AI is already in your organization. Whether it’s helping engineers write code, accelerating design verification, analyzing quality data, or becoming part of the medical device itself, AI is changing how MedDevice companies operate. The question is no longer whether to use AI, but how to govern its use without slowing innovation to a crawl. And while establishing an AI governance committee might sound like a responsible first step, another committee isn’t necessarily the answer. Effective governance is about making the right decisions, at the right level, with the right accountability.

Before establishing—or expanding—your AI governance approach, leadership should be able to answer five questions:

1. Where is AI already being used? You can’t govern what you don’t know exists. Look beyond approved applications to experiments, embedded vendor capabilities, and AI quietly influencing engineering and quality decisions.
2. Who has the authority to approve its use? Not every AI application requires executive oversight. Define decision rights that balance risk, expertise, and speed, with clear escalation paths for consequential decisions.
3. What happens when AI gets something wrong? From inaccurate requirements to missed safety signals, understand the consequences of failure and establish controls appropriate to the risk—not simply the technology.
4. How does AI governance fit into our existing QMS? Your ISO 13485 processes already address design controls, risk management, supplier qualification, and change control. Extend those processes to accommodate AI, rather than creating a parallel bureaucracy.
5. How will we know when something changes? AI models, data, vendor services, and even how employees rely on AI can evolve. Establish ownership, monitoring, and reassessment triggers before those changes become problems.

The goal isn’t to make AI adoption harder. It’s to make responsible AI adoption easier. Organizations that get governance right create clear boundaries within which teams can experiment, learn, and deliver value with confidence. Those that don’t risk either uncontrolled adoption or approval processes that move slower than the technology they’re supposed to govern. Neither is a particularly attractive strategy.

Join agilityIRL and Medical Alley on November 3 for our webinar, “Who Makes the Call? Structuring AI Governance in MedTech.” We’ll explore practical governance models, how to align oversight with your organization’s risk profile and culture, and how to integrate AI into the QMS you already operate. You’ll leave with actionable questions and a clearer path toward AI governance that enables innovation rather than obstructing it.