Autonomous Coding: Accountability and Governance | Nym Health

The original version of this blog appears on Libman Education’s website here and was published on July 21, 2026.

Autonomous coding changes how work gets done, but it does not change who is responsible for it.

Compliance risk does not transfer to the vendor when the engine makes a coding error. Your organization is still signing the claim. The engine is not, and the vendor is not. That reality makes contractual clarity and internal ownership essential.

Specificity in autonomous coding vendor contracts

When reviewing vendor contracts, I recommend pushing for specificity in these areas:

• What are the vendor’s obligations when accuracy falls below agreed thresholds? Knowing this in advance changes the dynamic when performance issues arise. Vendors should be committing to a clear remediation plan, including how they will improve accuracy, how quickly, and what accountability looks like if performance does not meet expectations, whether that is credits or other contractual adjustments.
• How are regulatory and payer policy updates handled, and within what timeframe? If the annual ICD-10-CM update takes effect October 1st, the expectation should be clear on when the engine is updated, validated, and ready for production.
• Who owns the audit trail? Vendors need to be able to produce documentation showing how each encounter was coded, what logic was applied, and when. A well developed audit trail should allow you to clearly trace the engine’s inputs, decisions, and coding outputs at the encounter level.

Vendors who are confident in their product will not balk at these conversations. Vendors who avoid specifics here are telling you something important. At the same time, vendor accountability does not replace internal accountability.

Autonomous coding governance structure

Autonomous coding needs an owner inside your organization. Not just the person who manages the vendor relationship, but a governance structure that connects HIM, Compliance, Revenue Integrity, and Finance around shared accountability for how the engine performs.

In practice, this often looks like a standing operating committee that meets regularly to review accuracy metrics, surface exception trends, flag payer-specific issues, and decide when human review thresholds need adjustment.

For example:

• Routing encounters back to human coders when specific charges or procedures are missing and impacting revenue
• Expanding automation into new specialties once performance has been validated

This is not just operational oversight; it is ongoing risk management and quite frankly ongoing AI management. This group does not need to be large, but it does need clear ownership and a defined cadence.

In most organizations that have gotten this right, HIM or Revenue Integrity chairs the committee, with standing representation from Compliance, IT, and Finance. The cadence is typically monthly once the engine is stable, moving to quarterly once metrics hold steady for several cycles.

Time to update your compliance plan

One practical step that often gets overlooked is updating your compliance program documentation to reflect that autonomous coding is in use. Many organizations are still operating off policies written when all coding was done by humans. Your policies should clearly state how autonomous coding is governed, how exceptions are handled, how accuracy is validated, and how the methodology aligns with your vendor. If it is not documented, it is very difficult to defend.

Check out this Peer Insights Playbook for insight into how Intermountain Health and Ohio State University Physicians approached coding accuracy and auditing after going live with Nym's autonomous coding engine.