AI in Healthcare Claims Processing: Workflow Overview
Struggling with manual claims processing and high costs? Learn how AI in healthcare claims processing works and see how you can implement it in your business.
Oops! Something went wrong while submitting the form.
In healthcare, every second counts, and so does every decision.
Traditional healthcare claims processing is often slow, paper-heavy, and prone to errors. Delays only drive up costs and complicate care.
AI in healthcare claims processing can streamline everything from claim submission to payment–accelerating workflows, improving accuracy, and delivering better claims outcomes for everyone involved.
Here’s a closer look at AI for claims processing in healthcare, so you can see how it works behind the scenes and how it can fit your company.
How AI Solves the Biggest Challenges in Healthcare Claims Processing
In the last few years, healthcare claims processing has been increasingly challenged by rising claims volumes, high error rates, and administrative burdens.
According to Experian Health’s State of Claims report, one of the biggest challenges is spending, which has reached $4.8 trillion in 2023, and it’s up 7.5% from the previous year. The costs are straining both providers and patients.
Another big issue is the claims denial.
In the same report, 77% of the surveyed providers reported an increase in denials in 2024. Most common causes include missing or inaccurate data, authorization issues, and coding errors.
In 2024, 84% of healthcare organizations tried to reduce denied claims and have made it their priority.
Experian Health tied this issue to an estimated $260 billion in wasted healthcare dollars annually.
Sift even mentioned that 31% of providers still manage denials manually, which quickly ramps up administrative time and costs.
A combination of increased claims and high error rates caused by manual handling of the documents is ramping up administrative costs. This situation isn’t ideal for healthcare providers, insurance companies, and clients.
Adapt to policies and regulations, including compliance
So overall, here’s how AI compares to traditional healthcare claims processing:
With so many benefits of AI-powered healthcare claims processing, companies are already implementing AI solutions in their workflows. Here’s what such workflow automation looks like behind the scenes.
How AI Can Be Used in Healthcare Claims Processing
Including AI solutions in healthcare claims processing doesn’t mean you have to rip and replace your existing workflows. For example, in AgentFlow, tailored AI Agents integrate into existing workflows and work together to automate the workflow end-to-end.
Submission and Ingestion
Healthcare claims begin when electronic health record (EHR) systems submit supporting documents like:
Medical records
Invoices
Other paperwork
With AgentFlow, ingestion happens automatically by capturing and preparing incoming data without manual bottlenecks.
Data Classification: Document AI
After submission and document ingestion, Document AI reviews the documents and extracts key data points. It classifies and organizes medical records, making them ready for validation.
All of this happens without human error or slow manual entry.
Validation and Diligence: Database AI and Conversational AI
Next, AgentFlow’s Database AI Agent cross-checks extracted data against patient information.
Conversational AI helps fill any gaps or request clarifications, ensuring that the claim data is complete, accurate, and compliant.
Approval or Denial: Decision AI
Decision AI analyzes all validated information to approve or deny the claim. It applies pre-set rules, learning from past decisions to improve over time–reducing delays and inconsistencies.
For complex claims, Decision AI can flag and notify the human for a review, keeping humans in the loop while logging every decision and reason behind it for explainability and compliance.
Automated Reporting: Report AI
Finally, Report AI generates detailed approval or denial records.
These reports can be automatically shared with claimants, providers, and insurers to ensure transparency and fast communication.
Report AI can also generate reports for the company to ensure transparency and compliance.
Best Practices for AI in Healthcare Claims Processing
Successfully implementing AI in healthcare claims processing workflows requires more than just automation.
You need a thoughtful, strategic approach that ensures trust, efficiency, and accuracy.
Ensure Transparency and Explainability
AI solutions in healthcare claims must do more than just make decisions. They need to show how and why they made them.
Claims teams and patients should be able to trace approvals, denials, or escalation decisions back to understandable factors.
Transparent and explainable AI helps build trust, improves regulatory compliance, and makes it easier to correct mistakes before they impact customer satisfaction.
Choose a Solution That Integrates with Other Systems
A healthcare claims AI system should work with existing EHRs, claims management process platforms, and external data providers.
Integrated systems create smoother workflows, reduce manual entry, and minimize the risk of data gaps or duplication.
The right AI solutions should connect easily with the tools and platforms your company already uses. Instead of the costs of ripping and replacing your existing systems, artificial intelligence that integrates via APIs can help bring faster adoption and greater AI ROI.
Use High-Quality Internal and External Data
AI Agents are only as good as the data they learn from.
Healthcare claims processing requires the use of both clean, structured internal data (for example, patients' records or historical claims data) and reliable external sources.
Keep in mind that unstructured data can also be used for AI, as long as the data is prepared for AI.
Feeding your AI system with diverse, high-quality data ensures more accurate classifications, validations, and accurate claims processing decisions over time.
Keep Humans in the Loop
While AI accelerates claim processing and reduces manual work, human oversight remains essential.
Medical insurance claims can often involve nuances that require expert judgment.
“AI should serve as a tool to enhance, not replace, human judgment.” — Kate O’Neill
Building workflows that allow humans to audit, review, and override AI decisions where necessary ensures ethical standards are met. It also reduces liability and maintains a high standard of care for claimants.
AgentFlow platform is a great example as it was designed with all the best practices at its core–delivering transparent decision-making, seamless integration, support for diverse data inputs, and flexible human-in-the-loop workflows to help companies modernize claims processing while staying in control.
Implement AI in Claims Processing
Would you like to implement AI in your healthcare claims processing to improve efficiency and save costs, among other benefits?
Book a demo to learn how AgentFlow works and how you can use it to create, orchestrate, and manage AI Agents in one platform to automate your workflows end-to-end.
.svg)
.svg)
.svg)
.avif)
.png)
