_FBlogo_red.png)
If your managed service provider (MSP) business supports medical practices, you already have a starting point for selling AI voice services: the client’s call data. Use it to show where callers struggle to reach the practice, which requests a defined service could handle, and how you will measure the result. A strong proposal connects that business problem to a service your MSP can deploy, manage, and support profitably. Here’s how to build that case with a healthcare client.
Key Takeaways
-
Use the healthcare client’s call-handling problem to lead the sales conversation, then demonstrate the workflow that addresses it.
-
Build the proposal from the client’s own call reports and financial assumptions. An industry missed-call rate is a discovery prompt, not a revenue forecast.
-
Package a specific administrative service with clear outcomes, staff handoffs, and ongoing support responsibilities.
-
Evaluate two sets of economics: the value to the healthcare client and the cost of delivering the service through your MSP.
-
Agree on healthcare data requirements and pilot success measures before deployment.
Lead With the Healthcare Client’s Business Problem
A practice owner or administrator needs a reason to approve another monthly service. Your MSP’s job is to connect the proposed investment to something the client already wants to improve: access to the scheduling team, coverage during busy periods, or a more dependable way to capture callback requests.
For example, a client may tell you that Monday morning calls overwhelm the front desk. Your next step is discovery. Determine how often calls go unanswered, what those callers need, and what staff does with the messages. That gives you a specific problem to scope and a baseline against which the client can judge your service.
Staff capacity can be part of the case, too. Track time returned to other work separately from additional appointment opportunities. A reduction in interruptions becomes a cash saving only when the client actually reduces a cost. Our guide to finding voice AI opportunities in your existing customer base explains how to distinguish these sources of value.
Use Healthcare Benchmarks to Open Discovery
CallRail’s January 2025 report found a 32% missed-call rate among healthcare businesses in its dataset, the highest of the industries measured. The report’s methodology describes 1.1 million de-identified conversations across seven industries; that total is not a healthcare-only sample.
For your MSP, the useful question is: What does this client’s call handling look like? The benchmark does not establish that a third of a particular practice’s patients are being lost, or that AI will recover the same share. Use it to earn a discovery conversation, then replace it with the client’s evidence.
Build the Proposal From the Client’s Call Reports
If your MSP already manages the phone system, you may be able to help the client obtain call reports within your authorized access. Have the practice validate the operational meaning of the numbers. Aggregate counts are often enough for the first business-case discussion; access to recordings or patient information needs its own approved process.
-
Establish a baseline. Review a representative period, such as 30 to 90 days, and note office closures, holidays, or unusual demand. Count inbound calls, unanswered calls, abandoned calls, and after-hours volume using the phone system’s definitions.
-
Remove overlap. An after-hours call may also be unanswered. Repeated attempts by the same caller may represent one request. Reconcile those categories before estimating opportunity.
-
Identify the requests your service could address. Work with the practice to distinguish scheduling inquiries, routine office questions, and callback requests from spam and calls that require staff. Document how any sample was selected and its limitations.
-
Ask the client to supply the financial assumptions. The practice should provide an appropriate average collected amount per completed visit, or another value relevant to the chosen outcome. Your MSP should not guess from a generic patient-value figure.
-
Estimate a cautious range. Account for callers the practice would have reached through its existing process, appointment availability, and the share of additional bookings likely to become completed visits.
This is an MSP-led discovery process with client-owned assumptions. Use the Agent Studio Opportunity Checklist to organize the discussion, and the AI voice agent discovery guide to document the current workflow and desired outcome.
Present a Business Case the Buyer Can Check
For a scheduling-focused offer, an illustrative model is:
Potential additional monthly collections = eligible missed scheduling opportunities × estimated additional booking rate × expected visit-completion rate × average collected amount per completed visit.
Hypothetical example: a practice identifies 100 distinct missed scheduling opportunities in a month. If a pilot could produce additional bookings from 20% to 40% of those opportunities, 80% of the resulting visits were completed, and the practice collected an average of $150 per visit, the modeled range would be $2,400 to $4,800 in additional monthly collections.
Those are invented inputs showing the calculation, not customer results or a promised return. The estimate assumes the bookings are additional to what the practice would otherwise obtain. It also requires available appointment capacity. Gross collections are not profit: the buyer still needs to account for the cost of providing care and the proposed AI voice service.
Show your setup fee, recurring service fee, and any usage charges alongside the assumptions. If the pilot only captures callback requests, report requests captured first. Appointment and collections results require follow-through from the practice’s scheduling and billing processes.
Package One Healthcare Workflow Your MSP Can Support
A healthcare vertical becomes easier to sell when your offer has a clear job. In the RingLogix workflow session, Eduardo Perotti put the scoping principle simply: We basically want to do small things.
Applied to your offer, that means defining a deliverable the practice can understand and your team can test.
The following are hypothetical service packages to explore with a client. Each requires validation of the proposed configuration, supported connections, and healthcare data handling.
| Client problem | Service your MSP could offer | What you would prove |
|---|---|---|
| Busy-period calls reach voicemail | An overflow agent that collects approved callback details and records a request in an approved destination | The request reaches the correct queue, staff can act on it, and the caller receives an accurate next step |
| Routine office questions repeatedly interrupt staff | An agent that answers practice-approved hours, directions, and other defined administrative questions, with staff routing for exceptions | Answers match the approved information, and out-of-scope questions follow the agreed handoff |
| After-hours scheduling inquiries wait until the office reopens | An after-hours callback-request service with an agreed staff follow-up process | Eligible requests are captured and followed up; an appointment is confirmed only after an authorized booking succeeds |
Write the scope around the action and its completion criteria. For a callback service, the completed action is a recorded request with a defined handoff. Direct appointment booking is a separate scope that requires a suitable scheduling connection and confirmed results. Our guide to scoping an AI voice agent for an SMB customer gives your team a framework for those boundaries.
Explain the work behind that outcome when preparing your implementation estimate. Jaime Norris describes the workflow pattern in the video: Or you have maybe several steps that have to happen in one action, right?
Validating a location, writing a request, and returning a confirmed status can involve separate operations, even when the client buys one straightforward service.
Price the Managed Service Around Its Delivery Cost
The client’s potential benefit helps establish whether the offer is worth evaluating. Your delivery model determines whether it is a viable service for your MSP.
Account for discovery, configuration, integration work, testing, and staff handoff training in the initial project. For ongoing delivery, include platform and usage costs, monitoring, support, exception review, and the changes you have agreed to maintain. Define which changes are included and which require another estimate.
You can offer the service on its own, alongside the client’s communications services, or as part of a healthcare package. The RingLogix guide to AI voice pricing for MSPs discusses those packaging approaches. Use your actual costs and scope to set the price.
A repeatable pattern can improve delivery efficiency across your healthcare customer base. As Jaime explains at 08:16, It's reusable across clients, which is nice, right?
Reuse tested components while reviewing each practice’s systems, approved information, permissions, and escalation rules. Budget for that customer-specific work.
Include Healthcare Data Requirements in the Proposal
Your MSP’s responsibilities extend to the proposed data flow. Identify where protected health information (PHI) could be created, received, maintained, or transmitted, including recordings, transcripts, workflow logs, and connected systems. HHS guidance on business associates specifically identifies relevant MSP services and explains business associate and subcontractor relationships.
Work with the client’s privacy and security leads to determine the applicable business associate agreements (BAAs), access controls, retention, and other safeguards before using PHI. HHS cloud-computing guidance addresses agreements alongside risk analysis and other obligations. Verify the suitability of the complete proposed service; a vendor statement or signed BAA alone does not establish compliance for every configuration.
Keep clinical decisions outside an administrative pilot. The practice should approve how clinical, urgent, and other out-of-scope calls reach qualified staff. Include that handoff in your scope and acceptance tests.
Use the Pilot to Prove Client Value and MSP Delivery Effort
Agree on the pilot’s scope, review period, baseline, and success measures before asking the client to approve it. Choose a period that captures enough representative calls to evaluate the workflow, then compare results with similar operating conditions.
For the client, track the outcome you actually sold: eligible requests captured, successful staff handoffs, requests that became appointments, or completed visits when the practice can validate them. For your MSP, track implementation hours, support effort, usage cost, failed requests, and changes needed to keep the service working.
Bring both views to the review meeting. Strong client results with excessive support effort call for a scope or pricing change. Low demand may mean this client is not a good fit for the proposed service. Either finding is more useful than a call-answer count on its own.
Bring a Specific Offer to the Next Healthcare Client Meeting
Your MSP’s proposal should connect five things: a documented call-handling problem, a defined administrative workflow, client-approved value assumptions, a delivery and support plan, and a pilot scorecard. That gives the practice owner or administrator a concrete decision and gives your team an offer it can stand behind.
Start with one healthcare client. Review its call data and map one workflow, then watch the RingLogix workflow session on YouTube with that service in mind. To evaluate how your MSP could build and manage the offer, explore RingLogix Agent Studio and bring the client’s workflow to an Agent Studio demo.
Frequently Asked Questions
How can an MSP make the business case for AI voice services to a healthcare client?
Use the client’s call reports to identify a specific access or administrative problem, agree on the eligible requests, and estimate value with client-supplied assumptions. Present a defined service, its full cost, and a pilot that measures the agreed outcome.
Can an MSP use the 32% healthcare missed-call benchmark in a sales proposal?
Yes, with attribution and context. CallRail’s January 2025 report found a 32% healthcare missed-call rate in its dataset. Use it to open discovery, then base the proposal on the individual client’s data. The benchmark does not measure that client’s lost patients or predict recoverable revenue.
What is a practical first AI voice offer for an MSP serving medical practices?
A defined administrative service, such as collecting overflow callback requests or answering approved office-information questions, is a useful starting point to evaluate. Validate the required connections, data handling, staff handoffs, and completion criteria before offering it.
How should an MSP price a healthcare AI voice service?
Estimate the initial implementation work separately from recurring platform, usage, monitoring, and support costs. Set clear limits on included changes. Consider the client’s expected benefit and your delivery cost without promising that modeled revenue will be recovered.
What HIPAA questions should an MSP resolve before deploying the service?
Determine how the proposed workflow handles PHI, which parties are business associates or subcontractors, and which BAAs and safeguards are required. Review the complete configuration with the client’s privacy and security leads, including access, recordings, logs, retention, and staff escalation.
