Slack estimates that the average user sends 70 messages per day, meaning that it can be difficult to keep track of conversations and know which messages are relevant.
Slack’s solution is to experiment with and introduce Artificial Intelligence (AI) to improve communication and collaboration. In early 2016, the startup hired Stanford-trained computer scientist Noah Weiss to make the platform smarter and more useful.
Over the past year and a half, Slack has used machine learning to enable faster, more accurate information searches within Slack and identify which unread messages are likely to matter most to each user.
Some of the technology is already live. One feature shows which people within a company talk about particular topics most often in Slack and where those discussions take place. The information, which appears when users conduct searches in Slack, is meant to pinpoint subject experts so people can direct questions to their most knowledgeable and accessible colleagues. Another feature, added last year, evaluates all of a user’s unread messages, across all Slack channels; highlights up to 10 of the ones its algorithms deem most important; and presents them in a single list.
Stewart Butterfield, the Slack CEO, sees AI as a long game. “I think what we have right now is good,” he says. “In a couple of years, it will be very good. In about five years, it will be excellent. And in 10 years it will be impossible to work without it.”