AI Voice Agent ROI for UK Contact Centres

How the numbers are calculated

This calculator uses the same model Rel8 walks through in a discovery call. Three drivers, plus a deployment cost line:

1. Containment savings

Contacts the AI voice agent resolves end-to-end never reach a human agent. The saving is the full handled cost of those contacts:

contained_contacts × AHT_minutes × (loaded_hourly / 60)

The default 14% containment is conservative; it matches what we've measured on Day 1 of real UK FS deployments, before model tuning and intent expansion. Mature deployments at 6-9 months typically run 25-35%.

2. AHT reduction on AI-assisted contacts

For contacts the AI doesn't fully contain, it still does intake (identity verification, context gathering, intent classification) before transferring to a human. The human agent picks up a shorter call with context already populated:

remaining_contacts × AHT × AHT_reduction × (loaded_hourly / 60)

30% AHT reduction is a typical UK FS measurement; well-deployed agents do better when integrated with the CRM and case-management system.

3. Loaded agent cost

Loaded cost includes salary + employer NI + pension + management overhead + tech licence + workstation + estate. UK FS contact-centre loaded cost is typically £25-30/hour. The slider extends to £45 for premium / regulated specialist roles (e.g., complaints handlers, vulnerable-customer specialists).

4. Implementation cost

£150k is the typical Rel8 4-6 week production engagement for a UK FS contact centre: discovery, design, build, FCA-coded guardrails, QM dashboards, go-live, and hypercare. The slider covers the realistic range from a single-use-case POC (£50k) up to a multi-LOB enterprise rollout (£400k).

What's NOT included

• Cloud infrastructure run-cost (AWS, model inference) — typically 3-7% of labour saving
• Compliance + audit tooling — assumed already in place at FCA-regulated firms
• CSAT / NPS impact — typically neutral-to-positive on well-deployed agents, but variable
• Revenue impact — outbound / cross-sell use cases where AI lifts revenue (separate calc)

Caveat: This is a desk-model. Every deployment has site-specific variation in containment, AHT, and integration cost. The reason to book a call is to model your actual contact mix and regulatory constraints — not to argue with the defaults.