When assessing a business AI assistant, the quality of its answers rightly gets a lot of attention. But a factor just as decisive for real adoption is latency: how long passes between the request and the answer.
Why speed drives actual use
A tool that makes you wait several seconds for every interaction is experienced as an obstacle rather than a help, particularly during a call with a customer or while preparing a quote under time pressure. Even technically excellent answers lose value if they arrive too late to be useful.
Streaming as perceived mitigation
Showing the answer as it is generated, word by word, instead of waiting for the complete text, reduces perceived latency even when total processing time is unchanged: the user sees something happening straight away rather than staring at an empty wait.
The trade-off between depth and speed
Tasks needing more reasoning — complex calculations, multiple data checks — naturally take longer than a direct answer. The design challenge is to reserve slower, deeper processing for the tasks that genuinely require it, while keeping simple and frequent interactions fast.