AI TRAINING
From Phone-Only to AI-Assisted Bookings
Set up an AI voice receptionist that handles bookings reliably without losing customers.
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Run the diagnostic →What it covers
This hands-on workshop guides service SME owners and managers through selecting, configuring, and launching an AI voice receptionist for their booking workflow. Participants leave with a live or near-live setup integrating calendar tools, fallback-to-human routing, and basic compliance practices. The session covers tools such as Goodcall, Rosie, and Dialpad, evaluated against real SME constraints. Roughly 60% of time is practical configuration, 40% is concept and decision-making.
What you'll be able to do
- Choose the right AI voice receptionist tool for your booking volume and budget
- Configure a call flow with booking capture and fallback-to-human routing
- Connect the AI receptionist to your existing calendar to avoid double bookings
- Review transcripts after calls to identify and fix errors in the AI script
- Apply GDPR-compliant call recording disclosures and data retention settings
Topics covered
- Comparing AI voice receptionist tools: Goodcall, Rosie, Dialpad
- Configuring call flows, greetings, and booking scripts
- Calendar integration with Google Calendar, Calendly, or similar
- Setting up fallback-to-human rules and escalation logic
- Reviewing call transcripts to catch errors and improve prompts
- GDPR basics for call recording and data storage
- Testing and going live: a practical checklist
- Measuring success: missed-call rate and booking conversion
Delivery
Delivered in-person or via live virtual session (Zoom/Teams). Each participant needs a laptop and credentials for their phone and calendar systems. The facilitator provides sandbox accounts for Goodcall and Rosie so attendees can test configurations safely. A printed quick-reference card and post-session config checklist are included. Ideal group size is 2-6 so the facilitator can give hands-on support to each participant.
What makes it work
- Spend at least one week in shadow mode (AI listens, human still answers) before switching over fully
- Assign one person to review transcripts weekly and refine the booking script
- Keep the fallback-to-human threshold low at first, then raise it only after confirmed accuracy
- Inform regular customers proactively that a new system is in place to reduce surprise and complaints
Common mistakes
- Going live before testing the fallback rule, real customers reach a dead end when the AI can't handle their query
- Using default greeting scripts that sound robotic and erode customer trust immediately
- Ignoring GDPR call-recording disclosure requirements and exposing the business to complaints
- Not reviewing transcripts in the first two weeks, so recurring AI errors go uncorrected
When NOT to take this
A business that uses a sophisticated CRM with complex multi-step booking logic (e.g., medical triage or multi-resource scheduling) should not start here, the AI voice tools covered are too simple and the integration work requires a dedicated technical project, not a one-day workshop.
Providers to consider
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