Over two years of building AI support agents we've seen both 400% six-month ROI cases and failures that cost a client 8% of their customer base in churn. The difference always comes down to one thing: was the scenario chosen correctly.
Where AI agents reliably outperform humans
- FAQs and common ops — order status, re-shipment, password reset
- Scenarios with a clean API: ticket creation, bookings, access grants
- Night support and markets outside your primary time zone
- First-line triage: classification and routing to the right team
Where AI breaks the experience
- 01Conflict conversations — refunds, complaints, legal questions
- 02Cross-domain tasks where the answer depends on 3+ systems without a unified API
- 03Markets where the customer expects a personal touch (B2B enterprise with €100k+ contracts)
- 04Cases where the cost of a single mistake exceeds the agent's annual savings
The best AI support agents are the ones that know when to hand off to a human. We always design escalation logic in sprint one.
How to measure success
- Containment rate — share of conversations the agent closes without handoff
- CSAT separately for AI and human conversations — compare, don't blend
- First response time (FRT) and time to resolution (TTR)
- Cost per resolved case — the metric your CFO cares about
What it costs to launch
A pilot connected to one system (e.g. Zendesk + knowledge base) takes 6–10 weeks and €25,000–€45,000. ROI typically lands in 5–9 months with a containment rate above 50%. If your traffic is below 3,000 requests per month the economics don't work — don't start.