Behind every therapy session and care plan, there’s an entire system working to make sure clients get the best possible support. It’s not just therapists or administrators that make good care happen—it’s also tools, processes, and standards bringing it all together and ensuring services are accessible and impactful to clients.

Accreditation is one of the less-glamorous ways behavioral health organizations are held accountable to high care standards. And now that AI is here, accrediting bodies must consider its effect on organizations’ ability to meet those expectations.

In this episode of No Notes, Dr. Denny Morrison sits down with Mike Johnson, Senior Managing Director of Behavioral Health at the Commission on Accreditation of Rehabilitation Facilities (CARF), to explore the many ways AI is impacting behavioral healthcare. They chat about the potential for AI to enhance clinical workflows and simplify documentation—ultimately helping organizations deliver better care while staying true to accreditation standards.

Read on to learn about the emerging role of AI in the care process—and how it helps more people receive higher-quality therapy services.

Want to listen to the AI and accreditation podcast in full? Check it out here.

What is CARF?

CARF accredits organizations in a variety of fields, including behavioral health, medical rehabilitation, child and youth services, and aging services. Behavioral health is CARF’s largest accreditation area.

CARF’s mission is to “promote the quality, value, and optimal outcomes of services.” As Johnson explained, “Our purpose is to ensure quality for the individual.” But for behavioral health organizations, accreditation isn’t just a certificate on the wall. “It’s an internal quality improvement activity that’s systematic and based on a set of standards that are field-tested and are the best processes for the field,” Johnson continued.

In his role as Senior Managing Director of Behavioral Health, Mike plays a key role in shaping these standards. “I’m the one responsible for writing all the standards in the behavioral health manual,” he said. Beyond that, he acts as “the interface between [CARF] as an organization and the field,” gathering feedback from providers, regulators, and clients to ensure CARF’s standards stay relevant and helpful.

The accreditation process pushes organizations to look at their internal processes and make improvements that drive better care outcomes. “The work that an organization goes through [during accreditation] is what’s important,” Johnson emphasized. It ensures care is consistent and that “things aren’t falling through the cracks.” Essentially, accreditation helps organizations provide the highest possible quality of care to those they serve.

AI and CARF Accreditation

CARF doesn’t restrict organizations from using AI to support care, as long as that usage is consistent with their mission of quality and accountability.

“We’ve never had standards that say the bulk of the note has to be formed by a sentient being,” Johnson said.

Instead, CARF cares about whether that documentation ultimately meets standards for quality and accuracy—regardless of who (or what) creates it.

AI tools like Eleos are helping organizations streamline required administrative work—by making the documentation process more efficient and accurate, for example. “Clinicians are going from session to session to session throughout the course of a day,” Johnson explained. “They’re not keeping up with their notes, and then a day or two—or even a week—later, they’re going back and writing a note.” This delay can lead to missing details or incomplete reflections of the client’s therapy experience. AI mitigates this problem by supporting real-time documentation, reducing errors, and making sure notes capture what actually happened in the session.

Even with AI’s assistance, though, the responsibility to submit accurate, complete, compliant documentation always stays with the clinician.

“The methodology that the organization uses, [or] the tool sets that they use to satisfy our standards—we don’t prescribe that,” Johnson said. And whether a provider uses an AI tool or not, it’s still up to them as human professionals to ensure their documentation meets CARF’s expectations.

Common Misconceptions About AI and CARF

There’s a lot of curiosity—and some confusion—about how AI fits into CARF’s accreditation process. Johnson addressed several common misconceptions to set the record straight.

Myth: CARF won’t allow AI-generated notes.

Reality: CARF has no issue with AI tools being used for documentation as long as the notes meet established standards for quality and accuracy. The methodology organizations use to comply with those standards isn’t prescribed; it’s the end result that matters.

Curious how AI helps providers write more compliant notes? See our compliant progress note examples here.

Myth: If AI makes a mistake, CARF will blame the AI.

Reality: Accountability always rests with the provider. “The organization—and the clinician—is responsible for that note,” Johnson emphasized.

Morrison agreed, adding, “If you have an autonomous bot, and it screws up—that’s not the bot’s fault. It’s the organization’s fault.”

At the end of the day, CARF’s standards are designed to ensure providers’ notes are up to par—regardless of the tools they use.

Myth: CARF will eventually accredit AI bots for clinical care.

Reality: CARF accredits human-driven care, not autonomous bots. AI can support clinicians by improving documentation or flagging risks, but Johnson emphasized that “the clinician remains responsible for interacting with that individual and ultimately making determinations.” CARF’s focus is maintaining high-quality care that is delivered by trained professionals, even when technology is part of the process.

AI’s Role in Behavioral Health

Specialized AI vendors are changing the face of behavioral health by building tools that not only support clinicians, but also align with existing quality standards—including those set forth by CARF. By improving documentation, detecting risks, and enhancing clinician workflows, AI helps organizations elevate the level of care delivered.

Where AI is Helping Clinicians Now

AI is already making an impact through tools like Eleos, which enable real-time, session-based documentation.

“The fact that we can have AI assisting the clinician in real time to keep up with those notes…we view that as something that has real value,” Johnson explained.

This reduces the incidence of “late notes” written from memory and helps providers complete their documentation accurately and promptly—key components of CARF’s standards.

AI also has the potential to help clinicians identify recurring risks. “There are a lot of individual cues that a person might present with that can be reflective of suicidal thinking that is completely missed by the clinician—because it happens over three or four or five sessions,” Johnson said. By identifying patterns like these as early as possible, AI tools like Eleos help clinicians provide more targeted and timely care.

Augmented vs. Artificial Intelligence

During their conversation on the podcast, Johnson and Morrison zeroed in on the difference between artificial intelligence and augmented intelligence. Artificial intelligence refers to fully autonomous systems, such as self-driving cars. Meanwhile, “augmented intelligence” is meant to support human professionals—including behavioral health providers—in the hard work they do. “It’s very challenging for somebody to be doing 7 or 8 hours a day of therapy…and be able to not miss things,” Johnson pointed out. However, augmented intelligence isn’t “self-driving”—it doesn’t replace clinical or professional judgment. The goal is to ease the cognitive burden on clinicians while keeping them in control of therapy sessions.

CARF’s approach to accreditation prioritizes accountability, quality, and the well-being of those receiving care. As AI becomes an integral part of the healthcare process, augmented intelligence tools like Eleos align with these values by supporting—not replacing—clinicians in the delivery of better, more efficient care.


The Bottom Line on CARF and AI

The final judgement: CARF doesn’t necessarily endorse the use of AI in behavioral health, but they also don’t oppose it. Instead, they focus on the end result: the quality of care delivered to each client. So, if your organization is thinking about implementing an AI tool, make sure it’s built to support quality behavioral healthcare—and ask the vendor if they can provide objective data that demonstrates a positive impact on client outcomes.

Ready to see how purpose-built AI is already helping behavioral health organizations across the country deliver higher-quality care? Request a demo of Eleos now.