This page compiles evidence on how AI product launches drive adoption and revenue spikes, drawing on OpenAI and Anthropic disclosures, TechCrunch reporting, OpenAI’s “How People Use ChatGPT” research, and public AI model release trackers.
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 launch-to-adoption is the clearest pattern in this category: unlike seasonality (which is weak for AI), launch effects are large, repeated, and visible in independent data — user milestones, message-mix shifts, and revenue jumps all cluster around releases. We pair disclosed metrics (WAU milestones, the measured image-gen spike) with the launch timeline so the cause-and-effect is legible.
Methodology notes: WAU milestones are disclosed irregularly by OpenAI, so the curve’s exact timing is approximate and the steps are not evenly spaced in time. The image-generation spike (multimedia ~2%→7%) is from OpenAI’s own usage research and is a clean measured example. Revenue effects (Claude Code) are from company/press reporting on run-rate, not audited figures. Attributing a usage jump solely to a launch is a simplification — marketing, seasonality, and competitor moves overlap — but the launch correlation is strong and repeated.
Sources used on this page:
- TechCrunch — ChatGPT: Everything to Know 2026 (WAU milestones; GPT-4o spike)
- OpenAI — How People Use ChatGPT 2025 (measured image-gen spike)
- Evertune — AI Model Release Tracker 2026 (launch timeline)
- SQ Magazine — Claude vs ChatGPT Statistics 2026 (Claude Code revenue after Claude 4)
Corrections or suggestions: research@aibehaviorindex.org