AI Will Not Save Your Call Center: Why the Future of DSOs is Hybrid

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For many DSO leaders, the math looks simple. Call centers are one of the largest operating expenses on the P&L. AI is everywhere, promising to automate conversations, reduce headcount, and keep patients happy at a fraction of the cost.

It is tempting to believe that AI can replace the call center entirely.

One CMO recently summarized what many CEOs and CFOs are thinking: if AI can take every call, book every appointment, and answer every question, why keep humans on the phones at all

As CEO of Reach, I have heard this myth more than once. In my conversations with DSOs and industry leaders, it has become clear to me that this belief is now one of the most dangerous assumptions in group dentistry. It ignores how patients actually behave, how revenue is really generated, and what AI is and is not good at today.

Ryan, CMO and COO at Mosaic and Peak Dental Services, sees the same pattern in his work.

“The biggest myth I see is the belief that AI will replace call center agents entirely. What AI actually replaces is inefficiency. It complements teams, not eliminates them.”

Amol, who builds AI solutions for dental organizations, is even more direct about the mindset behind that myth.

“If an executive sees the call center as just a cost line, it is a dead giveaway they are inexperienced or a deer in headlights leader who does not know the levers to pull to grow the business.”

This article is about what happens when that myth meets reality, and why the DSOs that win will not be the ones that automate everything, but the ones that design a thoughtful hybrid model where AI and humans work together.

The Real Cost of Cutting Humans and Where AI Actually Works

On paper, cutting headcount in the call center looks attractive. A DSO can take a large monthly expense and reduce it quickly. It is easy to point to a lower payroll number and call it efficiency.

I have seen the other side of that decision. In my experience, operators may save tens of thousands of dollars in staffing, yet quietly lose the equivalent of hundreds of new patients each month in missed opportunities and poor conversion. The loss rarely shows up as a neat line item. It appears in half filled schedules, inconsistent production, and marketing dollars that never turn into visits.

AI can absolutely help with parts of this equation. Online scheduling tools and AI chat are already booking patients directly into practice management systems. Ryan has seen these tools perform very well in the right context.

“We have already seen how online schedulers and AI chat can be extremely effective and even book directly into the PMS.”

Amol approaches the same topic through the lens of return on investment. As Amol sees it, the DSOs that win are the ones that treat the call center, especially when it is supported by AI, as an ROI engine rather than a cost center. In his view, a well run operation makes it possible to track the lift in revenue and to see clearly where additional investment stops creating meaningful return.

Viewed this way, the question is not “How do we spend less on the call center” but “Where does additional dollar stop producing meaningful return” and “Where does cutting too far start to destroy value”

That is where access and speed matter.

“Getting patients on the schedule is one of the most important revenue functions in the organization,” Amol notes. New patients will not wait thirty to sixty days to be seen. “If you cannot get them booked fast, they are gone.”

AI can be a powerful tool here, especially for capturing missed calls, handling after hours demand, and processing administrative noise that does not require judgment. Ryan has seen that when AI is implemented thoughtfully, it tends to pick up the work that does not require judgment.

The distinction is important. AI is very good at routing, triage, and simple transactional interactions. It is much less effective when a call is emotionally charged, medically complex, or requires negotiation and reassurance. Those are the conversations that usually determine whether a hesitant new patient books, whether a worried parent feels safe bringing a child in, and whether a frustrated person gives a practice another chance.

When DSOs treat the call center solely as a cost to be minimized, the first cuts typically remove the very people who handle those moments best. Short term savings then show up as long term leakage in revenue and loyalty.

The Human Layer: Empathy, Trust and the Front Door of Growth

To understand why humans still matter so much, it helps to zoom out beyond technology. I often think of research on early human societies that suggests survival did not belong to the strongest individual, but to the one who was most connected and trusted. Being liked, included, and supported by the group was a better survival strategy than brute strength.

In other words, we are wired for connection.

That basic truth still shapes how people behave as patients. When something routine happens, such as reordering a product, checking a simple balance, or confirming an appointment time, most people are comfortable with digital self service. This is why ordering paper towels from Amazon or confirming a delivery through a bot feels completely acceptable.

When something important is at stake, the expectation changes.

When an airline cancels my flight, I do not want to navigate an endless automated menu. I want a person who can listen, make tradeoffs, and solve the problem.

Dental care sits much closer to the airline example than the paper towels. Patients call when they are in pain, anxious about cost, unsure about treatment, or trying to coordinate care for their children. In those moments, a script is not enough. They listen for tone, patience, and empathy.

In my view, empathy is the competitive edge of a business going forward.

Ryan’s observation aligns strongly with that view.

“Humans will always want to talk to humans when they cannot get an immediate answer or simply prefer real interaction.”

The call center is where that preference is either respected or ignored. Amol describes it not as a back-office function, but as the real front door of the organization.

“Your call center is not a cost center, it is your front door, your growth engine, and can be a competitive advantage. And if it is truly a cost, you have the wrong leader or the wrong vendor.”

That front door is where empathy and access translate directly into growth. The question for DSOs is how to protect and scale that human layer while still taking advantage of what AI does well.

Designing The Hybrid Model: Lessons from the Field

In my view, the most important design decision is to stop framing the conversation as AI versus humans. The real opportunity is AI plus humans.

I have seen what happens when organizations chase automation first. Early in my career, I led one of the largest scheduling operations focused on dentistry, with hundreds of people responsible for managing patient calls. Some parts of that model were fragile and had to be rebuilt. The lesson for me was not that humans should be removed, but that structure, process, and discipline have to come before tooling.

Ryan captures a similar idea in a single sentence:

“The second myth is the idea that AI can fix a broken call center. It cannot. AI amplifies whatever is already in place, it does not fix bad scheduling templates, capacity constraints, or poor processes.”

AI will magnify whatever foundation it sits on. If templates, access, and capacity are broken, AI will simply make it faster and more visible. If the underlying operation is healthy, AI can remove friction and lift performance.

In a well-designed hybrid model, AI handles what it is truly good at. It can answer basic questions, confirm appointments, log simple requests, and route calls based on clear logic. It can work around the clock, handle after hours demand, and ensure that no call is completely lost without an attempted response.

Humans then focus on what only humans can do. They listen to nuance, understand emotion, and make judgment calls. They work with patients to find appointment times that match clinical reality and personal constraints. They de-escalate frustration and turn a potentially lost patient into a loyal advocate.

Ryan describes the practical effect this way:

“When deployed correctly, AI captures missed calls, handles after hours scheduling, clears out the administrative noise, freeing agents to focus on converting high value cases, solving patient issues, and driving revenue.”

Amol’s perspective adds a layer of leadership accountability to that design.

“The DSOs who win understand that a call center, especially one complemented by AI, is an ROI engine. When it is run correctly, you can measure the return, the uplift, and the exact point of diminishing returns. And if it is truly a cost, you have the wrong leader or the wrong vendor.”

In other words, the hybrid model is a full operating model, built on clear roles, well defined handoffs, and leaders who treat the call center as a growth engine rather than a necessary expense.

Patterns across DSOs show that those who tried to move to an AI only approach often find themselves reintroducing more human contact later. They learn, sometimes painfully, that automation without design leads to frustration without growth.

The Future of DSOs is Hybrid

No one seriously believes that AI is a passing fad. The technology will continue to improve, especially in speech recognition, natural language understanding, and integration with practice systems. More interactions will be automated. More patients will book appointments online without ever picking up the phone.

Ryan is clear on this point.

“AI is here to stay. The question is not if DSOs will use it, but how they will use it to enhance the patient experience. And ultimately, the DSOs that consistently deliver the best experience, powered by both AI and people, will be the ones that win.”

Amol’s language about ROI and competitive advantage points in the same direction. DSOs that treat the call center as an ROI engine, supported by AI, will have more levers to pull than those that only see it as cost.

For me, the long-term picture is not a fully automated contact layer, but a mature hybrid environment. I already see this in other industries. Ecommerce platforms rely heavily on automation for simple workflows, yet they still maintain human channels for disputes, exceptions, and high value customers. Airlines invest in digital tools and self-service, yet they keep human agents available when travel plans fall apart.

Group dentistry is moving along a similar path. The DSOs that will lead over the next decade are not the ones that remove humans from the call center at the first opportunity. They are the ones that decide, with intention, where AI creates real leverage and where human connection is non-negotiable.

The myth that AI will replace call centers entirely is appealing because it promises simple answers in a complex environment. The reality is more demanding, but also more powerful. It requires operators to understand their economics deeply, to respect how patients actually behave, and to design systems where technology and people make each other better.

Those who do that work will not only spend smarter. They will convert more patients, deliver better experiences, and build DSOs that are resilient in whatever market comes next.

If you want to explore this approach, schedule a brief conversation with our team to see how dedicated Virtual Assistants fit your operations. In fifteen minutes, we can outline which roles typically transition first, how integration works with your systems, and the KPI’s operators track to validate impact. Visit https://www.getreach.co/.

About the author:

Cory Pinegar is the CEO of Reach, a fast-growing company redefining virtual staffing for dental practices across the U.S. Since acquiring the company at 22, he has scaled Reach to support thousands of clinics while cultivating a culture of clarity, accountability, and purpose. A passionate advocate for sustainable growth and human-first leadership, Cory also serves on the boards of Veriffic and the Parkinson’s Foundation.

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