How to Estimate the ROI of Agentic AI in Healthcare Call Centers

Healthcare organizations are increasingly investing in AI to improve efficiency and reduce operational strain. According to a 2024 MGMA Stat poll, 43% of medical groups have adopted or expanded their use of AI tools, nearly doubling the rate from 2023. The rise in adoption reflects a clear expectation for technology to deliver measurable value, not just innovation.

Agentic AI in healthcare are systems that can autonomously make decisions and take action. By automating routine and high‑volume patient interactions, agentic AI reduces staff workload, improves access, and supports more scalable operations. Before investing in agentic AI, providers should evaluate ROI, understand why it matters, and identify the best solutions to generate value.

Where is Agentic AI used in Healthcare Call Centers?

Agentic AI platforms help automate routine interactions such as appointment management, medical record requests, and routing clinical questions to the right team.

In a 2025 patient access survey completed in partnership with Becker’s Healthcare Review, 36% of healthcare leaders reported investments in AI. The rise in adoption reflects a clear expectation for technology to deliver measurable value, not just innovation.

The real question isn’t if agentic AI delivers value. It’s how much.

Example of Healthcare Call Center ROI:

Imagine a large healthcare organization handling 360,000 calls a year. If even a portion of those were routine appointment changes that an agentic AI platform could automate, the labor costs of managing them could easily reach hundreds of thousands of dollars annually.

Automating a majority of those calls could free the equivalent of four or more full-time positions without adding headcount.

Why Does ROI Matter in Healthcare Call Centers?

While efficiency is critical, investments in agentic AI also need to demonstrate measurable value. Understanding where agentic AI platforms deliver return through time saved per call, higher appointment capture rates, and reduced downstream work for staff is key to building a strong business case. When applied strategically, it becomes more than a workflow enhancement. It’s a lever for long-term cost reduction and improved access to care.

Agentic AI platforms automate live phone interactions by handling routine tasks like appointment management and basic requests without the need for staff to pick up the phone. In high-volume healthcare call centers, that can translate into meaningful time and cost savings.

Call centers play a vital role in patient access, but they’re also resource intensive. Long wait times, missed calls, and scheduling errors all carry a cost financially and operationally. And with staffing stretched thin, simply adding more agents isn’t always feasible.

Where do Agentic AI Platforms Deliver Cost Savings?

Dash Voice AI is a proven example of how agentic AI platforms outperform classic IVRs by understanding natural language, following intelligent scheduling logic, and completing tasks from start to finish rather than routing callers through rigid menus. In healthcare, the strongest solutions are built for patient access and can apply scheduling rules accurately while handling high-volume interactions with consistency. At Mississippi Sports Medicine & Orthopaedic Center (MSMOC), Dash Voice AI handles around 20% of their inbound call volume, primarily appointment confirmations, reschedules, and other routine requests that would otherwise burden call center staff.

Healthcare Example of Agentic AI Cost Savings:

A simple way to estimate call center ROI from agentic AI is with an ROI formula: (Automated Calls Per Year x Average Handle time x Hourly Staff Costs) = Annual Labor Savings

To illustrate the impact: In a healthcare call center that fields approximately 10,000 calls per month, automating 20% of those calls would remove 2,000 manual calls from staff workload.

In high-volume environments, the baseline cost of manually handling appointment changes can be substantial. For some organizations, the labor cost of these routine calls approaches $300,000 per year before any automation is introduced.

Here are four key areas where agentic AI platforms translate into meaningful cost savings:

1. Labor Efficiency: Offloading 2,000 calls per month, at an average handling time of 3 minutes per call, saves approximately 112 staff hours per month, more than 1,340 hours per year.
2. Scalability Without Added Headcount: As call volume grows due to patient demand, service expansion, or seasonal spikes, it absorbs the increase without the need for additional hires. The average annual base salary for a healthcare customer service representative is around $20.70 per hour, even a single full-time role can cost more than $43,000 annually.
3. Fewer Errors and Scheduling Mistakes: Automated workflows backed by an intelligent scheduling engine follow provider-specific rules and preferences, reducing errors that lead to no-shows, rework, or lost revenue.
4. Operational Continuity and Uptime: An agentic AI agent operates around the clock, helping maintain availability during staff shortages, call surges, or outages. That reliability ensures smoother patient access without additional staffing pressures or service delays.

How Do Healthcare Organizations Estimate Call Center ROI?

Agentic AI platforms can unlock measurable savings, and you don’t need a complex model to estimate the impact. Start with these three simple inputs:

1. Annual Call Volume: Consider the number of inbound calls your team handles each year, such as appointment management requests, running late notifications, and location or business hours inquiries, then identify which could be automated.
2. Time and Labor Savings: Multiply the automated calls by the average handle time to get total hours saved. Then multiply by your hourly staff costs.
3. Operational Impact: Consider indirect benefits such as reduced hold times, fewer errors, and higher patient satisfaction.

Healthcare Example of How to Estimate High-Volume Call Center ROI:

Imagine your organization receives 360,000 calls per year, and 30% of those (108,000 calls) are routine appointment changes averaging 8 minutes each. At an average staff cost of $20.70 an hour, that’s nearly $298,000 per year in labor just for this type of call handling.

If agentic AI agents automated 60% of them (about 64,800 calls annually), you would save roughly $178,848 in annual labor costs without reducing patient access or satisfaction.

Whether large or small, the formula stays the same but as call volume and automation rates rise, the ROI can grow dramatically.

Reclaiming Value Where It Counts

Agentic AI platforms like Dash Voice AI are no longer exploratory. They are becoming strategic investments that enable healthcare organizations to operate more efficiently without compromising patient access or experience. When implemented with the right foundation, it can deliver measurable cost savings, optimize staff capacity, and support long-term operational resilience.

The return goes beyond budget impact. It’s about building a more scalable, sustainable system for both your team and your patients.

Agentic AI has the power to transform operations in today’s healthcare call centers. By autonomously making decisions and taking action for routine tasks, agentic AI platforms can reduce staff burden and expand access to care. However, providers must be strategic in making choices and clearly evaluate return on investment—understanding the specific problems agentic AI is best suited to solve and align with operational and patient experience goals.

About Relatient

Relatient is a healthcare technology company dedicated to improving patient access through intelligent, mobile-first solutions. Dash® by Relatient is a Best in KLAS intelligent patient access platform that integrates with leading EHRs and PM systems to automate scheduling, streamline patient communication, online chat, mobile payments, and digital intake. Trusted by over 50,000 providers and managing approximately 150 million appointments annually, Relatient helps healthcare organizations optimize workflows, reduce no-shows, and enhance the patient experience with modern, consumer-driven solutions.