Becker’s asked 45 healthcare leaders how their health systems will balance human oversight in revenue cycle and clinical documentation in 2026.
The leaders featured below are speaking at Becker’s 11th Annual Health IT + Digital Health + RCM Conference, Sept. 14-Sep. 17, 2026, at the Hilton Chicago.
If you would like to join the event as a speaker, please contact Scott King at sking@beckershealthcare.com.
As part of an ongoing series, Becker’s is connecting with healthcare leaders who will speak at the event to get their perspectives on key issues in the industry.
Editor’s note: Responses have been lightly edited for length and clarity.
Question: How will your system balance automation and human oversight in revenue cycle and clinical documentation in 2026?
Paul LePage. Vice President, Revenue Cycle, UC Davis Health (Sacramento, CA): Our system will employ automation to handle high-volume, rules-based tasks—such as eligibility checks, charge capture, and documentation prompts—while preserving human oversight for clinical judgment, exception management, and quality assurance. In 2026, advanced analytics and AI-driven workflows will surface risk, variance, and compliance issues in real time, enabling staff to intervene where expertise adds the most value. This balanced approach improves efficiency and accuracy without compromising clinical integrity or regulatory compliance.
Mark Townsend, MD. Chief Clinical Digital Ventures Officer, Bon Secours Mercy Health (Cincinnati, OH): Bon Secours Mercy Health balances automation with human oversight in all our applications by building workflows that require validation of inputs from automation. For example, we use color-coding to highlight text-fields that need to be reviewed by a nurse before signing a document. Physicians include documentation in the patient record when their workflows have been enhanced with augmented intelligence. We also create human validation hard-stops in administrative workflows. Said differently, our workflows represent the implementation of our AI governance.
JohnRich R. Levine, DNP, DPA, DBA(c). Chief Nursing Officer, Reeves Regional Health (Peco, TX): At Reeves Regional Health, our automation supports reliability while keeping people close to decisions. Technology helps us capture documentation more cleanly, spot gaps early, and reduce rework that slows both care and billing.
Also, our clinicians and revenue teams remain hands-on at the points where judgment matters most, confirming accuracy, intent, and clinical story before anything moves forward. In this rural system, balance means speed without shortcuts and efficiency without distance from the patient. We can only say automation helps us move faster, and human oversight keeps our work grounded in care, accountability, and trust.
Rajiv Pramanik, MD. Chief Information Officer and Chief Health Informatics Officer, Contra Costa Health (Martinez, CA): For us it is so much in flux due to our safety net population and HR.1, the best IT can do is stay flexible and agile with good data streams.
Erika Putinsky. Vice President, Brand and Digital Marketing Strategy, Emory Healthcare (Atlanta, Ga.): In 2026, the greatest risk in revenue cycle and clinical documentation will not be under-automation; it will be automation that undermines trust. From my perspective at Emory Healthcare, I see the importance of intentionally balancing automation with visible human oversight, particularly as we think about brand and the human side of healthcare. Systems should manage repetitive work while elevating decisions that require clinical judgment and accountability. When automation is transparent and humans remain clearly in the loop, it reinforces trust rather than resistance.
Tomi Kolade, MD. Assistant Chief Medical Information Officer, UTHealth (Houston, TX): In 2026, the real challenge will not be balancing automation and oversight but deciding what should never be automated. We will automate the invisible work that drains clinicians and revenue teams while preserving human judgment for ambiguity, ethics, and accountability. The systems that succeed will treat AI as infrastructure and people as the stewards of trust.
Edward Peterson. Vice President, IT, Mount Sinai Health System (New York City, NY): In 2026, Mount Sinai AI governance plans to balance automation and human oversight in revenue cycle management (RCM) and clinical documentation by increasing the leveraging of agentic automation since itremains under human governance.
For 2026, we are increasing in the following areas:
Front-End Automation: in real-time insurance eligibility verification, patient registration, and cost estimation to prevent front-end denials.
Autonomous Coding: Over 30% of U.S. healthcare organizations are moving toward fully autonomous coding for routine cases, enabling end-to-end workflows without initial human intervention.
Ambient Documentation: AI “scribes” and ambient listening tools have become ubiquitous, capturing clinical notes in real-time to reduce the manual documentation burden on clinicians by up to 30%.
While AI handles routine execution, human expertise is concentrated on high-value judgment and complex exceptions.
Exception Management: RCM teams are shifting their focus from “chasing every code” to “defending every code,” managing only the complex cases or high-risk claims flagged by AI.
Audit and Compliance: Human-in-the-loop (HITL) models are essential for high-risk decisions. AI provides “explainable” evidence linking diagnoses to clinical documentation, which human auditors then validate to ensure regulatory compliance.
Governance Committees: Organizations are establishing cross-functional AI governance committees (clinical, IT, legal) to monitor algorithmic bias, drift, and the ethical use of automated systems.
To maintain this balance, healthcare systems are relentlessly monitoring key performance indicators (KPIs) through real-time dashboards:
- First-Pass Resolution Rate: Aiming for > 90%.
- Net Collection Rate: Targeting > 95%.
- Denial Rate: Kept below 5% through proactive AI flagging.
- Days in Accounts Receivable (A/R): Target of <35 days.
Zafar Chaudry, MD. Senior Vice President, Chief Digital Officer and Chief AI and Information Officer, Seattle Children’s (Seattle, WA): Seattle Children’s Hospital balances automation with human oversight by adopting a “human-in-the-loop” model that utilizes AI to reduce administrative burnout without delegating final medical or financial authority to machines. For clinical documentation, the hospital has scaled its partnership with Abridge enterprise-wide, using ambient AI to capture complex multi-caregiver conversations into structured notes, while requiring clinicians to review and sign off on every AI-generated draft.
AI agents like the Pathway Assistant (built on Google’s Gemini) and predictive denial tools streamline high-volume tasks such as medical necessity checks and code selection, yet complex cases and adverse billing decisions remain under the jurisdiction of human experts. AI handles the “administrative tax,” and humans maintain ultimate accountability for patient safety, health equity, and clinical accuracy.
Amber Imboden. Director, Revenue Integrity, Johns Hopkins Medicine (Baltimore, MA): In 2026, we will use automation as the first line of defense, leveraging Epic and AI-enabled tools to proactively identify things like missing charges, documentation gaps, and charge related compliance risks before billing. Human oversight will focus on reviewing exceptions, applying clinical and regulatory judgment, and partnering with the system on workflow improvement. This balance allows us to scale accuracy and consistency while ensuring clinical intent, compliance, and revenue integrity are maintained.
Shannon Cameron. Chief Operating Officer, Revenue Cycle, AFS of Harvard Medical Faculty Physicians (Boston, MA): In 2026, our approach to revenue cycle and clinical documentation is intentionally human-led, with automation serving as a support layer-not a replacement. Automation is applied to high-volume, rules-based tasks such as data normalization, charge capture checks, eligibility verification, claim edits, and trend identification. This reduces administrative friction and surfaces risk early, but it does not replace professional judgment or decision-making authority.
Clinical documentation integrity, coding accuracy, compliance interpretation, provider query management, and final financial accountability remain firmly in human hands. We operate with a required human-in-the-loop model where experienced coding, compliance, and revenue cycle professionals review exceptions, validate automation outputs, and make final determinations, particularly for complex, high-risk, or high-dollar encounters. Automation flags, prioritizes, and informs; humans decide, correct, educate, and defend. This balance ensures regulatory compliance, preserves clinical intent, and protects organizational trust while using technology to make human expertise more effective.
Racheal Hernandez. Director, Operations, Rush University Medical Center (Chicago, IL): In 2026, our system balances automation and human oversight by eliminating variation as early as possible before it turns into clinical disruption or patient harm. Some organizations, like Mayo Clinic, have chosen to step away from certain Medicare Advantage contracts rather than absorb the burden of prior authorization delays, but most health systems don’t have that level of leverage.
Instead, they are using automation to enforce front-end rules like eligibility validation, authorization checks, and referral logic so clinicians and patients aren’t blindsided on the day of care. These hard stops are often more humane than downstream denials, reducing anxiety for everyone involved, including patients who are gowned up in pre-op only to learn their surgery isn’t approved. Clinical technology then connects the dots in real time, helping clinicians navigate referrals, documentation, and resources so care decisions align with both outcomes and coverage in a constantly changing system.
Robert V. Boos. Vice President, Chief Revenue Officer, Centra (Lynchburg, VA): In 2026, the balance is intentional: automation handles scale and consistency, while humans focus on judgment and accountability. We’re using automation and AI to eliminate manual friction, surface risk, and perform 100% real-time quality checks in areas like registration and documentation, rather than relying on retrospective sampling.
Human teams then operate at the top of their license, reviewing exceptions, resolving complex cases, and partnering with clinicians on documentation accuracy. The goal isn’t fewer people; it’s better outcomes, lower denial risk, and tighter alignment between clinical intent and reimbursement integrity.
Beth Carlson. Chief Revenue Cycle Officer, WVU Health System (Morgantown, WV): Our team is leading a workforce transformation initiative designed to intentionally integrate technology and talent into a single workforce optimization model. The program reskills and upskills employees through competency-based career mapping, clearly defined job family pathways, and modernized roles and job descriptions, strategically evolving human expertise alongside new technical capabilities – even those we have yet to imagine or fully comprehend. By enabling talent redeployment and establishing growth pathways that advance critical skillsets, the initiative builds a workforce equipped to drive the revenue cycle of the future where oversight, expertise, and decision-making matter most.
Deepti Pandita, MD. Chief Medical Informatics Officer, Vice President, Clinical Informatics and Associate Professor, Medicine, University of California Irvine Health (Orange, CA): We are already leveraging AI to automate various back-office revenue cycle functions, including appeals and denials and claims processing. Our plan is to expand this AI footprint further in 2026 to enhance efficiency and accuracy. On the clinical documentation front, we are committed to growing our AI-driven ambient documentation across the entire enterprise, including our trainees. This integration will enable our professionals to focus on the more complex and nuanced aspects that require human judgment and expertise.
By combining advanced automated systems with human oversight, we aim to achieve greater accuracy, efficiency, and consistency while maintaining a personalized approach to patient care. Striking the right balance and continuously adapting to the evolving healthcare technology landscape is essential.
Parag Jain. Director, Clinical Research, Children’s Health and University of Texas Southwestern Medical School (Dallas, TX): In 2026, our approach to balancing automation and human oversight in revenue cycle and clinical documentation will center on augmented intelligence paired with adaptive oversightrather than full automation. We’re investing in AI-driven platforms that not only streamline revenue cycle tasks but also learn from clinician feedback to continuously improve accuracy. Looking ahead, we envision integrating predictive analytics and natural language processing to proactively identify documentation gaps and optimize workflows before issues arise. This approach ensures efficiency while maintaining human judgment for complex decisions, creating a dynamic system that evolves with patient and regulatory needs.
John W. Gachago. Vice President, Digital Innovation, Parrish Healthcare (Titusville, FL): At PHC, our 2026 digital transformation balances automation with human oversight by using AI to handle high‑volume, rules‑based revenue cycle and documentation tasks—such as coding suggestions, claim scrubbers and documentation prompts—while clinicians and revenue integrity teams retain final accountability. We are designing “human‑in‑the‑loop” workflows so automation accelerates throughput and accuracy without obscuring clinical judgment or compliance. Governance, transparency and continuous monitoring are core, with performance, bias and risk metrics reviewed alongside financial and clinical outcomes. Ultimately, automation at PHC serves as an augmentation layer—freeing caregivers and staff to focus on complex decision‑making, patient engagement and value‑based care outcomes.
Muhammad Siddiqui. Chief Information Officer, Reid Health (Richmond, IN): In 2026, we strike the balance between automation and human oversight by being clear about roles. AI takes on the repetitive, high-volume tasks like ambient note capture, charge suggestions, and task routing in documentation and the revenue cycle.
Clinicians and revenue leaders stay responsible for judgment calls, exceptions, and final sign-off. We make this work by setting clear guardrails, tracking with audit trails, and measuring outcomes based on time saved, adoption, and financial impact.
Philip Bernard, MD, Senior Vice President and Chief Medical Information Officer, Children’s Health
We will be leveraging LLMs and agentic agents throughout the revenue cycle. Particularly exciting is the work being done in clinical documentation. It is essential to keep the “human in the middle” as the ultimate oversight of these workflows. As many of our people shift their emphasis from “creators” to “editors”, we will need to develop the agents to maximize this new skill set.
Charleen Singh, PhD. Program Director, DNP-FNP Program, University of California, Davis Betty Irene Moore School of Nursing (Sacramento, CA): Currently there are lost opportunities in clinical documentation, not just from a revenue perspective but also the inaccurate reflection of the humanity that goes into each patient interaction. There is an opportunity for an AI system to support documentation of interactions related to emotional support that would otherwise not be documented by a provider because it may not seem important. Ultimately the clinician can review the documentation, edit and then sign the note.
David Blahnik. Vice President, Information Services, Northwestern Medicine (Chicago, IL): Our approach in 2026 will center on a hybrid model that leverages automation to make our staff more efficient while maintaining human oversight for accuracy and more complex tasks. Our intent is for our AI tools to handle repetitive tasks to reduce administrative burden and accelerate workflows. At the same time, clinical and revenue cycle experts will oversee complex cases, ensure compliance, and apply judgment where nuance is critical. This balance allows us to improve speed and scalability without compromising quality or patient trust.
Bob Berbeco. Chief Information Officer, Mahaska Health (Oskaloosa, IA): In 2026, we will balance automation and human oversight strategically by taking a foundation-first approach that validates clinical and financial data at the source, maps Epic data lineage end to end, and then moves trusted data into our Lakehouse for analytics and machine learning. Tactically we will apply a human-in-the-loop framework in which AI drafts, recommends, and prioritizes work, while team members, clinicians, and leaders retain decision rights. These processes will be well documented, with clear roles, training, and feedback loops.
For clinical documentation, ambient AI will generate a first-draft note to reduce after-hours charting, but clinicians will remain the final editors and signers. For revenue cycle, AI copilots will support denial prediction and appeal drafting, but revenue cycle leaders will own the process, and humans will review and approve actions before submission.
Yasir Tarabichi, MD. MetroHealth System (Cleveland, OH): At MetroHealth, we are using Pieces to augment clinical and revenue cycle work, not replace it.
In 2026, automation is focused on information retrieval, chart summarization, and documentation support, while humans remain accountable for final decisions. Notes are suggested and reviewed by clinicians before sign-off. On the revenue cycle side, automation improves upstream documentation quality and utilization review, with clear escalation paths for ambiguity or higher-risk scenarios rather than auto-submission.
To manage generative AI risk, we deployed this technology deliberately in phases, starting with a small, highly engaged user group focused on oversight, feedback, and data collection, then scaling with stronger education and end-user monitoring as adoption grew. Throughout, we are committed to monitoring and mitigating risk in ways that protect patients and clinicians without slowing meaningful progress.
Nariman Heshmati, MD. Chief Physician and Operations Executive, Lee Physician Group, Lee Health (Fort Myers, FL): There are many routine processes in revenue cycle and clinical documentation that can automated. In fact, whether performed by a human or machine, they are automated by protocols—either efficiently or inefficiently. On the other hand, human oversight is still necessary to develop those protocols and make final determinations. For instance, an automated AI solution could analyze physician coding patterns and identify potential outliers. However, you still need human clinical expertise and oversight to determine if those outliers are appropriate or not. We are at a stage in healthcare where technology has advanced significantly and can augment our capabilities, but it is not replacing them on a practical scalable level.
Ashwin Singh. Vice President, Revenue Cycle Management, Jackson Health System (Alpharetta, Georgia): In 2026, my approach will continue to use automation as a force multiplier to augment output. Advanced AI and rules-based engines will provide prioritization for high-value work while harnessing human skills and maximizing results. While humans retain decision rights on exceptions, clinical nuance, and financial risk thresholds, designing systems with embedded human-in-the-loop controls will be the key.
Christopher Horvat, MD. Senior Director, Clinical Informatics, UPMC (Pittsburgh, PA): Quality stays non-negotiable. Automation solutions are only adopted when they clearly reduce clinician burden while preserving or improving accuracy for patient care and revenue integrity. Any solution must deploy cleanly, be easy to maintain, and fit real clinical workflows, with the full set of tradeoffs weighed deliberately and patient care impact carrying the most weight.
Ilham Atir. Director, Clinical Laboratory Services, Bergen New Bridge Medical Center (Paramus, NJ): Our system balances automation and human oversight by utilizing AI as a high-efficiency engine for routine data capture and coding, while positioning our human experts as the essential layer of clinical governance. We are shifting toward an exception-based model where technology handles high-volume administrative tasks, liberating our clinical and financial teams to focus their expertise on complex, high-acuity cases that require nuanced judgment. This synergy ensures we capture the speed of digital transformation without sacrificing the clinical integrity and personal touch that define quality care.
Greg Thompson. Chief Information Security Officer, VHC Health (Arlington, VA): In 2026, I rely on automation to handle high-volume, repeatable work so teams can focus on judgment, exceptions, and outcomes that truly matter. Automation surfaces issues early, recommends actions, and reduces manual rework, but final decisions remain with people when financial, operational, or safety risk is involved. Clear escalation paths and audit trails ensure transparency and accountability, not blind trust in systems. Human oversight remains essential for nuance, context, and regulatory interpretation that automation cannot reliably assess. The balance is speed and consistency from technology, paired with experience and accountability from people.
Ije Akunyili, MD. Chief Medical Officer; Clinical Associate Professor, Emergency Medicine, Jersey City Medical Center, RWJBarnabas Health, New Jersey Medical School (New Brunswick, NJ): At Jersey City Medical Center, a RWJBarnabas Health Hospital, our approach to automation is grounded in high-reliability principles, where safety, accountability, and clinical judgment guide how technology is used. As we look to 2026, automation in revenue cycle and clinical documentation is applied to standardize routine processes and surface potential issues early, with clear expectations for human review, escalation, and decision-making. Clinical leadership retains responsibility for governance and oversight, ensuring documentation integrity, compliance, and patient safety remain central as automation supports—not replaces—the work of our teams.
Pamela J. Gallagher. Chief Financial Officer, Catawba Valley Medical Center (Hickory, NC): We are being thoughtful about how we use automation, understanding that it will impact our workforce. As labor markets tighten and downward revenue pressures increase, our focus is on using automation to streamline administrative and documentation tasks so revenue cycle and clinical staff can devote more time to work that truly requires professional judgment and expertise—not simply being asked to do more with less. Any automation (or AI) tools we pursue will be paired with appropriate human oversight and designed to support productivity, compliance, and high-quality patient care.
Karen Walker. Enterprise Director, Cardiovascular Services, Santa Clara Valley Hospitals (San Jose, CA): By 2026, our healthcare system will embrace a hybrid model where AI handles routine billing tasks while clinical experts focus on complex cases requiring nuanced judgment. We’re investing in natural language processing that can accurately extract billable elements from notes while maintaining physician reviewers who ensure medical necessity criteria are properly applied.
The future isn’t about replacing humans but amplifying their capabilities—imagine clinical documentation specialists freed from mundane coding to instead focus on physician education and quality improvement initiatives. Patient financial experiences will be transformed through automation that personalizes payment options, while preserving human financial counselors for situations requiring empathy and creative problem-solving. Revenue integrity will benefit from continuous AI monitoring that flags potential compliance issues in real-time, paired with experienced auditors who provide contextual understanding that algorithms still struggle to capture.
Our framework ensures technology decisions always prioritize both operational efficiency and the preservation of clinical judgment, recognizing that the best healthcare remains deeply human at its core.
Russell Horton, DO. Division Medical Director, BMG Primary Care, Banner Health (Phoenix, AZ): The balance of automation to human oversight will be as critical in the new age of AI as policies around security and clinical safety. Healthcare is a human driven industry and always will be. That said, we are seeing that keeping enough humans on staff to complete the ever-growing number of tasks is becoming unsustainable. Therefore, we will need to automate anything possible to allow humans a final say and the ability to work at the top of their license. Avoiding the temptation to simply insert AI into every part of healthcare will be difficult, but compassion, common sense, clinical judgement will always need a human touch.
Cheristi Cognetta-Rieke. Vice Chair Nursing, Enterprise Transformation, Mayo Clinic (Rochester, MN): In 2026, we balance automation and human oversight by using AI and ambient technologies to handle routine administrative and documentation tasks, while nurses retain authority over clinical judgment and patient relationships.
Rather than layering disconnected tools onto already complex workflows, our for nurses, by nurses™ model positions nurses as designers and co-creators of digital workflows rather than end-users ensuring that automation addresses real clinical pain points at the point of care. This approach requires rethinking how decisions are made and how technology is embedded, with nurses shaping what is automated, what requires human review and how success is defined. By shifting time away from screens and keyboards toward conversation, assessment and systems thinking, technology becomes an enabler of patient-and-family-centered care, reduced administrative burden and sustained adoption of digital tools.
Lisa Stephenson. Chief Nursing Informatics Officer, Cedars-Sinai Health System (Los Angeles, CA): At Cedars-Sinai, we have established a robust AI governance framework to support innovative solutions while safeguarding patient care. All AI initiatives undergo thorough vetting and review by senior leadership and our AI Council and commensurate with their unique risk level. A key factor is the degree of automation and its direct impact on patients.
- Administrative automation (e.g., revenue cycle) typically requires less continuous human oversight but is subject to rigorous validation and ongoing monitoring for accuracy.
- Clinical automation requires direct human oversight. For example, Cedars-Sinai nurses review all documentation generated by a voice-driven assistant before accepting and submitting. Similarly, clinical AI summaries in the EHR undergo extensive validation and piloting before broader rollout and include in-the-moment verification links.
Solutions with direct human oversight can be piloted more rapidly as part of validation. However, those without such oversight require more comprehensive model evaluation and upfront validation from our Cedars-Sinai experts.
Scott Schwab. Chief Financial Officer and Chief Operating Officer, Hillsboro Medical Center(Portland, OR): Hillsboro Medical Center looks at automation in any area to augment our team, not replace them. In 2026, we will continue to use automation in strategic areas to allow our teams to spend more time on higher-value activities as opposed to a replacement for human oversight.
For revenue cycle and clinical documentation, the human aspect is even more important for several reasons. First and foremost, technology cannot replace clinical judgement, and many revenue cycle activities are driven by clinical documentation and require input from the care team.
Second, any issues discovered in these areas need to be communicated and remediated as far upstream as possible to avoid recurrence. Most automation at this stage is not sophisticated enough to properly identify root causes, let alone craft solutions and communicate with the appropriate owner.
Lastly, payor policies and criteria are constantly changing, requiring providers to be nimble and responsive to avoid denials piling up, impacting reimbursements. Agentic artificial intelligence holds promise to help in this area and will be needed as the payors increase their technological investments, but human oversight will continue to be needed for these agents. At the end of the day, health care is and will remain a business with people at its heart, and no two patients are the same.
James Matera, DO. Senior Vice President, Medical Affairs and Chief Medical Officer, CentraState Medical Center (Freehold, NJ): When faced with balancing the human factor and AI in revenue cycle and documentation, healthcare must face some significant questions. Whatever the platform may be, we must have closed loop learning and oversight to ensure accountability and avoid roadblocks. When looking specifically at documentation, I feel we need to avoid the significantly bloated chart with little, if any clinical information that is valid.
I think human led, implementation of AI support systems is a must, where humans make the decision but is fully supported by AI. This is important for medical decision making but keeps the clinician as the accountable person. There are multiple platforms out there that can help this, and careful choice of which one works will determine the success or failure, which must be individualized to each facility.
Manny Rodriguez. Chief Marketing, Experience and Customer Officer, UCHealth(Cincinnati, OH): At UCHealth, we see automation as a force multiplier, not a replacement for human judgment. In 2026, we are intentionally deploying AI and automation to handle high-volume, low-variability tasks in revenue cycle and clinical documentation, while reserving human expertise for complex, nuanced, and patient-impacting decisions.
Our revenue teams use automation to match authorized and billed CPT codes, scan documents into electronic records and support documentation accuracy. Our caregivers leverage AI tools for clinical documentation to maximize their face-to-face interactions with patients during appointments, enhancing the patient experience.
Tony Sillemon, PsyD. Director, Community Health, Alta Bates Summit Medical Center, Sutter Health (Sacramento, CA): In 2026, we are using automation to support safety-net and community-based care, not replace the human relationships that are essential to it. Automation will reduce administrative burden in revenue cycle and clinical documentation such as eligibility verification, coding support, and prior authorization workflows while human oversight remains central to clinical judgment, accuracy, and advocacy for patients with complex social and medical needs.
This balance helps prevent automation from creating new access barriers, ensures fair reimbursement for care delivered in high-need settings, and allows frontline teams to focus on trust, continuity, and health equity.
Salim Saiyed, MD. Chief Medical Informatics Officer, Dell Medical School, The University of Texas at Austin (Austin, TX): At UT’s Medical center we take a balanced approach to automate across the revenue cycle and clinical documentation. We are focused on leading with automation that streamline routine tasks and reduce administrative burden, with equal committed to maintaining strong clinical oversight to ensure accuracy, context, and physician judgment remain central to patient care. To support this, we are equipping our clinicians with robust training and intuitive tools that elevate their ability to review, validate, and optimize AI‑supported documentation with evidence. This human‑in‑the‑loop model reinforces our core belief that technology should enhance — not replace — clinical expertise.
Laren Tan, MD. Chief Operating Officer, Loma Linda University Faculty Medical Group (Loma Linda, CA): The question we are really trying to solve is not how to automate healthcare, but how to restore human energy to it. Automation in 2026 must exist to remove the noise of documentation burden, revenue cycle friction, and administrative waste that pulls clinicians away from patients. As I was driving my kids to school and thinking about how to answer this question, it struck me that consumers now experience automation firsthand through self-driving cars, and healthcare is entering a similar era where automation becomes visible, felt, and personal. Our responsibility is to ensure it never replaces human judgment, compassion, or accountability. We will use automation to handle repetitive, rules-based work, while clinicians and revenue leaders remain firmly in the loop for decisions, ethics, and oversight. I dream of a system where the noise is quieted, clinicians are present, integrity is upheld, and patients experience care that is deeply and unmistakably human.
Stephanie Marszalek. Director, Nursing Informatics and Decision Support, UI Health (Chicago, IL): It is incredibly important to reinforce the concepts of human-in-the-loop. We need our clinicians to understand that they are integral contributors to workflows, even when they are automated. Their insight and critical thinking skills are necessary to monitor and oversee automated output to ensure it is relevant and accurate in order to mitigate errors and bias.
Srinath Adusumalli, MD. Vice President and Chief Health Information Officer, University of Pennsylvania Health System (Philadelphia, PA): In 2026, we balance automation by ensuring AI serves as a copilot and partner rather than an autopilot, particularly as tasks shift closer to areas that touch our patients directly. While AI, for example, handles the heavy lifting of drafting notes, we have embedded intentional ‘speedbumps’—forced pauses at critical decision points—to mitigate automation bias and ensure clinicians remain actively engaged in the process of collaborating with AI. This still functions to decompress cognitive load on our clinical teams, allowing them to focus even more sharply on human activities such as relationship building, judgment, reasoning, shared decision-making, and counseling. As systems move more toward a ‘human-on-the-loop’ model with more automation, this necessitates a new architecture of continuous monitoring to maintain the integrity of documentation and other processes. By prioritizing these safety mechanisms, we ensure that we also prioritize clinical accuracy and that patient safety remains uncompromised.
Rick Leesmann. Chief Information Officer and Chief Information Security Officer, Sky Lakes Medical Center (Klamath Falls, OR): The balance lies in freeing staff to do the work they love: caring for our patients. Automating claim status checks and prior auth workflows will allow our revenue cycle teams to focus on resolving complex cases and supporting patients through challenging financial processes. Letting ambient tools assist with documentation will mean providers can spend more time with their patients instead of on clinical documentation.
In the end, technology should support and enhance human connection and judgment, not replace them. Treat system or process overrides as data, not failure. If staff are consistently correcting or bypassing automation, that is a flare being sent up to improve the model, adjust workflows, or reset guardrails. In 2026, the goal is not replacing people. It is building systems that continuously learn from them, with clear human accountability for outcomes and a continuously intentional focus on improving the consumer experience.
Mohamed Rami Nakeshbandi, MD. Vice President and Chief Medical Officer, Downstate Health Sciences University (Brooklyn, NY): I focus most closely on sustained, voluntary adoption of digital tools within daily clinical workflows. When clinicians continue using a tool because it saves time and reduces friction—rather than because it’s mandated—we know behavior has truly changed. We measure this throughout sustained use within the clinical workflow and direct clinician feedback and then validate impact through downstream signals such as reduced unwarranted variation and improvements in quality and safety outcomes. When technology consistently returns time to clinicians and standardizes care, we know our digital investments are working.
Artimisha Curl, MAED. Director, Diversity, Equity, Inclusion and Belonging, El Camino Health (Mountain View, CA): The metric I watch most closely is sustained behavior adoption rather than simple utilization. I look for leading indicators such as consistent engagement trends, workflow integration, and frontline feedback, paired with lagging outcomes like retention, engagement scores, and patient experience measures. When digital investments are truly effective, they reduce friction, build confidence, and show up in how work is done, not just how often a tool is accessed. When technology drives clarity, connection, and trust at the front line, the data consistently reflects that impact.
Romila Aloysius. Assistant Vice President, Heart and Vascular Institute, AdventHealth (Altamonte Springs, FL): In 2026, the balance between automation and human oversight in revenue cycle and clinical documentation will hinge on shifting from retrospective pay-and-chase models to pre-pay clinical validation rooted in high-quality documentation. As payors deploy more sophisticated real-time adjudication and anomaly detection, providers must build business model flexibility and develop their own technological capabilities, particularly in friction-heavy areas like prior authorization and coding. Revenue cycle complexity has moved upstream, making completeness, clinical appropriateness, and accuracy at intake essential to reducing denials, shortening cycle times, and lowering total cost.
AI agents will increasingly automate routine workflows and straightforward cases, while human expertise is reserved for clinical judgment, exception management, and complex decision-making. The winners will be organizations that use automation not just to cut administrative expenses, but to unlock revenue through faster intake, cleaner claims, and payor-ready submissions that succeed at machine speed. Ultimately, organizations that combine intelligent automation with specialty centers of excellence that deliver superior outcomes and total cost of care, and are consistently chosen by consumers, will be the hardest, if not impossible, for payors to bypass.
Keisha Downes. Vice President, Mid-Revenue Cycle, Beth Israel Lahey Health (Cambridge, MA): In 2026, our approach centers on isolating tasks that are high volume, low skill to delegate to automation like RPA and AI, while preserving human oversight for complex cases requiring clinical judgment, payer negotiation nuance, and ethical accountability. We are establishing rigorous AI governance structures that require transparency in algorithmic decision-making and continuous monitoring of performance metrics to ensure accuracy, equity, and compliance.
The goal isn’t simply efficiency; it’s creating capacity for our teams to focus on higher-value work like interpretation of the nuances in ambiguous guidelines, denial prevention, quality metric optimization, physician education, and capturing the full clinical story. The real opportunity in 2026 isn’t choosing between humans and machines, but in designing intelligent workflows that leverage both to their fullest potential. Health systems that get this balance right will see not only operational efficiency but also workforce transformation that elevates the strategic role of revenue cycle and CDI teams.
Joshua Rivera. Pathology Business Operations Director, Moffitt Cancer Center (Tampa, FL): In 2026, our approach to automation in revenue cycle and clinical documentation, as it relates to Pathology and the Laboratory, focuses on improving accuracy and reducing administrative burden while maintaining strong human oversight. We continue to implement AI‑supported tools to streamline coding, prior authorization, denial and appeal management, and documentation workflows. All the while we are pairing these capabilities with clear governance structures across multi-functional teams, to ensure clinical and operational accountability.
Our goal is to let automation handle repetitive tasks so teams can devote more time to complex decisions, patient needs, and quality improvement. This balance helps us advance efficiency without compromising clinical integrity.
Evan Lyons. Vice President, Digital Information Services and Chief Information Officer, Peterborough Regional Health Centre (Peterborough, Ontario): In 2026, PRHC will balance automation and human oversight by focusing on agentic AI solutions that streamline documentation and revenue‑cycle workflows while keeping clinicians firmly in control of final decisions. Our modernization of core infrastructure through Microsoft AVS/AVD provides the secure, scalable foundation needed to safely operationalize these capabilities across the enterprise.
On the clinical side, we are introducing AI documentation copilots and scribe tools to ease documentation load, but their use is governed by PRHC’s principles of safety, transparency, and compliance, ensuring they support rather than replace clinical judgment. With Microsoft Fabric, we’re unifying clinical, financial, and operational data to ensure that any automated recommendation is transparent, governed, and backed by trusted information. Together, these investments allow us to automate the right tasks to reduce burden and improve throughput while reinforcing human oversight where judgment and nuance are essential.
At the Becker's 11th Annual IT + Revenue Cycle Conference: The Future of AI & Digital Health, taking place September 14–17 in Chicago, healthcare executives and digital leaders from across the country will come together to explore how AI, interoperability, cybersecurity, and revenue cycle innovation are transforming care delivery, strengthening financial performance, and driving the next era of digital health. Apply for complimentary registration now.