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Benchmark data — 40+ sources

Voice AI containment by intent — 2026 enterprise benchmark

Defensibly measured voice AI containment clusters in three bands by intent. The gap between vendor-headline gross figures and finance-grade net figures is consistently 15 to 30 percentage points.

Measurement

Numbers below are blended from approximately 40 enterprise deployments and published case studies between 2024 and 2026. Gross containment = calls not escalated / in-scope calls. Net containment = gross minus calls that re-contacted within 7 days for the same intent.

Intent typeGross containmentNet containment (7-day)
Balance / account status70–85%60–78%
Order / appointment status65–80%55–72%
Simple changes (address, preferences)60–78%50–68%
Authentication & verification55–75%45–65%
Billing questions40–60%28–48%
Basic claims FNOL35–55%22–40%
Disputes & chargebacks20–40%10–25%
Retention & cancellations15–35%8–22%
Vulnerable-customer routingn/a (route to human)n/a

Caveats

  • Blended figures depend on intent mix — your number will sit somewhere on each row, not the average
  • Re-contact window of 7 days is standard; 14 days is more appropriate for claims and disputes
  • Vendor-published headline rates typically use a narrower denominator (excluding short abandons, out-of-hours, out-of-scope) — adjust before comparing
  • Containment is not resolution — see autonomous resolution rate for the stricter measure

Frequently asked

How were these numbers measured?

Aggregated across approximately 40 enterprise deployments and published case studies between 2024 and 2026, with gross containment defined as calls not escalated divided by in-scope calls, and net containment subtracting calls that re-contacted within 7 days for the same intent.

Why do these numbers differ from vendor headlines?

Vendor headlines typically use a narrower denominator (excluding short abandons, out-of-hours, and out-of-scope intents) and report gross rather than net of re-contact. Each adjustment is individually defensible; combined they lift headline figures by 15–30 points.

Can my deployment beat these bands?

Yes on individual intents with strong integration depth and a mature operating model. Blended figures rarely exceed the top of the band sustainably.

Related

Data licensed under CC BY 4.0. Citation: Lewis Crook, Voice AI containment by intent — 2026 enterprise benchmark, 2026-06-15. Methodology at about/methodology.