What 700 Million ChatGPT Users Actually Do with AI - And What It Reveals About Workplace Strategies
Key takeaways
- OpenAI's study with Harvard and Duke analyzed 1.5 million messages from ChatGPT, which has 700 million weekly users.
- 49% of ChatGPT messages ask for advice, learning or decision support, against 40% that ask the model to perform a task.
- The asking category is growing faster and gets consistently better ratings from users, a sign that people want AI to support their thinking.
- Writing accounts for 42% of work-related ChatGPT messages, and two-thirds of those ask for edits to existing text.
OpenAI published a massive study of ChatGPT consumer usage in September, conducted jointly with Harvard and Duke. ChatGPT currently has 700 million weekly users, representing approximately 10% of the world's adult population. The study analyzed a total of 1.5 million messages. While the research tells us nothing about organizational AI usage, it reveals fascinating insights into how people use personal AI services.
The study's key finding is that 49% of ChatGPT messages fall into the "Asking" category - requests for advice, learning, guidance, and decision support. 40% of messages are "Doing" messages, requests to perform specific tasks. The Asking category is growing faster and consistently receives better ratings from users - people want AI to support their thinking and decision-making.
Notably, in work-related usage, writing dominates - 42% of work messages relate to text production. Even more interesting is that two-thirds of these requests involve editing existing text rather than creating new content. People don't want AI to replace their creativity but to enhance it.
This raises important questions about workplace AI strategies. As Microsoft Copilot, ChatGPT Enterprise, and other business tools become more common, are they focusing sufficiently on what people actually want? Consumer ChatGPT usage strongly suggests that AI's value comes as much from supporting decision-making as from task automation.
From an organizational perspective, this opens intriguing opportunities for expanding AI strategy. While AI-powered automation solutions help employees with routine tasks, it might be worth considering what kinds of AI solutions support workers' decision-making and creative problem-solving.
How does your organization balance AI utilization between automation and decision support?
#AIStrategy #DecisionSupport #OrganizationalDevelopment
Reference: How People Use ChatGPT – OpenAI, Harvard & Duke (2025)
Marko Paananen
AI consultant and builder with 20+ years in digital business development. Helps companies turn AI potential into measurable business value.
Follow on LinkedIn →Related Insights
Distributed AI Development: Strategy or Drift?
Distributed AI development can be a sound strategy, but if no one maintains the overall picture, competitive advantages might not be identified.
The Second AI Investment: Systems, Not Models
Most organisations have made their first AI investment. The second, building reliable systems around models, is where the real work begins.
AI's value moved from models to workflows - where organisations should focus
The bottleneck in AI is no longer model capability but workflow judgment. Organisations must identify where repeated decisions slow the business down.
Interested in learning more?
Contact us to discuss how your company can leverage artificial intelligence.