Enterprise voice AI, decoded.

Field notes for the CX and contact-centre leaders buying and deploying voice AI — what's real, what breaks, and what actually works once it's live. From someone who has been the buyer, the builder, and the person in the room.

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Lewis Crook — Practitioner Analysis

Voice AI for contact centres

Honest economics, no vendor spin & no theatre.

What I write about

The honest economics, evaluation framework, integration depth, operating model, and measurement of enterprise voice AI — separated from vendor marketing.

Who it helps

CX, contact-centre, and customer-service leaders in regulated and high-volume industries: financial services, insurance, telco, healthcare, utilities, airlines, retail.

What it is not

Not a sales site. No service packages, no booking links, no sponsored vendor coverage. An analysis archive, written from production experience.

The pillars

Where to start.

All guides →

01
Economics
Voice AI vs legacy IVR: the honest unit economics
Voice AI is cheaper than a live agent and more expensive than a touch-tone IVR. The real question is not cost per call but cost per resolved call — and most vendor ROI models quietly assume containment rates that production deployments do not hit.
02
Evaluation
How to evaluate enterprise voice AI platforms: a vendor-neutral framework
A defensible enterprise voice AI evaluation rates nine dimensions, not three. Most procurement decisions go wrong by over-weighting demo quality and under-weighting integration depth, observability, and the operating model required to keep the agent useful after launch.
03
Metrics
Voice AI containment rate: what's real vs what vendors claim
Containment rate is the single most-quoted and least-defined number in enterprise voice AI. Vendor figures of 70%+ are not wrong, but they usually measure a narrower denominator than the one a CX leader cares about.
04
Operations
Why enterprise voice AI pilots fail to reach production
Most enterprise voice AI pilots that stall do so for the same five reasons, and none of them are model quality. They are integration depth, operating model, measurement, scope creep, and stakeholder alignment.