We help back-office and administrative support providers redesign delivery so AI handles the repeatable steps, people handle exceptions, and clients can see quality in the numbers.
AI can take on repeatable steps inside client workflows, such as sorting incoming documents, drafting appeals, checking eligibility and preparing status reports, while trained staff handle exceptions and quality sampling. The value comes from a redesigned delivery model with logged outputs, not from adding a tool to an old process. Client data safeguards and contracts come first.
If AI shortens the work behind a task, per-hour or per-FTE pricing starts to look wrong to the buyer. In Bessemer and Bain's September 2026 sample, half of surveyed organizations reported cutting headcount because of AI or planning to within six months.
HHS says an AI-enabled contractor handling PHI for a covered entity can be a business associate, and names an AI patient-portal chatbot as a possible example. Every AI vendor you add is another link a client will ask about.
In a 2026 Guidehouse and HFMA survey of provider executives, 69% outsourced some or all revenue-cycle work, yet 59% had not implemented AI or automation in their revenue cycle. These are buyer figures, and they matter to billing and RCM companies too.
Clients see the final claim or call outcome, not your checks. An AMA survey reported in May 2026 found only 24% of physicians said medical-necessity denials were consistently reviewed by qualified clinicians, so expect clients to ask for proof.
The same eligibility check runs through different EHRs, payer portals and fax queues. McKinsey found integration the most-cited barrier to scaling AI, which makes data integration a delivery cost, not an afterthought.
Established means widely deployed and well documented. Emerging means real deployments exist but results vary with your data and workflow. Early means pilots or research, not a safe default.
Scanned pages are classified, fields extracted and patients matched, with unmatched items sent to a review queue. Patient matching is never perfect on messy faxes, so people still work the remainder and own the exceptions. AI automation keeps the source image linked to every extracted field.
Defined back-office tasks such as documentation checks, code suggestions and coverage checks have task-level evidence. A coverage check is not an authorization decision, so a coder or specialist still approves anything that changes a claim.
Appeal letters are drafted from the payer's denial reason and the supporting documents, then edited by an appeals specialist. Use is still limited, though affected payers generally must give specific denial reasons from 1 January 2026 under CMS-0057-F.
AI picks which completed items an auditor should check and groups errors by cause. We know of no independent healthcare BPO evidence for this yet, so it is a design to measure, not a proven method.
Agents handle identity verification, routine questions and narrow booking when your team is busy. One major cloud provider lists voice appointment management as preview only, so AI agents should start with routing and verification.
Agents working claims and appeals across systems, with audit trails, are being piloted. Bessemer and Bain report 67% of provider RCM respondents using semi- or fully autonomous agents, but that is self-reported.
Owns the client service levels, explains exceptions and decides when work returns to the client.
Samples completed work, defines error categories and has authority to pause an automated step.
Approves codes and appeal content before submission, so accountability stays with a qualified person.
Keeps business associate agreements, the subcontractor list and the incident process current as part of AI governance.
Works the cases AI could not resolve and reports patterns back.
Measure the share of items needing a human fix and the reasons, then remove the common causes.
Track queue age and receipt-to-completion time by client and task type.
A weekly pack of volumes, accuracy and escalations can replace manual status calls.
A written playbook for rules, systems and sampling is meant to reduce surprises on day one.
Buyers outsource to reduce cost and uncertainty, and they stay with vendors who show quality and controls. AI changes your cost to serve, and go-to-market work turns the delivery model into a story procurement can check.
General information for planning, not legal advice. Statuses and dates are as published at the time of writing.
Sample today's manual work to record turnaround, error rate and exception reasons before any automation changes them.
List every system, AI vendor and agreement that touches client data, and check where records are stored and who can see them.
Automate the safest step with an exception queue and human approval, then share results with the client.
It can add to them. If your service creates, receives, maintains or transmits PHI for a covered entity, business associate requirements can apply, including an appropriate agreement and safeguards. Assess each AI vendor you use the same way.
Only where your data supports it. We found no independent data on how healthcare BPO contracts are being repriced, so we model it from your own volumes, exception rates and rework. Outcome pricing without a stable baseline moves risk onto you.
That depends on the client contract and applicable rules. Texas requires covered EHRs to be physically kept in the US or a US territory from 1 January 2026. We map where data is stored and accessed before designing the workflow.
Sample it. Each week a qualified person checks a risk-weighted selection of completed items and you report error rates and exception reasons. Keep the source document and AI output linked so any item can be traced.
Possibly, but the evidence we have describes intentions, not outcomes. A common first change is a shift from keying to review and exception handling, and we plan those role changes with your managers.
Tell us which client workflow carries the most manual effort and we will help you baseline it and design a supervised pilot.Book a discovery call to scope it.