Quick answer (updated August 2026): An AI receptionist is worth testing for most home-service businesses once you measure your missed calls. Invoca’s 2024 call-tracking data shows 27% of calls to home-services businesses go unanswered. At 200 calls a month and a $300 average ticket, that puts roughly $1,800 a month at risk against a tool costing $49 to $150. The formula to run your own numbers is below. We sell no software and take no commissions.

Should you trust this comparison?

Fair question, because most of what ranks for “AI receptionist” is written by AI receptionist companies, and each one concludes that its own product is the best. Hourback is an AI assessment practice, not a software vendor. We sell no phone software, take no affiliate commissions, and have no reseller deals with anyone in the table below. Every price in this article comes from the vendor’s own published pricing page, checked on July 22, 2026, with the link shown so you can re-check it.

Two more disclosures. First, prices in this category change without notice, so treat the table as a snapshot and the links as the source of truth. Second, we make money when businesses hire us to figure out which tools are worth buying. That gives us a bias toward “measure first, buy second,” which is exactly the bias this article recommends.

Start with the math, not the demo

Every vendor demo sounds impressive. The only question that matters is what your missed calls cost, and you can estimate it with four numbers you already have or can get from your phone bill:

Monthly revenue at risk = monthly inbound calls × missed-call rate × share that are new-job inquiries × close rate × average ticket

For the missed-call rate, use a measured figure, not a guess. Invoca’s call-tracking data (2024) found 27% of calls to home-services businesses go unanswered, and fewer than 3% of callers pushed to voicemail leave a message. A missed call is usually a silent loss. Phones still carry the buying decision: Invoca’s consumer research found 62% of buyers call a business before purchasing.

One honest caveat: CallRail’s 2025 analysis of 1.1 million business calls found a lower home-services miss rate of 14%. The two datasets measure different customer bases. Run the formula both ways and treat the lower result as your floor.

A worked illustration (not a promise)

Here is the formula applied to a hypothetical plumbing company, with every input rounded against the purchase. This is an illustration, not a result any client achieved:

Input Value Note
Monthly inbound calls 200 From the phone bill
Missed-call rate 27% (Invoca, 2024) 54 missed calls
Share that are new-job inquiries 50% Haircut for spam, vendors, existing customers
Close rate on answered inquiries 25% Use your own; round down
Average ticket $300 Use your own; round down
Revenue at risk per month ~$1,800 54 × 0.5 × 0.25 × $300, rounded down

Rerun it with CallRail’s 14% floor and the same haircuts and you get roughly $900 a month. Against a $150-per-month tool (costs rounded up), even the floor case pays for itself several times over, if the tool actually converts those calls. That last clause is the whole game, which is why the trial design in the checklist below matters more than the demo.

What AI receptionists do well in 2026

The category got dramatically better in 2024 and 2025, and the reason is infrastructure, not hype. Andreessen Horowitz’s 2025 voice-agent update notes that 22% of the most recent Y Combinator class was building voice-agent companies, and that OpenAI cut its realtime voice API prices by 60% on input and 87.5% on output in December 2024. Cheaper, faster models mean the current tools hold natural conversations instead of reading phone-tree scripts. Grand View Research values the broader conversational AI market at $14.3 billion in 2025, projected to reach $78.9 billion by 2033.

In practice, the current generation is genuinely good at the calls that make up most of a home-service day: answering after-hours and overflow calls instead of voicemail, booking routine appointments into your scheduling software, answering standard questions (service area, hours, rough pricing ranges you approve), taking structured messages, and texting the caller a confirmation. If your pain is booking-type calls that ring out while your techs are under a sink, the technology fits. Our guide to AI for home-service businesses covers where phone answering sits among the other fixes.

Where they still fail

Be equally clear-eyed about the misses. AI receptionists in 2026 remain weak at complex triage: the caller describing a furnace noise that could be three different problems, the commercial client with a multi-property job, the negotiation over price, the furious customer whose repair failed twice. They also can’t judge a true emergency the way a human can; they can only pattern-match against the emergency rules you wrote. And a minority of callers simply hang up when they realize they are talking to a machine, which is a real cost you should watch in your call recordings.

The practical conclusion is not “avoid AI” but “design the handoff.” A well-configured deployment answers the routine 80% and escalates the rest to a human fast: transfer to the owner’s cell, an on-call tech, or a human answering service. Vendors that make escalation rules easy to configure and test are worth more than vendors with the slickest demo voice.

What AI receptionists actually cost (verified July 2026)

Prices below are from each vendor’s published pricing page, fetched July 22, 2026. They change often; the links are the source of truth.

Vendor Published pricing (as of July 22, 2026)
Rosie $49/mo (250 min) · $149/mo (1,000 min) · $299/mo (2,000 min)
Goodcall Starter $79/mo per agent · Growth $129 · Scale $249 (annual: $66/$108/$208); unlimited minutes, priced on unique customers
Smith.ai AI Receptionist Free $0/mo (25 calls, then $3.00/call) · Pro $150/mo ($2.00/call) · Enterprise $500/mo ($1.67/call)
Slang.ai Core from $399/location · Premium from $599/location
Retell AI (build-it-yourself platform) “$0.07–$0.31/min for AI Voice Agents”; vendor’s worked example ~$0.11/min
Synthflow Enterprise-only; contracts start at $30,000 annually

For contrast, human answering services publish these rates: Smith.ai’s human/AI-blended plans run $300/mo for 30 calls up to $2,100/mo for 300 calls ($8.50–$11.50 per overage call), and Ruby runs $250/mo for 50 minutes up to $1,725/mo for 500 minutes, roughly $3.45–$5.00 per receptionist-minute. AnswerConnect publishes no pricing at all. The verified gap: AI coverage runs roughly $49–$599 a month, human coverage $250–$2,100 for far less capacity. That gap, not any single feature, is why this category exists.

The compliance wrinkle the sales pages skip: the text-back leg

Almost every AI receptionist includes a texting feature: text the missed caller back, text booking confirmations, text follow-ups. That text leg carries two compliance obligations most vendor pages never mention.

A2P 10DLC registration. U.S. mobile carriers require any business sending application-generated texts from a normal ten-digit local number to register its brand and messaging campaign; per Twilio’s published guidance, anyone sending application-to-person SMS to U.S. numbers over local numbers needs to register, and unregistered traffic faces filtering. Your AI receptionist’s texts are application-generated by definition.

TCPA consent. The federal Telephone Consumer Protection Act, enforced by the FCC, restricts automated texts to mobile phones without the called party’s prior express consent, with a stricter written-consent standard for marketing messages; the FCC’s Small Entity Compliance Guide (2024) also extends Do-Not-Call protections to texts, and FCC rules require honoring opt-out requests such as a “STOP” reply. A text-back to someone who just called you sits on much safer ground than a promotional blast, but the rules are technical and violations carry statutory damages. This article is not legal advice; the FCC’s TCPA materials and your attorney are the authorities.

What you actually need to do: ask the vendor, in writing, who registers the 10DLC campaign, in whose name, who pays the carrier fees, and how opt-outs are honored. A vendor who answers crisply has done this before. A vendor who says “don’t worry about it” is handing you the risk.

The evaluation checklist

Bring this list to every demo. It is short because each item is a dealbreaker:

  • Month-to-month terms. The product is cheap to try and the market is moving fast. Do not sign an annual contract for an unproven tool.
  • Your call recordings, exportable. You need recordings and transcripts to audit what the AI actually says, and you need to keep them if you leave.
  • A configurable human escalation path. Transfer rules by time of day and call type, tested by you with real calls before launch.
  • Data terms in writing. Whether your calls train their models, how long data is retained, and what is deleted when you cancel.
  • Number portability. If the vendor provisions your tracking or text number, confirm you can port it out.
  • Texting compliance handled and documented. The 10DLC and consent questions above, answered in writing.
  • A measured trial. Note your answered-call rate and booked jobs for two weeks before launch, then compare four weeks after. The phone system’s own logs settle the ROI question better than any testimonial.

If you run the trial and the numbers disappoint, cancel. That option is precisely why the checklist starts with month-to-month terms.

Bottom line

Price the problem before the product. With Invoca’s 27% home-services miss rate (or CallRail’s 14% floor), a 200-call-a-month shop with a $300 average ticket has roughly $900 to $1,800 a month at risk, against verified tool prices of $49 to $599 a month. If your own formula clears the tool cost by 3x or more, run a measured month-to-month trial with human escalation and the texting compliance settled in writing. If you want the missed-call fix ranked against everything else eating your week, that is what an AI opportunity assessment does; Atlanta operators can start with our local home-services guide.

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