6 ways AI will make virtual care more effective in 2026

Intake assessments

According to Caroline Goldzweig, M.D., chief medical officer of Cedars-Sinai Medical Network, one of the primary ways AI will impact virtual care is by making the patient intake process more efficient.

Cedars-Sinai's 24/7 virtual primary care clinic CS Connect is already leveraging AI to conduct intake assessments.

"When patients log into CS Connect, they put in their chief complaint or what they're coming there for," Goldzweig said. "And then there's an AI chat function that converses with the patient and essentially asks a bunch of questions. It has been trained on millions of patient records and creates, essentially, a history of present illness. And it gives the patient a sense of what may be going on."

Providers can access these assessments, giving them a picture of the patient's medical needs before they connect with the patient virtually. The AI-enabled summarization can help clinicians act more efficiently when diagnosing and creating a treatment plan for patients during telehealth visits, Goldzweig added.

Mass General Brigham's Vice President of Digital Patient Experience Raj Patel, M.D., echoed Goldzweig, noting that intake and pre-visit functions are a promising use case for AI tools in the virtual care arena, as these tools can help make provider-patient interactions more targeted and efficient.

"I think we're going to start to see, increasingly, [AI-based] triage, summarization, [treatment] plan proposal, with humans-in-the-loop on all of that stuff," he said. "And, more and more, semi-autonomy around it."

Ambient listening & video analysis

Ambient listening is undoubtedly one of the most popular applications of AI in healthcare.

"AI-assisted dictation software, such as Dax Copilot and the Doximity tools, is able to more quickly take what is happening in the patient interview and prepare an actionable note from it," said Joshua Jones, M.D., medical director-telepsychiatry at Providence Virtual Care and Digital Health. "I think that is becoming very standard throughout the industry and is well recognized."

Clinicians can benefit from ambient listening tools during virtual visits in the same ways that they do during in-person care, namely that the tools can help reduce clinician burnout and ease documentation burdens.

Jones expects to see these capabilities continue to evolve in 2026 to include AI-based identification tools that can pick up on non-verbal cues, including body posture, cadence and inflection of the speaker's voice to indicate differential diagnoses.

"I think that's going to be used throughout healthcare," Jones said. "It will especially be helpful in telepsychiatry and, I think, in tele-primary care."

Clinician co-pilot & treatment decision support

AI shows significant promise in offering clinical decision support at the point of virtual care.

According to Mass General Brigham's Patel, advancements in AI, including the emergence of agentic AI, could offer clinicians a tool to help fill gaps in patient care by providing reminders for orders or other types of follow-up care, ensuring clinicians close the loop on the cases they are handling.

"As we take care of the patientsthe co-pilot can help," he said. "It can ask, 'Hey, did you notice this lab? Did you see that the ENT wrote their note and suggested this thing? I'm not seeing it in the record yet."

Michael Dalton, CEO of virtual-first provider Ovatient, noted that EHR vendors are increasingly upgrading their solutions with AI, which will also have a positive impact on clinical decision-making in the virtual care setting.

For instance, AI is enabling providers to query a patient's medical record in the EHR, retrieving relevant information that can inform their treatment plan decisions. Providers can also share this data with patients to walk them through their treatment journey during virtual visits.

"I think that is going to be a game changer," Dalton said. "I like to say, virtual care is the great equalizer. I really think that AI becomes an even greater equalizer. You could say virtual care changed what the front door is for healthcare. It made it super accessible. I think AI changes what happens when you walk through the front door."

Predictive analytics

AI-based predictive analytics solutions have the potential to enhance virtual care, especially in the remote patient monitoring (RPM) arena.

For instance, Cedars-Sinai is currently piloting a predictive-modeling algorithm to manage congestive heart failure and ensure that patients receive guideline-directed medical therapies, Goldzweig shared. The AI algorithm ingests data from RPM devices and provides recommendations on medication adjustments.

Not only can AI-based predictive analytics be used in outpatient RPM programs, but they can also boost inpatient telecritical care and telehospitalist workflows by alerting virtual clinicians to patients who need attention in the inpatient setting, Providence's Jones added.

Furthermore, Madelyn Knowles, senior research manager at Rock Health Advisory, noted that AI-based predictive analytics can help health systems better understand various patient populations and their needs, thereby enabling more strategic implementation of virtual care initiatives, including hospital-at-home care.

"The organizations can get a broader perspective on how to target the right patient at the right time with the right intervention," Knowles said.

"AI integrated in remote patient monitoring solutions and hospital-at-home programs allows health systems to think about potential risk indicators and, therefore, coordinate more targeted engagement and follow-up," she continued.

Patient outreach & engagement

According to Oleg Bestsennyy, partner with the healthcare practice at McKinsey, integrating AI into virtual care can significantly improve how health systems reach and engage patients.  

The benefits of AI-based digital outreach are especially evident in chronic disease management.

"If you think about some diseases in particular that require a lot of wraparound care, for example, cardiometabolic conditions, where diet, nutrition and exercise are very important, it's not enough to have a once-a-month visit or even a once-a-week visit -- the behaviors have to change on a daily basis," Bestsennyy said.

"And this is where the greatest promise of AI, I think, lies, which is, how can you actually take this machine-to-human interaction to a much, much greater level and really break through this barrier of being able to change people's behaviors through daily constant nudges and become a trusted partner?" he continued.

Until now, encouraging patient behavior change has required significant staff involvement. But, with AI-enabled outreach and nudges, health systems can offset the costs typically involved and achieve greater levels of lifestyle intervention, Bestsennyy said.

Ovatient's Dalton further underscored that integrating AI agents into digital health tools can drive greater patient engagement. AI can be used to personalize content and outreach to patients, offering engagement opportunities that align with their needs.

"It could just be about health maintenance and reaching out and making sure that we're encouraging awareness, encouraging an explanation of the why, answering any questions, and then helping through that care navigation and scheduling to say, 'let's get you booked for that,'" he said.

This type of direct and continuous outreach can not only improve patient experience but also reduce unnecessary emergency department visits and hospitalizations, Cedars-Sinai's Goldzweig pointed out.

Personalized at-home care interventions

Advancements in digital healthcare are supporting increased access to care at home, and now, AI can help personalize these interventions to each patient, Rock Health's Knowles noted.

For example, AI can customize virtual physical therapy (PT) by offering patients real-time analytics and feedback. In virtual PT sessions, patients receive direction on exercises through synchronous or asynchronous telehealth. The addition of AI can help enhance both synchronous and asynchronous sessions by analyzing patients' body movements or postures and suggesting adjustments in real time, Knowles suggested.  

In fact, as AI becomes increasingly integrated into virtual PT and other digital health programs, it alleviates the need for synchronous telehealth services, which, in turn, can help support care access amid clinician shortages.

"I anticipate that we will just continue to see virtual care become more scalable, more touchpoints available via asynchronous means rather than being solely reliant or more centrally reliant on synchronous virtual care, more personalization, more things like real-time feedback and data integration, that sort of thing," Knowles said.

With AI's ability to make virtual care more efficient, improve patient outcomes and support clinician experience, there is no doubt that AI will continue to be integrated into virtual healthcare in 2026 and beyond. Health systems must ensure they are prepared for all the changes that rapid AI advancements will bring to reap the benefits while protecting themselves from AI risks.

Anuja Vaidya has covered the healthcare industry since 2012. She currently covers the virtual healthcare landscape, including telehealth, remote patient monitoring and digital therapeutics.