A new industry perspective argues that healthcare organizations are deploying AI tools but are not yet prepared to manage AI agents inside everyday clinical workflows. The article frames the gap as operational and governance-focused: organizations can adopt software, but effective use of AI “agents” requires safeguards, accountability, and workflow integration planning. The key point for biotech-adjacent stakeholders is that AI deployment can change data flows, decision checkpoints, and documentation burdens that affect downstream clinical development and real-world evidence generation. Without operational readiness, AI systems risk introducing variability or workflow friction that teams cannot easily attribute. The piece suggests the next phase for AI in healthcare is not more models, but more management: monitoring, incident handling, and clear roles when software acts beyond passive inference.