AI Governance

Last week I wrote about Shadow AI becoming healthcare's #1 technology hazard.

The response made one thing clear: this isn't a niche problem. Clinicians everywhere are reaching for tools that weren't built for them because the right tools haven't shown up yet.

But here's the part that doesn't get talked about enough.

Even when health systems recognize the problem, fixing it is harder than it looks.

Because the real challenge in 2026 isn't adoption. It's governance.

Clinicians moved fast. Policy didn't. And now organizations are trying to build frameworks around tools that are already embedded in daily workflows, sometimes without anyone in leadership knowing they're there.

Governance sounds bureaucratic. In healthcare, it's a patient safety issue.

A general-purpose LLM doesn't know your formulary, your documentation standards, or when it's getting something wrong. And it definitely doesn't have a BAA.

So what does AI governance actually require in a clinical environment?

1. Visibility: Knowing exactly which AI tools are being used, by whom, and where patient data is flowing. You can't govern what you can't see.
2. Accountability: clear ownership over AI outputs. When a tool generates a note, a code, or a recommendation, someone has to be responsible for reviewing it. AI assists. Clinicians decide.
3. Compliance Infrastructure: Not just a BAA checkbox, but real alignment with HIPAA, SOC 2, and whatever regulatory frameworks are coming next. Because they are coming.
4. Clinical Validation: Evidence that the tool performs accurately in real workflows, not just in a demo. That means measurable benchmarks, not marketing claims.

The organizations getting this right aren't starting with bans. Shadow AI exists because a real need went unmet. The clinicians using unauthorized tools aren't reckless, they're burned out and resourceful.

Real governance means giving them something better: purpose-built AI that fits clinical workflows, meets every requirement above, and is transparent about what it doesn't know.

When the right tool exists, the workaround disappears.

2026 will be the year health systems either get ahead of this or spend the next few years cleaning up what shadow AI left behind.