Perhaps most telling in this entire report is Table 1. It shows that the non-work has grown 8x in 1 year, whereas work has only ~3.4x. Considering that non-work related usage of ChatGPT now makes up 73% of the requests, ChatGPT is very much in the consumer market, despite substantial marketing of LLM products in a professional context and even as much as compelled usage in some corporations.
Since many consumers are typically relatively tight-fisted in the b2c market, I don't think this bodes well for the long-term economics of the market. This may explain the relatively recent pivot to attempt to "discover" uses.
The chats alone are backbreakingly costly relative to the market mix of ChatGPT.
Rest of the market be damned -- combined with the poor customer mix (low to middle income countries) this explains why there has been such a push by the big labs to attempt to quantize models and save costs. You effectively have highly paid engineers/scientists running computationally expensive models on some of the most expensive hardware on the market to serve instructions on how to do things to people in low income countries.
This doesn't sound good, even for ad-supported business models.
> ChatGPT is widely used for practical guidance, information seeking, and writing, which together make up nearly 80% of usage. Non-work queries now dominate (70%). Writing is the main work task, mostly editing user text. Users are younger, increasingly female, global, and adoption is growing fastest in lower-income countries
# How People Use ChatGPT
(Chatterji, Cunningham, Deming, Hitzig, Ong, Shan, Wadman – Sept 2025)
### Scope
- Study of ChatGPT consumer plans (Free, Plus, Pro) from Nov 2022–Jul 2025.
- Covers ~700M weekly active users by mid-2025 (~10% of world’s adults).
- Uses automated, privacy-preserving classification of billions of messages.
---
### Key Findings
*Adoption & Growth*
- Usage grew 5× between mid-2024 and mid-2025.
- Growth from both new users and heavier use by existing users.
*Work vs. Non-Work*
- Mid-2024: ~47% work / 53% non-work.
- Mid-2025: ~27% work / 73% non-work.
- Shift due to both new cohorts and existing users expanding non-work use.
*Topics of Use*
- 3 main topics = ~80% of all use:
1. Practical Guidance (advice, tutoring, ideas)
2. Seeking Information (facts, search-like queries)
3. Writing (drafting, editing, summarizing)
- Technical help (e.g. coding, math) ≈ 4%.
*Work Activities (ONET mapping)*
- Common across occupations:
- Getting Information
- Documenting / Interpreting
- Problem Solving & Decision Making
- Thinking Creatively
- Advising/Consulting
*Demographics*
- Early skew male; now near gender balance.
- Younger users dominate; older users more work-focused.
- Strong growth in low- & middle-income countries.
- Higher education correlates with more work use.
*Quality / Satisfaction*
- Positive (“good”) user feedback outnumbers negative and is improving.
- Asking messages have highest satisfaction rates.
---
### Implications
- ChatGPT’s value is broad: not just coding/technical, but also decision support, writing, learning, and personal tasks.
- Increasing non-work use suggests large social value beyond workplace productivity.
- Broad relevance across occupations → general-purpose tool.
- Adoption trends point to narrowing gaps across gender and geography.
Since many consumers are typically relatively tight-fisted in the b2c market, I don't think this bodes well for the long-term economics of the market. This may explain the relatively recent pivot to attempt to "discover" uses.
I don't think this ends happily.
Rest of the market be damned -- combined with the poor customer mix (low to middle income countries) this explains why there has been such a push by the big labs to attempt to quantize models and save costs. You effectively have highly paid engineers/scientists running computationally expensive models on some of the most expensive hardware on the market to serve instructions on how to do things to people in low income countries.
This doesn't sound good, even for ad-supported business models.
> ChatGPT is widely used for practical guidance, information seeking, and writing, which together make up nearly 80% of usage. Non-work queries now dominate (70%). Writing is the main work task, mostly editing user text. Users are younger, increasingly female, global, and adoption is growing fastest in lower-income countries
# How People Use ChatGPT (Chatterji, Cunningham, Deming, Hitzig, Ong, Shan, Wadman – Sept 2025)
### Scope - Study of ChatGPT consumer plans (Free, Plus, Pro) from Nov 2022–Jul 2025. - Covers ~700M weekly active users by mid-2025 (~10% of world’s adults). - Uses automated, privacy-preserving classification of billions of messages.
---
### Key Findings
*Adoption & Growth* - Usage grew 5× between mid-2024 and mid-2025. - Growth from both new users and heavier use by existing users.
*Work vs. Non-Work* - Mid-2024: ~47% work / 53% non-work. - Mid-2025: ~27% work / 73% non-work. - Shift due to both new cohorts and existing users expanding non-work use.
*Topics of Use* - 3 main topics = ~80% of all use: 1. Practical Guidance (advice, tutoring, ideas) 2. Seeking Information (facts, search-like queries) 3. Writing (drafting, editing, summarizing) - Technical help (e.g. coding, math) ≈ 4%.
*Intent* - Asking (49%), Doing (40%), Expressing (11%). - Work-related chats skew toward Doing (esp. Writing tasks).
*Work Activities (ONET mapping)* - Common across occupations: - Getting Information - Documenting / Interpreting - Problem Solving & Decision Making - Thinking Creatively - Advising/Consulting
*Demographics* - Early skew male; now near gender balance. - Younger users dominate; older users more work-focused. - Strong growth in low- & middle-income countries. - Higher education correlates with more work use.
*Quality / Satisfaction* - Positive (“good”) user feedback outnumbers negative and is improving. - Asking messages have highest satisfaction rates.
---
### Implications - ChatGPT’s value is broad: not just coding/technical, but also decision support, writing, learning, and personal tasks. - Increasing non-work use suggests large social value beyond workplace productivity. - Broad relevance across occupations → general-purpose tool. - Adoption trends point to narrowing gaps across gender and geography.