📰 Key Takeaways

OpenAI has released “OpenAI Signals” data analyzing how ChatGPT is used at work. The data covers about 100 countries and breaks users’ work usage into 165 work activities, showing how people actually use ChatGPT on the job. Besides looking at the usage distribution across activities, the data also tracks how these patterns change over time, so outsiders can see how ChatGPT is spreading across different countries and types of work, and which work activities are growing in share. The original summary only describes the scope and angles of the analysis, and doesn’t give specifics like usage percentages, rankings, or per-country numbers. See the original link for details.

💬 JudyAI Lab’s Take

OpenAI just released OpenAI Signals, which breaks down ChatGPT’s workplace usage across about 100 countries into 165 work activities. What’s worth noticing is that it doesn’t look at “who’s using it,” but at “what they’re using it for.”

Past talk about AI adoption mostly stopped at the number of users or how often they use it. This data uses work activities as the unit of analysis, which is basically admitting that AI’s value isn’t in replacing a whole occupation, but in cutting into the individual tasks inside it. For AI builders, this is a really practical way to think about design: instead of slapping a job-title label on your product like “for marketers” or “for engineers,” ask what exactly your users are doing and which step eats the most time. The data also tracks changes over time along with how usage spreads across countries and types of work, which is a reminder that usage behavior moves. Today’s mainstream use isn’t necessarily the mainstream use six months from now. The original summary doesn’t give specific percentages or rankings, so you’ll still need to check the original for details.

My suggestion: break your own product’s use cases into a list of work activities the same way, find the ones whose usage share is growing, and put your resources there first.

📅 Original Info

🔗 Further Reading