Average Handle Time (AHT)
A legacy support metric measuring the average duration of customer interactions. In AI-first support models, AHT becomes less meaningful for human agents as they shift from handling volume to resolving complex, time-intensive issues that AI cannot address.
Why AHT Breaks Down with AI
Average Handle Time was designed for a world where support teams managed high volumes of relatively similar queries, and efficiency meant moving through them quickly. Lower AHT indicated better productivity and often correlated with cost savings.
But when AI Agents handle the majority of straightforward queries, human agents are left with edge cases, sensitive situations, and emotionally charged issues that require more time, empathy, and judgment. In this context, AHT naturally rises—but that's a sign of impact, not inefficiency. Longer handle times reflect the complexity and value of the work humans are now doing.
Measuring Human Performance Differently
In AI-first organizations, teams need to move beyond volume-based metrics like AHT and instead focus on outcome and value metrics: resolution quality, customer satisfaction on complex issues, contribution to system improvement, and strategic impact. The goal isn't to handle conversations faster—it's to deliver meaningful value in every interaction.
For AI Agents, speed remains important because instant responses are part of the customer experience value proposition. But for human agents in an AI-first model, time spent should reflect the genuine complexity of the work, not arbitrary efficiency targets designed for a different era.