Posts related to ai category

Healthcare Compliance Is Where AI Agents Earn Trust or Lose It Forever

Vinay Patankar · 10 Mar, 2026 · AI

I sell AI automation to hospitals. I spent three days at HIMSS in LV. And honestly? I'm less confident about AI agents in healthcare than when I arrived. Not because the technology is bad. Epic just launched Agent Factory. Microsoft announced Agent 365 at $15 a seat. Every booth had some version of "our AI does the work for you." The demos were good. The compliance conversations were terrifying. I kept ending up in sessions where compliance officers and risk managers were asking the same question in different ways: "Who is responsible when the agent makes the wrong call?" Nobody had a great answer. Trust in healthcare AI isn't about whether the agent can do the task. It's about whether you can prove it did the task correctly, every time, to someone who will fine you if you can't. That's a fundamentally different bar than "it works." That is the regulated-industry version of the control plane problem. A STAT News piece that came out during the conference kind of nailed it: health AI agents are here but validation is not. The capability gap closed. The trust gap didn't. I watched a vendor demo an agent that could process prior authorizations in minutes instead of hours. Legitimately impressive. Then someone in the audience asked "where's the audit trail?" and the demo person kind of froze. There was no audit trail. The agent just did the thing. In healthcare, "it just did the thing" is not an acceptable answer. Joint Commission doesn't care how fast your agent works. They care whether you can produce documentation showing every step, every decision, every exception, and every human review point. The companies getting this right are the ones that started with the compliance architecture and added AI on top. Not the other way around. They built the evidence layer first. Who approved what, when, why, what data was used, what the fallback was if the agent was wrong. The ones getting it wrong are bolting agents onto existing workflows and hoping the existing audit trail covers it. It doesn't. An agent doing work autonomously generates completely different compliance requirements than a human clicking through screens. We see this constantly at Process Street. The organizations that deploy AI agents successfully in regulated environments are the ones that treat compliance as the first design constraint, not the last checkbox. They build the proof infrastructure before they build the automation. Most companies are still doing it backwards. Ship the agent, worry about compliance later. That works fine until survey season. If you're deploying AI agents in healthcare or any regulated industry, the question isn't "can the agent do this?" It's "can we prove to a regulator that the agent did this correctly, and what happens when it didn't?" That's not a feature request. That's the whole product.

Process Before Agents

Vinay Patankar · 16 May, 2026 · AI · Technology

UiPath added testing, deployment, credentials, and audit on top of Claude Code and OpenAI Codex this week. Most of the coverage called it the path to enterprise AI. That misses what is actually happening. UiPath, ServiceNow, Collibra, IBM, monday.com. Five of them shipped or rebranded an agent governance layer in the last 30 days. Different names. Same pitch. Their control tower will watch your agents and govern what those agents are allowed to do. That is the loud fight. The quiet question underneath it is simpler. Govern what, exactly? You cannot govern an agent's output if the work the agent is doing is not already a defined process. A control tower sitting on top of freeform tickets, chat messages, and ad hoc tasks is monitoring chaos. The agent does whatever. The tower logs whatever. The auditor still has no idea what should have happened. Real agent governance starts one layer below the control tower. It starts with the process the agent is supposed to follow. Steps, decisions, approvals, evidence, role assignments. The boring stuff that turns "the agent ran" into "the agent followed the right path." This is the gap most of the category is skipping. The companies racing to ship governance dashboards have the easier half of the problem. The harder half is that most of their target buyers do not have structured processes underneath the work they want agents to do. Without that, the dashboard becomes theater. Pretty charts. Bad signal. The buyer's real question this year is not which control tower to pick. It is whether the work an agent is about to touch is structured enough to govern in the first place. If it is, any decent governance layer will do its job. If it is not, the dashboard will just give a confident readout while the agent quietly writes bad data into the system of record. Process before agents. Process before governance. Process before control towers. The operators I am watching get this right are the ones treating the agent layer as the last thing they bolt on, not the first.