Published on May 12, 2026
How AI agents are transforming healthcare BPO and RCM;
beyond what systems like oracle cerner can't do
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Table of contents
Executive summary
Healthcare revenue cycle management teams are under more pressure than ever since more than 63% of providers face shortage in RCM staffing. Prior authorizations, claims processing, denial management, eligibility verification, and patient billing all need to move faster, yet most workflows still rely heavily on manual coordination. .
The global healthcare BPO market was valued at roughly $396 billion in 2025 and is projected to cross $756 billion by 2034. Revenue cycle management alone is expected to grow from $102 billion in 2024 to $291 billion by 2033 in billing, coding, claims, and denial workflows that sit at the heart of BPO operations. As healthcare organizations scale operations and payer requirements become more complex, administrative teams are spending increasing amounts of time navigating disconnected systems rather than focusing on high-value work.
Platforms like Oracle Cerner continue to play a critical role in healthcare operations. It is a reliable, enterprise-grade EHR and RCM platform that gives organizations a structured way to manage patient records, orders, and billing workflows. But healthcare organizations are beginning to realize that storing information and acting on it are two very different things.. And that gap between where data lives and how work actually gets done is where much of the operational drag in healthcare BPO and RCM exists today.
Strata decision tech
The operational gap between systems
The biggest challenge in healthcare operations is not necessarily a lack of data. It is the amount of work required to move that data across systems, workflows, and payer processes.
Prior authorization is one of the clearest examples. A clinical request comes in and someone needs to check whether that request requires authorization, review payer-specific rules, verify eligibility, gather supporting documentation, assemble the submission packet, and monitor payer responses. If the payer requests additional information , the process begins again.
The EHR holds the patient record. The RCM system tracks the claim. Payer portals have manage approvals and status updates. But no single platform coordinates the movement between all three. That coordination work still falls on people.
"80 to 90 percent of prior authorization requirement checks are still performed manually. Between 20 and 40 percent of PA packets go out incomplete or misaligned to payer policy on the first submission. "
What Ai agents actually do differently
This is where AI agents are starting to reshape healthcare BPO and RCM operations. AI agent is not just a reporting dashboard. It is not a workflow template or an RPA bot that clicks through a fixed sequence of screens. They can monitor workflows, understand rules and context, take action automatically, and escalate exceptions when human review is necessary.
In a prior authorization workflow, for instance, agents can detect new PA requests as they arrive, check for relevant payer policy, pull from the EHR, assemble submission packets, and flag it for review; all without someone manually moving between systems to make it happen.
The distinction matters because the bottleneck in most RCM operations is not a lack of data. It is the cost of acting on that data, repeatedly, across high volumes, with the kind of consistency that prevents errors from compounding downstream.
Where agents change the equation in healthcare BPO:
Among all RCM workflows, Prior authorization has emerged as one of the strongest use cases for AI agents. It combines high volume, high variability across payers, and high stakes when it goes wrong. An agent handling PA does not replace the EHR or the RCM system; it works alongside them.
When handled manually, prior authorization often becomes a bottleneck that slows patient care, increases denial rates, and overwhelms administrative teams. AI agents help reduce that friction by automating intake, documentation gathering, validation, and status tracking while working alongside existing EHR and payer systems.
Manual workflow today
Receive PA request
Manually check payer policy
Pull clinical docs from ECR
Review for completeness
Build & submit packet
Handle AIR/ resubmit manually
Every step requires human action
High volume × manual effort = bottleneck
VS
Agent-powered workflow
AI Document Review
Agent check payer policy
Agent pulls docs from ECR
Agent validated completeness
Agent build & submit packet
Human reviews flagged cases only
Human effort reserved for edge cases
Scale without adding headcount
What this means for healthcare BPO operators
For BPO leaders, the shift is not about replacing people. It is about improving how people spend their time. AI agents change the equation by taking over repetitive coordination tasks that consume a large portion of staff time. This allows healthcare teams to focus on more strategic and patient-centric work rather than administrative processing.
This also changes how you think about capacity. If authorization volume spikes — because of a new payer contract, a seasonal pattern, or growth in a particular service line — an agent-based workflow scales without a corresponding headcount increase. You are not adding people to handle more of the same work. You are handling more work with the same people because repetitive coordination is automated.
Organizations that treat agentic workflows as a layer on top of existing systems — rather than a replacement for them — tend to see faster deployment, less disruption, and cleaner results. The EHR stays the system of record. The agent becomes the system of action.
Governance is not optional
One legitimate concern in healthcare RCM is that automation, if it operates without oversight, creates compliance risk.
That means every automated action should be logged, every decision should be explainable, and low-confidence cases should still route to human reviewers. Responsible automation is not about removing people entirely from the process. It is about ensuring human expertise is applied where it adds the most value.
The elsai PA Agent, operates through governance frameworks such as ARMS- Agent Resource Management System that maintains full audit trails for every PA decision, packet, and AIR response,. while allowing organizations to configure review thresholds based on their operational preferences.
Starting without overhauling everything
The practical question for most BPO operators is not whether agents can improve RCM operations — the evidence on that is becoming fairly clear. The question is how to start without disrupting workflows that, however inefficient, are at least predictable.
The answer most organizations find useful is to begin with a single high-volume, high-friction process. elsai Prior authorization is a natural starting point because the pain is well-understood, the workflow is defined, and the results are measurable. You connect the agent to your existing EHR and RCM systems, define the automation rules and review thresholds, run a pilot on one service line or payer, and measure the impact before expanding.
This is not a multi-year transformation project. It is a targeted intervention in a specific workflow, with clear metrics — cycle time, first-pass rate, AIR rate, staff hours per case.
The shift that is already happening
Healthcare BPO operations are not going to stop using systems like Oracle Cerner. These systems remain foundational for clinical and financial operations. But the industry is beginning to recognize that systems of record alone are no longer enough to handle modern administrative complexity. The organizations pulling ahead operationally are building intelligent action layers on top of their existing infrastructure.
Layers capable of coordinating workflows, reducing manual effort, and moving processes forward without waiting for human intervention at every step.
AI agents are quickly becoming that layer.
.The question is not whether they will become standard in RCM operations. It is how quickly each organization will get there, and how much operational drag they are willing to carry in the meantime.
FAQ
Q: Do agents replace EHR systems like oracle cerner?
No. Agents work alongside your existing EHR and RCM platforms. The EHR remains the system of record — agents handle the coordination and action layer on top of it, without requiring you to replace your core infrastructure.
Q: What RCM processes are most suited for agents right now?
Prior authorization, denial management, eligibility verification, and AIR handling are the clearest fits. These processes are high-volume, rule-based, and time-sensitive — exactly the conditions where agents create the most measurable lift.
Q: How do agents handle compliance and PHI in RCM workflows?
Responsible agent platforms operate in HIPAA-aligned environments with encryption, role-based access, and audit logging. Every agent action should be logged and explainable, with human review built into the workflow for low-confidence decisions.
Q: How long does it take to deploy an agent in a healthcare BPO environment?
Most organizations start with a pilot in one service line or payer segment. This approach lets you validate results before expanding, and typically moves faster than a full-scale implementation because it works with your existing systems rather than replacing them.
Q: Can BPO operators control how much automation the agent runs?
Yes. Well-designed agent platforms let you set automation thresholds — so high-confidence cases run automatically while ambiguous ones route to a human reviewer. This gives operators control over where automation runs and where human judgment is preserved.
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