Customer experience
What AI support productivity really means
A customer does not care how quickly an answer was generated if it is wrong. The useful question for AI in support is whether people can resolve the issue more effectively while preserving the judgment, accuracy and accountability the customer needs.
Help people find the right answer
A new team member may know that a policy exists without knowing where to find it. Useful assistance can shorten that search and suggest a starting point. The important asset is not the chat window. It is a trustworthy collection of current answers, clear boundaries and someone responsible for maintaining them.
Start by identifying repeated questions your staff can already answer reliably. Keep exceptions visible: refunds outside policy, unusual account circumstances or anything that requires verification should reach a person with authority. A confident guess is not a resolution.
Do not grade speed alone
Track whether the customer returns with the same issue, whether the answer was correct and whether an escalation was handled properly. Faster responses that create repeat contacts move work around instead of removing it. Include the time spent reviewing suggestions when calculating any gain.
Review outcomes separately for new and experienced staff. A tool that helps a beginner may interrupt an expert or encourage reliance on an answer that does not fit the situation. Let evidence determine where assistance belongs rather than requiring identical use from everyone.
Make improvement reversible
Pilot one queue with a defined review period and an easy fallback. Keep a record of incorrect suggestions, their source and the correction. Ask agents which recommendations they ignored and why. Those explanations can expose weaknesses that a response-time dashboard misses.
The takeaway
The opportunity is better-supported people, not a promise that every business will gain 15%. Judge the system by completed, correct resolutions and the customer’s experience.
Primary source
Generative AI at WorkErik Brynjolfsson, Danielle Li and Lindsey R. Raymond
Revised November 6, 2024
The research and reported findings belong to the named source. The practical recommendations are Lead Franchise’s interpretation; they are not the source’s endorsement of our services.