Last year, generative AI stole the show in healthcare with tools like ambient scribes that turned conversations into clinical notes and bots replying to MyChart messages. It was impressive progress but mostly assistive, not autonomous.
In 2025, the spotlight is on agentic AI. Unlike earlier tools that support or augment human workflows, agentic AI is built to act independently, completing tasks from start to finish with little or no human input. It represents a shift from assistive technology to autonomous systems.
According to CB Insights, AI agent startups raised $3.8 billion in 2024, nearly triple the amount from 2023. Every major tech company is either building AI agents or offering the infrastructure to support them. This surge of investment signals a ton of opportunity, and healthcare is right in the middle of it.
The push comes as hospitals look for new ways to cut costs and reduce staffing pressures without compromising service. Back-office operations, like revenue cycle management, have become a prime testing ground, with agentic AI beginning to automate everything from insurance verification to claims processing and appeals.
But the impact isn’t limited to behind-the-scenes tasks. Agentic AI is also gaining traction in patient-facing roles, where it’s starting to ease some of healthcare’s most common friction points, starting with the front desk.
Scheduling smarter with AI agents
One of the clearest signs that agentic AI has arrived is how it’s changing appointment scheduling—traditionally a manual, back-and-forth process involving long hold times or multiple phone calls. Now, AI agents are taking over that task from start to finish.
Companies like Hippocratic AI, Assort Health, and Innovaccer are building AI agents that do more than offer time slots. They’re reimagining how front-office healthcare works.
Hippocratic AI agents proactively reach out to patients who miss notifications about routine test results, like normal labs, and handle inbound calls with empathetic, first-ring support to answer basic patient questions.
Assort Health focuses on EHR integration, automating appointment scheduling, insurance updates, and patient data entry in real-time, closing the loop without staff intervention.
Innovaccer applies its AI to referral management, automating the entire workflow end-to-end, making sure patients get connected with the right specialists while reducing network leakage.
For patients, this means less friction. For healthcare providers, it means fewer no-shows, more accurate bookings, and better resource utilization.
Keeping tabs on patients outside care walls
The shift to value-based care means providers are increasingly responsible for what happens after the patient leaves the clinic. That’s where agentic AI is stepping in again. This time, as a kind of virtual case manager.
Sarah, an AI agent from Hippocratic, can ask assisted living patients about their day, organize menus and transport, and remind patients to take their medication. Another AI-powered agent, Rachel, conducts check-ins for patients with chronic kidney disease, helping identify and close gaps in care before they escalate.
The same kind of intelligent support is emerging in more acute settings. Innovaccer’s ED Follow-up Agent automates routine post-discharge check-ins, then coordinates the best time for a care manager to call, freeing up staff to focus on high-risk cases and helping hospitals reduce readmissions.
These systems don’t just send templated messages. They analyze responses, escalate issues when needed, and keep clinicians in the loop. For chronic care patients or those recovering from surgery, this kind of proactive engagement can catch complications early and lower the likelihood of rehospitalization, all without requiring hours of nurse outreach time.
Reimaging the revenue cycle with end-to-end AI automation
Few areas of healthcare are as complex or as costly as the revenue cycle. Verifying insurance, getting prior authorizations, submitting claims, handling denials: it’s a tangle. But increasingly, agentic AI is starting to own more of it.
Startups like Thoughtful AI and VoiceCare are pushing automation into revenue workflows. These solutions don’t just assist billing teams, they take on the full process, from eligibility checks and benefit verification to generating and submitting appeals when claims are denied.
For instance, VoiceCare AI’s agent, Joy, makes outbound calls to insurers for tasks like benefit verifications, prior authorizations, and claims follow-up—then reports back with call summaries. Mayo Clinic is already piloting it.
Thoughtful AI goes a bit further, offering real-time reporting on denial trends, coding accuracy, and workflow efficiency, so teams can fix systemic issues faster.
For providers, that translates to faster reimbursements, fewer billing errors, and less administrative burden on staff. And as these systems improve, they could help close a major efficiency gap that plagues the healthcare industry, one made worse by insurers’ increasing use of utilization management tools like prior authorizations.
Agentic AI in healthcare is still a work in progress
While the vision for agentic AI is ambitious, the reality is still in its early stages, especially in a high-stakes industry like healthcare. To ensure safety and compliance, most AI agents today operate within strict “guardrails.” These typically include predefined workflows, decision trees, and human-in-the-loop mechanisms that constrain what the agent can do. Rather than fully autonomous systems, they’re more like intelligent task runners: highly effective within specific tasks, but not yet capable of replacing human judgment.
For healthcare organizations, this makes early deployment more manageable but also underscores the importance of governance, oversight, and transparency in design. Still, for many healthcare organizations, AI is no longer an experimental add-on. It’s becoming part of the infrastructure.
See the signal in the noise
The promise of agentic AI isn’t just about cutting costs or streamlining administrative tasks. It’s also about improving the patient experience. As these tools mature, they have the potential to offer 24/7, personalized, and highly responsive support at scale. That could mean shorter wait times, quicker access, and smoother journeys through a complex system. But the real win? Letting human clinicians focus more on care and less on coordination.
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