ISG presentation at Becker’s IT + Revenue Cycle Conference focuses on leveraging AI and automation to address revenue and cost pressures
STAMFORD, Conn., September 15, 2026–(BUSINESS WIRE)–Healthcare organizations are achieving measurable financial and operational results by applying AI to longstanding revenue cycle challenges, says an expert with global AI-centered technology research and advisory firm Information Services Group (ISG) (Nasdaq: III).
Speaking today on the “Navigating the Next Wave of Revenue Cycle Pressures” panel at the Becker’s IT + Revenue Cycle Conference in Chicago, ISG Partner and Healthcare Lead James Burke said AI is delivering immediate financial returns for hospitals and health systems—easing front-end patient access, reducing preventable denials, strengthening coding accuracy and optimizing patient financial engagement.
“Organizations are turning to AI not simply to automate tasks, but to build more resilient and scalable revenue cycle operations that can adapt to rising denial rates, growing prior authorization requirements, workforce shortages and increasing payer complexity,” Burke said. “The greatest revenue cycle value from AI is coming from solving longstanding operational problems at scale. AI is modernizing workflows across the entire RCM value chain, improving workforce productivity and accelerating cash.”
AI solutions can identify claims likely to be denied before submission, flag missing documentation and prioritize work queues based on the likelihood of reimbursement, Burke said. Health systems are reporting denial rate reductions of 10 to 20 percent.
AI is also helping to automate patient access and authorization processes, including prior authorization workflows, eligibility verification, benefit checks and medical necessity reviews. Organizations are reducing manual touch points by 30 to 50 percent and shortening authorization turnaround times from days to hours, resulting in more claims being auto-adjudicated and better care outcomes.
In clinical documentation and coding, generative AI and machine learning are helping to improve coding accuracy, automate chart reviews and identify missed charges and documentation gaps. Organizations are seeing productivity improvements of 20 to 40 percent in targeted workflows while reducing coding-related denials and strengthening revenue integrity.
AI-powered digital assistants also are improving patient financial engagement by expanding self-service capabilities for billing questions, payment plans and financial assistance screening. Engaging patients earlier and providing greater transparency can improve patient satisfaction, reduce call center volumes and increase collections, Burke said. Successful initiatives are tied directly to measurable revenue cycle metrics such as denial rates, net collections, cash acceleration, labor productivity, cost to collect and patient satisfaction.