AI Boosts Customer Service KPIs 50%+ for Top Performers: EY
EY research finds top-performing organizations achieve over 50% improvement in core customer service KPIs after deploying AI, widening the gap with slower adopters.
A new EY report finds that top-performing organizations are seeing improvements of more than 50% across core customer service KPIs after deploying artificial intelligence. The findings point to AI adoption as a significant differentiator between customer service leaders and the rest of the market, with the gains concentrated among companies that have moved furthest along their AI implementation.
EY's research frames this as evidence that AI is no longer a marginal efficiency tool in service operations but a lever capable of reshaping core performance metrics when applied by organizations with the right foundations in place.
For leaders running contact centers, service operations or digital transformation programs, this report reinforces that the gap between AI leaders and laggards in customer service is widening, not narrowing. When top performers see KPI gains north of 50%, that's not incremental optimization — it signals AI is beginning to change the operating model for service delivery itself, from how queries are resolved to how performance is measured.
The finding also raises the stakes for organizations still treating AI in service as a pilot or a chatbot layered on top of existing processes. If the biggest gains go to top performers, the implication is that AI's value in customer service is conditional on execution quality, not just tool adoption.
— Over 50% improvement across core customer service KPIs reported by top-performing organizations using AI, according to EY.
Headline statistics like "50% improvement" are easy to celebrate and easy to misread. The real story isn't the number — it's the gap it implies between organizations that have built the right conditions for AI to work and those that haven't.
Most leaders will fixate on the percentage and rush to deploy more AI tools, when the actual lesson is about readiness: data quality, process design and employee enablement determine whether AI amplifies good service or just automates bad service faster. A customer-obsessed operator should treat this report as a prompt to audit the foundations — journey maps, data pipelines, escalation paths — before chasing the same KPI lift. Without that groundwork, the other half of the market risks deploying AI and getting a fraction of the result, or worse, consistently faster failure.