Summary

In Q1 2026, ChatGPT consumer-plan usage broadened across inferred gender, age groups, and more countries. Users with typically feminine names surpassed parity among inferred-gender users and now account for over half of inferable users. Messages increased across all age cohorts, with users over 35 gaining share while under-35s remain the largest group. Country-level per‑capita rank gains were strongest in Latin America, Asia‑Pacific, and Africa (e.g., Dominican Republic +9, Haiti +9, Japan +8). Workplace activity on consumer accounts shifted from general content generation toward more specialized, repeatable tasks (notably content creation, health documentation, and information retrieval).

Note: this analysis covers only consumer plans (Free, Go, Plus, Pro) and excludes Codex, enterprise, and education products, so it understates total workplace and education usage.

Key Points

• Demographics: users with typically feminine names now represent >50% of inferable-gender messages; all age groups grew and 35+ users gained share.
• Geography: relative per‑capita rank increases concentrated in Latin America, Asia‑Pacific, and Africa; top movers include Dominican Republic (+9), Haiti (+9), Japan (+8), Mexico (+6), Brazil (+5).
• Workplace trends: growth in specialized tasks (content creation, health-related documentation, information retrieval); repeatable, recurring workflows increased on personal accounts.
• Methodological caveat: excludes Codex, enterprise, education — technical and coding activity is likely undercounted.
• Engineering implications: plan for broader regional capacity and localization, prioritize performance and reliability for repeatable workflows, instrument task types and workplace signals for product and safety monitoring.

Actionable takeaways for engineers

• Monitor per‑region capacity and latency as adoption spreads beyond established markets.
• Improve localization, i18n, and regional telemetry to capture emerging usage patterns.
• Optimize APIs and UX for repeatable workplace workflows (templates, retrieval, document handling).
• Continue tagging and distinguishing consumer vs. enterprise/Codex traffic to avoid underestimating technical usage.