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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Payer enrollment exceptions—applications or follow-ups that need missing, conflicting, or payer-specific information resolved—are a plausible fit for a human-supervised AI agent working alongside enrollment software. The case is about the shape of the work, not proven product performance: existing sources document fragmented processes and revenue concerns, but do not show that agents outperform SaaS. The practical question is whether an agent can manage the irregular handoffs without taking consequential decisions away from authorized staff.
Where the revenue leak starts
A provider may be ready to see patients while payer enrollment remains incomplete. Until the relevant enrollment is in place, a group can face delays in billing or payment. The operational work is not just entering information into a form: staff may need to assemble accurate provider and organization details, submit them through the applicable process, check status, and resolve requests or inconsistencies.
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The Centers for Medicare & Medicaid Services (CMS) calls provider enrollment “the gateway to the Medicare Program.” Its February 2024 presentation describes the Provider Enrollment, Chain, and Ownership System (PECOS) as collecting and maintaining data submitted on CMS-855 enrollment forms. CMS also identifies PECOS and the National Plan and Provider Enumeration System (NPPES) as systems of record for provider enrollment information and National Provider Identifier (NPI) data. An NPI is a unique 10-digit identifier for providers and organizations in the United States. These facts describe Medicare enrollment systems; they do not mean that all payer enrollment runs through PECOS or NPPES.
Friction can arise at handoffs as well as during initial data entry. In a survey-and-certification context, CMS materials document providers’ uncertainty about whom to contact, inaccurate status information, and delayed or incomplete referral packages. Those are specific examples from the processes covered by the presentation, not evidence that every commercial or state Medicaid workflow has the same failure modes. Medicaid enrollment is state-administered, and CMS says it cannot require states to align their processes or processing timeframes.
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That variation matters to automation. A system may be able to standardize collection and tracking, while a particular case still needs a person to interpret a request, reconcile source information, or decide what can safely be attested.
Why exception packets are a plausible agent-sized unit of work
“Exception packet” is a useful design term here, not a formal industry standard. It means the case-specific bundle of information and actions needed to resolve an enrollment issue: the application or request at issue, the relevant source records, what is missing or inconsistent, the next follow-up, and evidence of what happened. Keeping the case together gives an agent a bounded objective instead of asking it to automate an entire enrollment department.
What can be prepared or coordinated
- Identify a missing field or a mismatch between submitted information and an available source record.
- Gather the relevant documents and organize them for staff review.
- Draft a payer-specific follow-up using the case facts and prior correspondence.
- Track what has been submitted, what remains unresolved, and which response or review is due.
These are candidate tasks for a supervised workflow, not capabilities established by the cited studies. An agent should not infer unknown facts, silently alter a provider record, make an unsupported attestation, or submit a consequential change without the required human review. A useful division of labor is machine preparation and monitoring, with an authorized person resolving ambiguity and approving actions that carry compliance or payment consequences.
Why this differs from automating the routine path
When information is complete and the process is predictable, standard forms, rules, and workflow software can handle repeatable collection and routing. Exceptions are less uniform: the next step may depend on what is missing, which payer or jurisdiction is involved, and what has already been communicated. That makes them a plausible place for an agent to assist with context gathering and follow-up while leaving the system of record and approval authority intact.
This is a design argument, not a finding that agents are inherently better than SaaS. The sources below document operating problems, survey responses, and a standards-based slice of the ecosystem; none is a head-to-head agent-versus-software performance study.
What the reported revenue and staffing figures do—and do not—show
Medallion’s January 21, 2026 announcement summarizes a survey of more than 550 healthcare leaders from provider groups, health systems, and payers. These are vendor-published survey results, not government statistics or independently verified population estimates:
- More than half of surveyed hospitals and provider groups reported measurable revenue loss tied to credentialing delays; many hospitals reported losses above $1 million annually.
- 38% of surveyed healthcare organizations reported high turnover or burnout in administrative and clinical roles, while another 20% reported vacancies across medical staff services teams.
- Nearly one-third reported denial rates between 25% and 50%; the announcement says 40% were tied to application-related errors in the survey’s reported context. This is not a claim that 40% of all healthcare denials have that cause.
- 12% of AI investments and initiatives reportedly touched credentialing or enrollment.
Medallion CEO and founder Derek Lo characterized the findings this way: “The data isn’t subtle. Credentialing delays are costing organizations real money. Behind every delay is a stack of manual, error-prone processes that are ripe for automation.” That is an executive’s interpretation of the company’s survey, not evidence that an agent beats SaaS.
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A separate Medallion survey of 337 U.S. provider-based healthcare organizations, announced March 20, 2024, offers historical context rather than a current prevalence estimate. The vendor reported that 46% of respondents said unoptimized enrollment workflows and slow turnaround affected revenue; 69% used two or more software tools to complete enrollment; and 52% reported entirely manual credentialing workflows. Around 60% said they spent more than four hours on primary-source verifications for a single provider, and nearly one-third reported end-to-end turnaround of 30 days or more. These figures are respondents’ reported experience in that 2024 survey, not a measurement of every organization today.
Jennifer Mohler, chief revenue cycle officer at Southwest Medical Imaging and a respondent in Medallion’s 2026 report, said, “Most provider groups and payers are in survival mode. Many providers are associated with multiple entities, and affiliations are fluid.” Her comment points to a practical challenge: provider relationships can change, so keeping enrollment information current may require ongoing coordination, not just a one-time application.
Where standards and existing software fit
Enrollment work is not a blank slate awaiting an agent. Provider groups already use software and operational processes, and some parts of the ecosystem have standardized rules. CAQH CORE’s EFT and ERA enrollment data rules set maximum standard data elements health plans or their agents may collect and specify aspects of collection flow and format. That is a standards-based part of the ecosystem, not proof that the rules cover every credentialing task or payer-specific exception.
Likewise, enrollment software can support data management, routine workflow, and visibility. An agent, if used, should complement those capabilities rather than be treated as a replacement for the authoritative records, required processes, or staff accountability. The right architecture depends on what the organization already uses and where unresolved cases actually stall.
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The following criteria are a practical evaluation framework, not a validated scoring model. Assess them on a bounded pilot using representative cases and your organization’s own controls.
| Evaluation area | Question to test | Evidence to look for |
|---|---|---|
| Exception coverage | Can it route missing, conflicting, or payer-specific information to the right person and track resolution? | Cases handled, exceptions escalated, and unresolved items made visible. |
| Status and handoffs | Can staff see what was submitted, what remains pending, and where follow-up is needed? | A traceable case history with clear ownership and next actions. |
| Human control | Are attestations and consequential submissions reviewed by an authorized person? | Approval gates that cannot be bypassed by an automated draft or action. |
| Auditability | Are source documents, decisions, changes, timestamps, and communications recorded? | An auditable record that lets staff reconstruct how the case was handled. |
| Integration and data reuse | Can it work with provider data and enrollment systems already in use? | Reliable data flow without creating conflicting records or duplicate entry. |
| Operational fit and cost | What setup, maintenance, training, and exception-review work remains? | A realistic account of staff time and ongoing ownership, not just a software demonstration. |
Compare the agent-assisted process with the existing workflow on the same kinds of cases. Track completion, rework, elapsed time, unresolved exceptions, staff review burden, and whether every consequential action had the required approval. A faster draft is not a win if it creates more correction work or weakens control.
What a safe rollout looks like
- Map the current exception path. Identify where cases stall, who owns each handoff, which records are authoritative, and what evidence is required before a submission or attestation.
- Choose a narrow, reviewable use case. Start with tasks such as assembling a case packet, flagging mismatches, or drafting follow-ups. Keep final decisions and sensitive submissions under authorized staff control.
- Define escalation and audit rules before launch. Specify what the agent must not infer or change, when it must stop for human input, and how source material, drafts, approvals, and communications are retained.
- Measure against the current process. Use comparable cases and include rework, staff effort, pending-case visibility, and approval compliance alongside turnaround time.
- Expand only where results justify it. Different payers, states, and enrollment processes may require different handling; success in one bounded workflow does not establish suitability everywhere.
The practical conclusion
The strongest case for an agent is not that it replaces enrollment software. It is that a supervised agent may help manage the irregular work around otherwise structured processes: assembling context, noticing gaps, preparing follow-ups, and keeping exception status legible. CMS materials show that system and jurisdiction boundaries matter; vendor surveys report operational and revenue concerns; and CAQH CORE rules demonstrate that some enrollment activity is standardized. None establishes superior agent performance. Treat the agent as a candidate layer for a measured, human-controlled workflow—not as a proven shortcut to payer approval or payment.
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