The AI Observatory: A Public Measure of Real-World AI Use

Understanding the benefits, risks, and impacts of general-purpose AI assistants requires looking at real conversations---not curated benchmarks or surveys. Yet AI use narratives rely on limited proprietary reports, or on few data sources, fragmented across platforms, models, and time. We introduce the AI Observatory, a public measurement platform that aggregates the most comprehensive set of real AI conversation sources, and develop a common taxonomy of 145 features, spanning function, topic, sensitive use, interaction style, multi-turn dynamics, and conversation structure. Across 23,158 conversations and 85,633 turns, we find that real AI use is highly heterogeneous: sources differ substantially in tasks, structures, and sensitive-use distributions, with no single source that generalizes. We further show that occupational summaries such as Anthropic's Clio capture an important but incomplete slice of use: 48\% of the conversations we analyze would be filtered out for being non-occupational, omitting substantial personal, social, cultural, and safety-relevant interaction. Real AI use is also not static: we find tokens and turns per conversation all rise sharply between 2023 and 2025, and we expose how model variants within the same developer support distinct usage regimes. The Observatory provides a new taxonomy, reusable annotation tools, and a public platform for reproducible measurement of how AI assistants are really used and evolving in the wild: \url{https://project-ai-observatory.vercel.app/}.