What AI Can (and Can’t) Do for DME Providers
If you've been in this industry over the last two years, you've heard the pitch: AI can fix everything. Prior auth backlogs, referral processing, staffing shortages, all solved by a chatbot assistant or an autonomous agent. Except we know in practice, that’s not always the case. MIT's 2025 GenAI Divide study found that 95% of enterprise AI initiatives saw zero measurable ROI. Not because the technology doesn't work, but because of how it's being sold, taught, and deployed.
In this fireside chat, Trey Holterman, CEO at Tennr, sits down with Tennr customers from national DMEs to talk through why the two AI models currently being pitched to healthcare operators, full autonomy on one end, task-level chatbots on the other, both miss where the real work actually breaks down: at the handoffs between people, payers, and systems.
Drawing on lessons from Tennr's own AI deployments across DME and specialty providers, this conversation offers a different mental model for AI in your operation: not a replacement for your team, and not a productivity nudge, but the underlying machinery that keeps work moving, checked, and correct, station to station. Attendees will leave with a practical framework for evaluating AI vendors, questions to ask before adopting any AI tool, and real examples of what's actually working today.
