Healthcare organizations are facing mounting board-level pressure to operate more efficiently. Regulatory changes including the One Big Beautiful Bill Act (OBBBA) and HRSA administrative and compliance updates to 340B are significantly reducing revenue streams, and many health systems must now cut tens to hundreds of millions of dollars simply to maintain the margins they were previously achieving. Doing more with existing resources is a business imperative for boards and executive teams.
As healthcare leaders evaluate where to act, revenue cycle management (RCM) is emerging as an opportunity to improve efficiency. RCM has already embraced automation and the next generation of AI can further extend that progress.
A board-level and business imperative
Shrinking reimbursement, persistent labor costs, growing denial volumes and rising administrative complexity mean that healthcare systems cannot simply hire their way out of today’s challenges. Boards are asking management how the organization will sustain its mission while absorbing reductions in revenue. Efficiency is central to the answer.
“The conversation about AI has moved into the boardroom,” said Adrianne Boylen, a Grant Thornton Partner of Transformation/Finance Modernization for Healthcare. “Our clients are being asked to protect their margins in the face of significant revenue reductions, and Board members are asking how to do more with less. The revenue cycle is one area that can support this imperative.”
Payors today are deploying AI to review and adjudicate claims at an increased speed and scale, which is contributing to rising denial volumes. When one side of the transaction automates and the other does not, the imbalance is seen directly in aging accounts receivable, rework and administrative cost to the system. To keep pace, healthcare systems must bring comparable capabilities to their own operations by using AI to anticipate and prevent denials, respond faster and match the sophistication of the payors they negotiate with every day.
Building on a strong foundation
For many healthcare systems, automating RCM should not be a leap into the unknown. The revenue cycle has been one of healthcare’s earliest adopters of machine learning and natural language processing. Robotic process automation (RPA) and computer-assisted coding have been used for more than a decade to handle high-volume, repetitive tasks such as eligibility checks and claim-status follow-up in payor portals.
“The revenue cycle has been quietly evolving for years, as seen through computer-assisted coding and RPA. The use of AI lets us extend that automation further, building on a foundation our teams already understand,” Boylen said.
AI today uses large language models and agentic capabilities that offer opportunities to augment existing automation. Where earlier tools followed fixed rules or suggested actions for a human to confirm, newer capabilities can interpret unstructured information, adapt to change and take on more of the routine work end-to-end. For revenue cycle teams that have already built automation muscle, AI is the natural next step in a journey that is well underway.
How we can help you
INDUSTRY
Maximizing your IT investments
As adoption expands, so do questions about security, governance and control. Here, a practical advantage is emerging: many EHR and enterprise platforms are now embedding AI and agentic capabilities directly into the systems healthcare organizations already use. Using and integrating what vendors are building rather than assembling standalone AI agents tends to make their use more secure, because the guardrails are inherited from the platform’s existing security permissions and the defined set of data those agents are allowed to access.
Using embedded, vendor-built capabilities keeps AI operating within established access controls, reduces implementation risk, and helps maintain governance and compliance while allowing teams to adopt more quickly and with far fewer resources than a custom build would require.
Empowering people to focus on what matters most
The most compelling reason to pursue AI in the revenue cycle is how it improves the workflow of employees. Revenue cycle professionals spend a significant portion of their day on repetitive, low-judgment tasks: checking a portal, re-keying data, following up on a status. When AI absorbs that routine work, it gives time back to the people who do it.
That capacity can be redirected to the work that only those professionals can do, including working the exceptions, the nuanced payer conversations, and the complex appeals and the judgment calls that require genuine critical thinking. These activities are where experienced staff create the most value, and where automation cannot substitute for human expertise. Framed this way, AI is less about replacing people and more about elevating them: reserving human attention for the problems that truly need it.
Is your revenue cycle AI strategy positioned to deliver more efficiency securely?
Healthcare leaders evaluating AI in the revenue cycle should ask:
- Are we keeping pace with the AI capabilities payors are using to adjudicate our claims?
- Are we building on the automation foundation we already have rather than starting over?
- Are we prioritizing measurable outcomes such as denial reduction, cash realization, cost to collect and workforce capacity?
- Are we using the guardrails built into our existing systems?
- Have we redesigned the workflow so staff can focus on the exceptions, and the judgment calls only they can make?
- Have we defined where human oversight remains essential, especially for patient-facing and compliance-sensitive activities?
The guiding principle
Even as health systems embrace AI to become more efficient, implementation must be thoughtful. Used well, AI protects a healthcare system’s margins and frees the time and the abilities of the people that make their mission possible.
Contact:
Partner, Transformation - Finance Modernization, Healthcare Advisory
Grant Thornton Advisors LLC
Content disclaimer
This Grant Thornton Advisors LLC content provides information and comments on current issues and developments. It is not a comprehensive analysis of the subject matter covered. It is not, and should not be construed as, accounting, legal, tax, or professional advice provided by Grant Thornton Advisors LLC. All relevant facts and circumstances, including the pertinent authoritative literature, need to be considered to arrive at conclusions that comply with matters addressed in this content.
Grant Thornton Advisors LLC and its subsidiary entities are not licensed CPA firms.
For additional information on topics covered in this content, contact a Grant Thornton Advisors LLC professional.
Ready to talk? We’re ready to listen.
Request a meeting and a member of our team will be in touch to see what we can do to meet your needs.
Want to submit an RFP? Please submit your request through our RFP submission page.
Share with your network
Share