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AI automation for customer support

Klarna saved $60M. Then they learned the real lesson.

The biggest AI customer support story of 2024-2025 is not about replacing humans. It is about building hybrid systems that handle 60-70% of volume so your team handles what matters. Here is the data.

$60M

Saved (Klarna)

98%

Auto-resolved (Ruby Labs)

-90%

Cost vs human agents

60-70%

Optimal AI handling rate

Verified case studies

What's already working in customer support

The full Klarna arc, plus companies that got the hybrid model right from day one.

Klarna - The most studied AI support deployment in history

Fintech - Global

Problem

150M users generating massive support volume. Customer service costs at $0.32 per transaction. Manual handling could not scale with growth.

Solution

OpenAI-powered AI assistant deployed globally. Handled 2.3 million conversations in its first month - equivalent to 700 full-time agents. Operates in 35+ languages, 24/7. Cost: $2-3M implementation cost (per CEO Sebastian Siemiatkowski).

  • $60M

    total savings as of Q3 2025

  • $39M

    saved in 2024 alone (IPO filing)

  • -40%

    CS cost per transaction ($0.32->$0.19 over 2 years)

  • -82%

    improvement in response times (15min->2min)

  • -25%

    reduction in repeat issues

  • 2/3

    of all inquiries handled by AI

Sources:OpenAI case study, CX Dive / Yahoo Finance, CX Dive, The Finanser, Klarna press release - Q3 2025 earnings, Q1 2025 earnings, IPO filing analysis, and Klarna press release (Feb 2024).

The Klarna lesson - why hybrid wins

Critical context

Problem

Klarna initially went all-in on AI, laying off staff and pausing hiring. By May 2025, they reversed course and began rehiring humans for complex cases after overpivoting on pure cost containment.

Solution

Hybrid models (60-70% AI, 30-40% human) typically deliver the strongest mix of cost savings and customer satisfaction. Full automation can produce short-term savings followed by CSAT erosion.

  • 60-70%

    AI handling in a stable hybrid model

  • 30-40%

    human handling for complex cases

  • Hybrid

    best long-term balance of cost and quality

Source:CX Dive - Klarna staffing and model shift in 2025 with analyst commentary on complexity-driven handoffs.

Ruby Labs - AI-First Support Resolution

SaaS - USA

Problem

Support team could not scale with user growth. Every new user added linear support cost. No way to maintain quality at scale.

Solution

AI agent deployed as front-line support, handling the full resolution cycle for routine queries - ticket classification, response generation, and follow-up.

  • 98%

    of support chats resolved without human intervention

  • Scalable

    support without proportional headcount growth

Source:Botpress - "10 Real World Case Studies of AI Agents" (May 2025)

NIB Health Insurance (Australia) - "Nibby" AI Assistant

Health insurance - Australia

Problem

High volume of routine customer inquiries consuming licensed agent time. Agents tied up answering repetitive questions instead of handling complex cases.

Solution

AI digital assistant "Nibby" deployed for routine inquiries with seamless handoff to human agents for complex cases - a hybrid model from the start.

  • $22M

    total savings

  • -60%

    reduction in human support need

  • -15%

    decrease in phone calls to agents

Source:FactR / DataPeak - industry comparison in AI cost savings analysis

Waiver Consulting Group - Waiverlyn AI Lead Bot

Consulting - USA

Problem

Website visitors dropping off without converting. No scalable way to greet, qualify, and book consultations without dedicated sales staff.

Solution

AI lead generation bot ("Waiverlyn") deployed to greet visitors, answer questions, collect contact info, book consultations, fill calendar invites, send reminders, update Google Sheets, and notify the sales team - all autonomously.

  • 3 weeks

    to pay for itself in booked consultations

  • Fully auto

    lead capture -> qualification -> booking -> notification

Source:Botpress - "10 Real World Case Studies of AI Agents" (May 2025)

American Express - Travel Counselor Assist AI

Financial services - Global

Problem

5,000 travel counselors across 19 markets creating personalized travel plans. Enormous research burden per customer interaction.

Solution

AI assistant working alongside human counselors - pulling real-time travel data, matching suggestions to cardholder preferences using booking and spending behavior, handling research instantly.

  • 85%+

    of counselors say AI saves time and improves quality

  • Real-time

    location-specific travel intelligence

  • Hyper-personal

    suggestions from spending behavior analysis

Source:Botpress - "10 Real World Case Studies of AI Agents" (May 2025)

Industry benchmarks - customer support AI

40-70%

efficiency gains in customer service from AI

Hype Studio / industry benchmarks

$80B

projected global contact center savings from AI by 2026

Digital Applied analysis

60-70%

optimal AI handling rate for hybrid models

Industry deployment data 2024-2025

30% call center

time savings is the typical industry benchmark

Agility at Scale / Deloitte, McKinsey

Next step

We build the hybrid model. Not the "replace everyone" model.

Scenario-based classification. Human handoff. Error handling. Guardrails. Our AI support systems are built to handle 60-70% of volume with 100% confidence - and hand off the rest to your team with full context.

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