To measure if an AI agent helps or hinders customer support, one must analyze several key performance indicators. Crucially, observe changes in average handle time (AHT) and first contact resolution (FCR) rates; a reduction in AHT and an increase in FCR indicate efficiency gains. Simultaneously, monitor customer satisfaction (CSAT) scores and Net Promoter Scores (NPS), as positive trends here confirm improved customer experience, not just speed. Conversely, if the AI creates more work, you'll see agents spending significant time correcting AI errors, escalating issues initially handled by AI, or even dealing with an increase in follow-up tickets due to incomplete AI interactions. Additionally, assess agent feedback regarding task automation and workload; an increase in agent frustration or burnout suggests the AI isn't truly supportive. Finally, track the overall volume of support interactions and the proportion handled autonomously versus those requiring agent intervention, looking for a clear reduction in agent-handled contacts for simpler queries. More details: https://www.labico.gr/BannerClick.php?BannerID=11&LocationURL=https://infoguide.com.ua/