This page is an analytical myth-check rather than a single-dataset report. It draws on the Federal Reserve’s quarterly Real-Time Population Survey, product-launch timelines, and education-usage patterns to assess whether AI adoption exhibits genuine quarterly seasonality.
The AI Behavior Index is the research arm of OneChat AI, an integrated multi-model AI platform. We compile and analyze data from primary research sources to make AI adoption and market trends more accessible to journalists, researchers, and decision-makers.
Why we built this as a myth-check: we looked for a rigorous, repeating Q1-vs-Q4 seasonal pattern in AI adoption and did not find one. Rather than manufacture a seasonal narrative from noise, we present the honest conclusion — adoption is trend- and launch-driven, not season-driven — and clearly label the charts as illustrative analysis. The two genuine exceptions (education, enterprise budgets) are real but narrow, and we say so rather than overstating them.
Methodology notes: this topic lacks a clean published “seasonality of AI adoption” dataset — which is itself the finding. The charts are illustrative representations of the trend-vs-season relationship and the drivers of movement, not measured seasonal indices. Distinguishing “seasonality” (a repeating calendar effect) from “trend” (secular growth) and “shocks” (launches) is the analytical core. If rigorous seasonal-decomposition data on AI adoption is published, we will update this page with it.
Sources used on this page:
- St. Louis Fed — State of Generative AI Adoption 2025 (quarterly trend data)
- OpenAI — How People Use ChatGPT 2025 (launch-driven usage spikes)
- Federal Reserve — Monitoring AI Adoption 2026 (trend dominance)
Corrections or suggestions: research@aibehaviorindex.org