When companies consider AI customer service, the first question is often how much labor it can save. A better question is how many more customer issues a team can resolve without reducing service quality.
A field study involving 5,179 customer-support agents found that access to a generative AI assistant increased productivity by about 14 percent on average. The gains were much larger for novice and lower-performing agents, reaching roughly 34 percent, while experienced agents benefited far less. This suggests that one of AI’s most valuable roles is transferring the practices of top performers across the organization.
That finding changes the best adoption strategy. Instead of trying to replace human agents immediately, companies can first use AI to retrieve knowledge, summarize customer requests, recommend replies, and prepare case notes. Human agents remain responsible for judgment and final decisions, but they work faster and more consistently.
Productivity, however, is not the same as quality. Businesses still need to track incorrect answers, repeated contacts, escalation quality, and whether agents become overly dependent on AI suggestions.
The strongest AI service systems do more than respond quickly. They help less experienced employees perform closer to expert level while preserving human control for unusual, emotional, or high-risk cases.
**Research basis:** NBER, “Generative AI at Work.”
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