For Dental Support Organization (DSO) executives, the quest for efficiency, profitability, and exceptional patient care often hits a significant roadblock: scheduling complexity. At Dykema’s 2025 DSO Conference, TrueLark hosted a breakfast session unpacking how front-office AI has proven to be a game-changing solution for leading DSOs.
Eric Weeden, Head of Sales at TrueLark, moderated the panel discussion featuring Amy Manzo, Senior Director of Operations at MB2 Dental; Chris Ternus, Strategic Accounts Manager at Planet DDS; Tapan Patel, Head of Product at TrueLark; and David McNeil, Chief Revenue Officer at Weave. Together, they explored how well-configured AI is helping DSOs overcome the persistent operational challenge of scheduling.
Here are key takeaways from the panel discussion:
1. Getting Scheduling Right is Everything – But It’s Complicated
Central to growth, healthy margins, and patient access, an optimized schedule is the foundation of a thriving practice. “It sounds straightforward,” Eric started, “but too often, operational challenges make ‘getting scheduling right’ unattainable.” He shared four core issues consistently standing in the way of scheduling success:
- Process and workflow inconsistencies can lead to double bookings, missed appointments, and frustration for patients and staff.
- Lack of standardization at the DSO and practices makes it nearly impossible to implement scalable systems or automation.
- Disconnected data sources can cause operating silos, blind spots, and bottlenecks.
- Tech tools that require too much human intervention put practices at risk of errors, lost time, and revenue leakage.
The panelists unanimously agreed, with nods from the audience, that the current state of scheduling is a costly chaos. Scheduling is indeed hard for humans and technology, but while AI has finally provided the industry with a solution, most DSOs are still living in the problem.
2. Implementing AI in Scheduling Offers Tangible Benefits
Until today, DSOs and practices have tried to address complexities and streamline scheduling processes with limited success. Relying on experienced staff members or investing in narrow-scope tech solutions—like online scheduling tools or virtual receptionists—has not delivered the operational efficiency practices need. These approaches have consistently fallen short of providing optimal value to both practices and patients.
“AI has come a long way,” Amy lauded, noting that many people don’t realize they’re engaging with AI when they contact an MB2 practice using TrueLark’s platform. “You don’t necessarily know. It’s not robotic,” she said, “and it’s definitely made an improvement because it’s taking that task off the front office staff so that they can focus on the patient in front of them.”
David chimed in with an example of how advanced forms of AI, like those engineered at TrueLark, have the ability to incorporate patient context into their processes, which enables the technology to manage the schedule in a much more effective way. “If a patient is calling in to make an appointment,” he said, “the AI will recognize that a family member has an appointment scheduled later in the week and will offer to coordinate the visits. It creates a better experience for them and for you.”
Building on how AI enhances the patient experience and drives revenue, Amy pointed out that “nobody likes being put on hold – or sitting through seven rings until a voicemail picks up and asks the patient to ‘press one’ to do something. When the practice doesn’t pick up the phone,” she continued, “TrueLark automatically kicks in, and sends a text to handle the appointment.” She shared that as a result, some of her practices have booking conversion rates as high as 89%. “The engagement is actually incredible!”
3. AI Platforms and AI Assistants are Not Created Equal
The panelists agreed that it’s crucial for DSO executives evaluating AI solutions to look beyond superficial automation. Tapan explained that point solutions – sometimes referred to AI receptionists, AI bots, and AI assistants – solve for a single problem, such as automating after-hours web chats. Acknowledging that DSOs, like other businesses, have limitations in adopting, evaluating, and implementing new solutions, he asserted that “they aren’t going to be able to onboard every single point solution with as much effort every single time.”
The goal, he stressed, is to “develop solutions that not only address immediate problems but can also be extended to tackle evolving challenges.” A comprehensive platform, such as the TrueLark AI Communications Control Center, provides multi-use-case functionality, offering long-term adaptability. The panel agreed that for a scheduling solution to check the boxes – and deliver value at the DSO and practice level – it needs to be…
- Configurable. Every DSO and practice has unique scheduling rules, so the key is a system that adapts to variations, turning best practices into scalable automation. This includes handling different provider types, appointment rules, timing, operatory setups, and even phantom columns.
- Comprehensive. Patients use various methods—texts, calls, forms, website chat, or in-person—to book appointments. A complete solution must handle all these channels and use cases, from missed calls to web chats, and integrate with existing systems like PMS, phone systems, and CRMs to avoid increasing manual work.
- Automated. True automation focuses on task completion, not just awareness. A system that can’t finish the job, like booking appointments or preventing duplicates, merely shifts the burden to staff. This is the difference between a chatbot and a true AI solution, preventing the system from becoming just a notification service.
- Extensible. As needs expand (reminders, outbound campaigns, new locations, specialties), you shouldn’t need a new system. A truly extensible system lets you build once and scale fast, leveraging existing configurations for new use cases without starting from scratch, keeping your tech stack clean and operations efficient.
4. Scheduling Solution Configurability Is a Hot – and Nuanced – Topic
Since every DSO and every practice within a DSO has its own set of scheduling rules, workflows, and logic, they need a system that can accommodate variation. The right platform should be able to take your organization’s best practices and turn them into scalable automation across locations.
When considering what configurability should look like at the DSO level, Chris stressed that “solutions should match what the organizational operational leadership team needs from the top down” so that processes can be streamlined across the DSO and customizable at the practice level.
“The reality is that practices operate differently,” noted Tapan, “so any system should account for how the practice is running today so that you can deliver value today.” Amy, whose organization gives practices full autonomy, agreed that having the ability to customize configurations for particular locations – “figuring out a way to schedule that is profitable for each practice, but also effective and efficient” – is critical for success.
When asked how PlanetDDS help DSOs scale and move from chaos to clarity within the platform environment and especially scheduling across multiple practices with different workflows, Chris shared that they approach it by having an extremely configurable system that can be deployed and unified across a full enterprise DSO. “That way, you’re getting the same information consistently across the board with your practices.”
5. The Future is Data-Driven
The end-game for a flexible, customizable solution configuration, Tapan suggested, is that DSOs can leverage data and iterate to arrive at a standardized approach that allows them to get to an ideal state of operation. Ultimately, robust dental communications data is the power behind these seamless patient experiences. AI systems that integrate tightly with PMS and other tools, surfacing real-time patient data (contact info, pending appointments, balances), enable highly contextualized interactions and effective schedule management.
The panelists and session participants agreed that while the industry is moving towards greater data accessibility, challenges remain in achieving clean, consistent data across various PMSs, which is crucial for advanced features like predictive analytics (e.g., predicting no-shows). However, the ability to collect and analyze performance data from different scheduling configurations within a DSO allows for identifying best practices and driving improvements.
“When the DSO and practices are able to extract the insights they need from their operational data,” David shared, they’ll know how to “…do scheduling right and differently over time,” optimizing their schedules. Srivatsan Laxman, TrueLark’s CEO, took the opportunity to add that “the TrueLark platform generates a matrix that allows DSOs to see through our analytics to identify best practices that may help improve the performance or the scheduling set up at a location.”
For DSO executives, implementing configurable, comprehensive, and automated AI solutions is no longer a luxury but a strategic imperative. It’s about moving from costly chaos to clarity, unlocking true operational efficiency, and delivering the patient experience of the future.
To learn more, watch the full recording here: Tackle Scheduling Complexity with AI: TrueLark Dykema 2025 Breakfast Panel.
