How to Choose an AI Receptionist: A 2026 Buyer's Checklist

What to evaluate

• ✓Human-first design: does your team get the first chance to answer, with the AI stepping in only as a fallback?
• ✓Approved information only: does it answer from what you've provided, or does it improvise prices and availability?
• ✓Escalation: can you define what's urgent and who receives it, and what happens if they don't pick up?
• ✓Booking: can it book on a real calendar, hand off to your own booking link, or collect a callback, whichever fits you?
• ✓Records: are calls recorded, transcribed, and summarized, and how does it handle consent?
• ✓SMS: are texts consent-based and limited to messages tied to the caller's own request?
• ✓Setup: how long does it take, and can you place a real test call before going live?
• ✓Pricing: what are the included minutes, the overage rate, and what counts as a minute?

Questions to ask every vendor

1. 1What happens when the AI doesn't know the answer?
2. 2Can I hear real calls, not just a scripted demo, before I commit?
3. 3What does my monthly bill look like at my actual call volume?
4. 4Which integrations exist today, and which are only on a roadmap?
5. 5How are recordings, transcripts, and caller data stored and protected?
6. 6What are the limits, and can you show them to me in writing?

Red flags

• ✓'Unlimited' plans with no published fair-use terms.
• ✓Statistics and customer counts you can't verify.
• ✓No way to test on your own line before paying.
• ✓A vague answer about what the AI does when it's unsure.
• ✓Integrations listed as available that turn out to be 'coming soon.'

Test it on real scenarios

Before you commit, call your own AI receptionist with the calls your business actually gets: an emergency, a routine quote request, a caller who wants a person, a caller with an unusual question. Listen for whether it stays within what you've approved, escalates properly, and leaves your team with a clear summary.