An AI receptionist pilot should prove that the system can answer approved questions, route calls correctly, recognize when it should stop, protect caller information, and reach a person when automation is not appropriate. Start with a limited number, after-hours window, or overflow queue. Use test callers and non-sensitive scenarios first. Do not send every customer, client, or patient to the system on day one.
Intermedia announced its AI Receptionist on September 10, 2026. As of September 25, the product was available in open beta to eligible Intermedia Unite and Contact Center customers in the United States, with general availability expected in October. Intermedia did not specify October 1 in its public announcement. Eligibility, production availability, features, pricing, and data-handling terms should be confirmed in the current quote and service documents before an AI receptionist pilot.
Why run an AI receptionist pilot instead of switching all calls?
An AI voice agent can answer routine questions, use business-provided information, identify caller intent, and transfer a call to a configured destination. Intermedia says its product can also provide a recap when a call is handed to a person. Those capabilities can help during busy periods and after hours, but they depend on the information, guardrails, destinations, and failure behavior configured by the business.
A controlled AI receptionist pilot exposes bad assumptions while the consequences are small. It can reveal an outdated holiday schedule, a circular transfer rule, a pronunciation problem, a privacy risk, or an urgent call that should have reached a person sooner. The goal is not to produce a flawless demonstration. It is to learn whether the system improves the caller experience under real operating conditions.
Test 1: Can it answer only approved questions?
During the AI receptionist pilot, build a short set of approved facts: business hours, locations, service areas, parking instructions, general services, and routing options. Then ask the same question in several ways. Test incomplete sentences, background noise, accents, corrections, and callers who change topics.
The system should answer from the information the organization approves. It should not invent pricing, availability, legal advice, medical guidance, appointment status, or promises about service. Create a clear fallback response for questions outside the approved scope and send those callers to the right employee or queue.
Test 2: Do transfers reach the right destination?
Map the most common call intents to specific destinations. Examples may include sales, service, supplies, billing, an employee directory, an on-call number, or voicemail. Test transfers during business hours, after hours, holidays, and when the destination does not answer.
Watch for transfer loops and dead ends. If a queue sends the call back to the AI agent, or the agent repeatedly tries an unavailable extension, the caller can become trapped. Every route needs a final fallback that a business owner accepts.
Test 3: Does it escalate urgency and frustration appropriately?
Use scenarios where a caller is upset, repeatedly asks for a person, reports an urgent operational problem, or says the automated answer is wrong. The agent should not keep defending its answer or force the caller through a long dialogue.
Define the situations that require an immediate handoff. A technology service call, a possible safety issue, a patient concern, and a legal deadline do not share the same escalation path. The business—not the software vendor—must decide who is responsible and when a human becomes mandatory.
Test 4: Are the privacy boundaries clear?
Document what the AI receptionist hears, records, transcribes, summarizes, stores, and sends to other systems. Ask where the data is processed, how long it is retained, who can access it, whether it is used to train models, and how it is deleted. Review call recording and consent requirements with qualified legal counsel for the states in which callers and employees may be located.
For a medical practice, do not assume that using a healthcare-oriented phone platform makes every AI feature appropriate for protected health information. HHS explains that a cloud provider that creates, receives, maintains, or transmits electronic PHI on behalf of a covered entity is generally a business associate, and a compliant business associate agreement is required. Confirm that the exact AI receptionist service is within the applicable agreement and risk analysis before allowing it to receive PHI.
For a law firm, test whether callers may disclose confidential facts before a conflict check or attorney relationship exists. Configure the agent to collect the minimum information needed and direct substantive legal questions to a person.
Test 5: Can callers reach a human without fighting the system?
Test phrases such as “representative,” “front desk,” “operator,” and “I need a person.” Also test silence, repeated misunderstanding, and a caller who cannot use the expected menu or vocabulary.
An AI receptionist pilot should measure the number of turns before a human handoff and the percentage of transfers that reach a useful destination. A shorter automated conversation is often better than a clever one. Make the escape route obvious and consistent.
Test 6: Does it work for different callers and conditions?
Include test callers with different accents, speech speeds, ages, and familiarity with the business. Test mobile calls, speakerphones, road noise, poor connections, and assistive technologies where practical. Ask the provider what accessibility features and alternative channels are supported.
Do not judge success only from calls placed by the people who configured the agent. They already know the expected wording. A useful pilot includes people who have not seen the script and are willing to say when the experience is confusing.
Test 7: Are summaries and reports accurate enough to use?
If the system creates call recaps or analytics, compare them with the actual test conversation. Check names, phone numbers, requested services, urgency, transfer destination, and promised follow-up. A summary should help an employee continue the conversation, not create a false record.
Decide whether summaries are operational notes or part of a regulated or official record. Limit access appropriately and avoid copying unverified AI-generated statements into a customer, patient, or legal file without human review.
Test 8: Can staff update information without creating new errors?
Assign an owner for hours, holidays, locations, employee changes, service descriptions, escalation rules, and approved answers. Make one controlled change during the AI receptionist pilot and verify that the agent uses the new information without breaking another route.
Keep a change log. The system may work perfectly at launch and become wrong later because the business changes while the knowledge and call flows remain frozen. Set a recurring review date and an urgent process for correcting harmful answers.
Test 9: Does the pilot improve a measurable business problem?
Choose a small set of outcomes before the test starts. Useful measures may include answered-call rate, abandoned calls, correct-transfer rate, time to reach a person, after-hours messages captured, caller complaints, and staff interruptions. Compare the AI receptionist pilot with the prior process over a reasonable period.
Do not treat every automated call as a success. A call that was answered but misrouted, mishandled, or never reached a person is not an improvement. Include staff feedback and a sample of caller feedback in the decision.
What should an AI receptionist quote include?
Intermedia’s public September announcement did not provide standalone retail pricing. Ask for a written quote that identifies the eligible platform and edition, licenses or usage units, included call volume, overage charges, phone numbers, implementation, knowledge setup, integrations, support, training, data retention, and cancellation terms.
Also ask which capabilities are beta, generally available, or roadmap items. A product page can describe a broad feature set while a particular tenant, license, or beta release supports a narrower set. The signed order and current service documentation should control the buying decision.
What this means for Tallahassee and Thomasville businesses
An AI receptionist can be useful for a Tallahassee law firm, medical office, professional service company, or growing business that misses calls during busy periods or after hours. It can also frustrate callers if it is treated as a complete replacement for a thoughtful call-handling process.
Advanced Business Systems supports business phone and managed IT environments from Tallahassee across North Florida and South Georgia, including Thomasville. ABS can help map current call flows, identify a limited pilot, test transfers, and document questions for the provider. Privacy, recording, legal, and healthcare-compliance decisions should be reviewed by the qualified advisers responsible for them.
Frequently asked questions
Is Intermedia AI Receptionist generally available?
Intermedia’s September 10, 2026 announcement said the product was in open beta for eligible U.S. Unite and Contact Center customers, with general availability expected in October 2026. Confirm current status and customer eligibility before ordering because availability can change.
Does an AI receptionist replace a human receptionist?
It can handle approved routine questions and routing, but it should not replace human judgment, empathy, or responsibility. A good deployment makes escalation easy and defines which conversations must reach a person.
Can a medical practice use an AI receptionist with PHI?
Do not assume so. Confirm whether the exact service will create, receive, maintain, or transmit PHI, whether the vendor and relevant subcontractors will sign or are covered by the required business associate agreements, and whether the practice’s risk analysis and safeguards support the use. Start with non-PHI test scenarios until that review is complete.
How long should the pilot run?
An AI receptionist pilot should run long enough to include normal business hours, after-hours calls, busy periods, staff absences, and the common exceptions that create trouble. A limited two- to four-week pilot may provide useful evidence, but the right period depends on call volume and risk.
What happens if the AI agent gives a wrong answer?
The response should fall back to a person or approved message, and staff should have a fast correction process. Track the error, update the source information or guardrail, retest the scenario, and review whether similar answers are affected.