Artificial intelligence is no longer a futuristic concept in healthcare payments. It’s now a strategic necessity. More than 80% of healthcare leaders consider AI an integral part of their revenue cycle management (RCM) operations, with 70% classifying it as a top organizational priority, according to a new study commissioned by healthcare payments software provider Waystar and conducted by Forrester Consulting.
The research, based on surveys of more than 300 healthcare finance and IT executives, revealed that AI is delivering measurable improvements in claims accuracy, denial prevention, workforce efficiency, and payment speed — with performance gains ranging from 13% to 37%.
Key Findings
- Outperformance Across the Board: AI exceeded expectations in nearly every RCM function measured. Survey respondents reported improved denial prevention (+27%), greater workforce efficiency (+36%), and enhanced collections and patient financial experiences (+37%).
- Growing Trust in AI: 60% of decision-makers said their trust in AI increased after adoption. Many who were initially skeptical now view AI as more accurate than human execution, especially for tasks like claim follow-up and denial appeals.
- Widespread Use of AI Tools: Technologies such as machine learning, generative AI, and agentic AI are being applied across front-end authorizations, mid-cycle coding, and back-end claims processing.
- Faster, More Secure Implementations with Trusted Partners: Most healthcare providers are leaning on existing RCM software partners to deploy AI, citing easier integration, quicker ROI, and stronger security — while only 1% are turning to new-to-market AI vendors.
Strategic Recommendations: The report includes clear guidance for organizations looking to optimize their use of AI:
- Define Clear Use Cases: Successful AI implementation begins with well-scoped goals. Leaders should identify which RCM tasks AI will support and set realistic expectations for value creation.
- Build Internal Trust Through Early Wins: Deploy AI in focused areas — such as denial prevention or claim accuracy — to build internal confidence before scaling.
- Train Teams for New Roles: As AI reduces manual workloads, staff should be retrained to focus on strategic and analytical responsibilities, with a strong emphasis on AI literacy, ethics, and data privacy.
- Prioritize Payer-Facing Workflows: Leaders should target AI investments that enhance payer interactions, including tools that generate prior authorization documents and denial appeals.
- Enhance Collaboration Between RCM and IT: 82% of surveyed leaders are now making AI investment decisions jointly between revenue cycle and IT departments to ensure better alignment and results.
