Michelle Tabart

Imagine you’re looking for a specific bakery in a maze of narrow city streets. Your maps app is technically flawless, giving real-time directions and rerouting perfectly. But you’re still lost, squinting at your phone and second-guessing every corner. Your cognitive load is through the roof. Eventually, you close the app and ask a local for help. This is workflow breakage in action. The system was correct, but it failed to meet you where you were.

AI agents are quickly becoming the backbone of enterprise productivity. They promise faster resolution times, better efficiency, and happier customers. But for those designing agents, we face a critical challenge: a technically “working” agent, with excellent system accuracy scores, can still be perceived by the user as not providing value, or even not worth using. Our latest internal research on end user perspectives highlights a crucial gap.

Agentforce is transforming how work gets done, from triaging cases to querying records and engaging customers. Even as adoption accelerates, the question remains: How much time do agents actually save us? If a task takes a human five minutes and now an agent can do it in seconds, does that mean we’ve saved five minutes? The answer isn’t so straightforward, because that logic assumes that the task was clearly defined, frictionless, and self-contained.