Most AI projects fail not because of the model — but because the workflow was never documented well enough to automate.

Before Carenodes built viperOS, we spent 7 years manually executing one of healthcare's most complex operational workflows: payer contracting. Fee schedule negotiation, network enrollment, underpayment recovery, compliance tracking — for 600+ providers across every major U.S. insurer. We didn't start with a hypothesis. We started with a spreadsheet, a phone, and a repeating problem.

When we finally built the AI layer, we had something most organizations don't have: a fully documented, field-tested operational playbook with 7 years of ground truth. The result was 16–18x documented ROI — because we automated what was already proven to work.

This session is for operators and leaders deciding where AI belongs in their organization. Not "what AI can do in theory" — but how to identify the specific workflows where AI delivers real ROI within months, what it takes to transition a manual process into an intelligent system, and the three mistakes most organizations make when they skip the operations step.

Key Takeaways:

1. How to identify which workflows are genuinely ready for AI automation — and which aren't yet
2. Why your existing operational documentation is your most valuable AI training asset
3. What the transition from manual process to AI-automated system actually looks like — including what breaks and what surprises you