Anka CRO says AI in healthcare must finish revenue cycle work

Anka Chief Revenue Officer Gayatri Garg said revenue cycle teams need AI that does more than flag problems during a recent interview on Hum FM’s Open Forum Business Hour. Her message: automation should help hospitals and physician practices collect payment faster, especially as rural providers face mounting financial pressure.

Why it matters: - Hospitals and physician practices can now see more of their revenue cycle problems, but many still lack the staff or systems to fix them. - A denied claim creates two jobs: identifying the issue and completing the work needed to recover payment. - For rural hospitals, the stakes are especially high. The Chartis Center for Rural Health says 41% of rural hospitals operate with a negative margin. - Uncollected earned revenue can limit a provider’s ability to keep serving patients.

What happened: - Gayatri Garg, Chief Revenue Officer at Anka, discussed AI in healthcare on Hum FM’s Open Forum Business Hour. - Garg said AI creates value when it helps revenue cycle teams complete work, not just spot problems. - Garg also outlined what healthcare leaders should evaluate before buying revenue cycle technology. - The full interview is available in Anka Health’s resources.

The details: - Garg said revenue cycle teams need AI that can pull records, answer documentation requests, check claim status and follow up until a claim is resolved. - Garg compared AI to driver assistance, saying the technology works best with accurate data, well-configured processes and specialists who know when judgment is needed. - Garg cautioned against assuming AI can fix a broken workflow. - Garg also warned against paying for automation that an EHR already provides. - Garg said denial rates above 5% should prompt leaders to ask why the rate is that high. - Garg said some denials cannot be prevented, but others can. - Anka connects to a provider’s existing EHR and identifies where revenue is leaking. - Anka works claims, denials and underpayments to recover revenue. - Experienced RCM specialists step in where judgment matters. - Anka’s team stays involved from onboarding onward.

Between the lines: - The interview reflects a broader shift in healthcare AI from analytics toward execution. - Vendors that only surface problems may not improve collections unless their tools also drive the next action. - Garg’s message also suggests buyers should measure technology by provider outcomes, not vendor efficiency. - She said AI’s benefits should show up in collections, denial performance, days in AR and cost-to-collect. - Automation should also free experienced staff for complex cases and patient conversations.

What's next: - Garg said hospitals and doctors should keep pushing for tools that help them get paid for services already delivered. - Revenue cycle leaders are likely to keep weighing AI platforms against workflow gaps, staffing limits and existing EHR capabilities. - The central question for buyers is whether a system only finds work or actually gets it done.

The bottom line: - In Garg’s view, healthcare AI is only valuable if it helps providers collect more of what they are already owed.