requires changes to workflows, governance, and organizational processes — not just technology implementation.
