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A pre-conference workshop at the 13th Annual Dykema DSO Conference. The executives who have already deployed AI across thousands of practices, on the record about what worked, what did not, and what they would do differently.
Most dental groups are growing 2 to 3 percent a year while costs climb 5 to 6 percent. That gap is where value quietly disappears, and most operators try to close it by spending more.
This workshop takes the other path. It is built around the four levers operators are actually pulling right now to drive organic same-store growth: marketing, patient access, case acceptance, and revenue cycle.
No vendor pitches. No future-of-AI speculation. Just operators from Heartland Dental, Sage Dental, Dental Care Alliance, Affordable Care, Riccobene Associates, and Tally telling you what is working in 2026. Every panelist went on the record with us on the Healthcare 100 podcast before this event. Live, we push them to go deeper.
At the end of every conversation, each panelist answers the same question: what is the one move a group in this room could make tomorrow that returns $100,000 of EBITDA inside a year?
These are not futurists. They are the executives who have already deployed AI across thousands of practices. You will not find this collection of operators being this honest anywhere else.
Each panel pairs executives running the function at scale, in centralized and decentralized models, so you can see what transfers to your organization.
Acquiring more profitable patients while search turns into answer engines and AI agents start shopping on patients' behalf. These two CMOs run marketing for over 2,200 practices between them, and both hold marketing accountable for completed visits, not leads. They will show you why the flat percent-of-revenue budget is dead and what replaced it.
Going deeper live: should the marketing budget trend toward zero? Is every paid dollar an admission your organic engine failed?
Converting the lead, creating capacity, and recapturing revenue, in centralized and decentralized models.
Going deeper live: a lost patient is a marketing problem, a sales problem, or an ops problem. AI call analysis separates the three at scale.
Computer-vision AI driving better diagnosis, higher case acceptance, and patients reaching optimal health. Three platforms, three operating models, past the pilot phase.
Going deeper live: most clinical AI pilots stall around month four. These three DSOs moved past it. Here is how.
Where the money actually changes hands: verification, denials, AR aging, and cost to collect. Revenue cycle is dental's most under-discussed lever and its most under-measured cost center. Tally pairs production AI agents with expert ops, where every exception a human works becomes training data that makes the AI better. That compounding loop is what pushes cost to collect below 4 percent.
Benchmarks to write down: cost to collect is 8–10% typical, ~5% best in class, and under 4% is the AI-era target.
Before the workshop, Amol and A.J. sat down with every panelist on the record. The best of those conversations is distilled into a workbook every attendee takes home.
Insights and direct quotes from every panelist on the left pages. The right pages are yours, structured so you capture what you hear live.
Every panelist's answer to the same question: the one move that returns $100,000 of EBITDA inside a year. In writing, per lever.
A commitment page near the back. One move per lever, chosen by you, ready to execute the Monday after Denver.
Seating is limited and this room filled fast last year. If you are attending the 13th Annual Dykema DSO Conference, this is the highest-density four hours of the week.