The spreadsheet cell nobody can explain

How to systematically read an AI system’s unresolved queries as market research instead of a model-training backlog, using the categorization approach Ingka’s data pointed to

The specific organizational mechanism that converted a customer-service cost center into an accountable, targeted revenue channel

Why reskilling programs succeed or fail based on whether they target an evidenced capability gap, rather than a generic “AI upskilling” mandate

How to report automation savings and new-revenue metrics separately, so a bigger opportunity doesn’t get buried inside a cost-savings press release

A specific 7-day pilot you can run using your own support system’s escalation logs, with no new AI tooling required

What this implies about where competitive advantage is shifting in an AI-saturated market, and why “best model” is the wrong thing to optimize for

Ingka Group, the largest IKEA franchisee, deployed an AI chatbot called Billie for customer service starting in 2021and from 2021 to 2023 it resolved approximately 47% of customer enquiries, translating to 3.2 million interactions and nearly EUR 13 million in savings.

Rather than treating the unresolved majority of queries as a bot-training problem, Ingka analyzed them and found a concentrated, unmet demand for interior design consultation, a service its call center wasn’t built to sell.

Instead of shrinking headcount to match the automation rate, Ingka reskilled 8,500 call-center employees into remote design consultants and sales advisors, a group that now operates from 24 remote-sales centers covering all 31 countries where Ingka has a presence.

That channel generated an estimated 1.3 billion euros (roughly $1.5 billion) in revenue in fiscal 2022 alone, about 3.3% of group sales, with Ingka setting a public target of 10% of total revenue by 2028.

Ikea’s in-house customer happiness score has risen to 89%, up from 60% prior to Billie’s rollout, according to Ingka.