By use case.

Same evaluation framework; different intent shape, different integration depth, different regulatory ceiling. Each use case has an industry-specific page where the design materially changes.

• 01
  FNOL & structured intake

  Voice AI for FNOL and structured intake

  Structured intake is the cleanest voice AI use case there is: narrow intent, well-defined writes, and a clear escalation path. The economic value lives in straight-through resolution where coverage is clean, and in faster, better-prepared pickup on everything else.

  Containment band: 30–60% depending on coverage cleanliness and integration depth

  Industry deep dives: Insurance

• 02
  Appointment & field-service scheduling

  Voice AI for appointment and field-service scheduling

  Scheduling is one of the most predictable voice AI deployments — when the AI can see and negotiate against real availability. The trap is a flat day grid that sells slots the operator cannot keep; the cure is integration depth against the actual scheduling system.

  Containment band: 45–80% depending on calendar complexity and integration

  Industry deep dives: Healthcare, Telecommunications, Utilities

• 03
  Balance & account status

  Voice AI for balance and account-status enquiries

  Balance and status enquiries are the workhorse voice AI use case: narrow intent, structured data, low decisioning. They deliver the highest containment numbers and the most misleading headline metrics — because vendors quote gross containment on the easiest call type and call it a platform benchmark.

  Containment band: 60–85% gross; 50–75% net of 7-day re-contact

  Industry deep dives: Financial services, Healthcare, Telecommunications, Utilities

• 04
  Billing & payments

  Voice AI for billing enquiries and payments

  Billing and payments split into three: explaining the bill, taking the payment, and offering a plan. The first two scale on voice AI cleanly with the right PCI architecture. The third — payment plans, deferrals, hardship — is where Consumer Duty and equivalent regimes constrain the AI to triage and capture, not autonomous resolution.

  Containment band: 40–70% across explain / pay / plan, much lower on hardship by design

  Industry deep dives: Financial services, Healthcare, Insurance, Telecommunications, Utilities

• 05
  Authentication & identity

  Voice AI for authentication and identity verification

  Authentication is the hardest half of most voice AI calls. The deployments that hold up treat it as a tiered policy layer — low-assurance for disclosure, step-up for change, multi-factor for sensitive actions — with voice biometrics as a factor, not the factor.

  Containment band: Not a containment use case — measure success, friction, and fraud loss

  Industry deep dives: Financial services, Insurance, Telecommunications

• 06
  Outbound & proactive notifications

  Voice AI for outbound and proactive notifications

  Proactive outbound voice AI routinely delivers more economic value than incremental inbound containment — by killing the inbound call before it happens. The hard parts are consent, opt-out behaviour, and frequency capping; the AI itself is the easy part.

  Containment band: Measured as inbound-deflection lift (typically 20–50% of the targeted intent volume), not containment

  Industry deep dives: Financial services, Healthcare, Insurance, Telecommunications, Utilities