What 100 Trillion Tokens Reveal About How People Actually Are Using AI

There's a lot of speculation about how people are using AI. Productivity boosters. Coding assistants. Research tools. The assumptions tend to skew toward efficiency and output—getting more done in less time.

However, a new research paper from A16Z and OpenRouter describes their study which analyzed over 100 trillion tokens of real-world AI usage across the past year. A token is roughly a word or word piece, so this represents billions of conversations and prompts and is one of the largest empirical studies of how people actually interact with AI tools.

The most notable finding is that neither productivity enhancement nor software coding are the primary uses. Tthe finding that surprised a lot of people is that over 50% of open source model usage is for role play and creative storytelling.Programming does come in second, so the productivity use cases are real. But the dominant use of these tools is people engaging with AI for creative and social experiences. They're building fictional worlds, having conversations with characters, exploring narratives.

What does this reveal? People are drawn to AI for reasons beyond efficiency. There's something about the interactive, responsive nature of these tools that people find genuinely engaging. They're not just using AI to save time—they're using it because they enjoy the experience.

A year ago, handled a negligible share of total usage. Today, open source AI models account for roughly 30% of all token volume. Models like DeepSeek and Qwen have driven much of this growth. The practical implication: the AI landscape is diversifying fast. No single company or model has a permanent lock on the market. The tools available today will be different from the tools available in six months, often with expanded capabilities at lower cost.

It also means the barriers to AI adoption keep dropping. Capabilities that required expensive enterprise contracts two years ago are increasingly available through open source alternatives. Your smaller peer organizations aren't as far behind as you might think.

The Rise of Agentic Inference

AI usage is shifting from single-question, single-answer interactions to multi-step reasoning workflows. The study found that reasoning models now represent half of all usage. AI systems that plan, use tools, validate their work, and iterate. And prompt length has quadrupled—from about 1,500 tokens to over 6,000 tokens on average.

What's happening beneath the surface is even more dramatic. A single user inquiry might trigger dozens of separate AI prompts behind the scenes. One email asking a simple question could result in 300,000 to 700,000 tokens of processing as the system researches the person's history, checks relevant databases, validates facts, and refines the response.

Other Patterns Worth Noting

Anthropic's Claude handles over 60% of programming-related AI usage. That's the most concentrated category by any single provider.

Geography is shifting. North America now accounts for less than half of global AI usage. Asia has grown from 13% to 31%, with significant increases in Singapore, Germany, China, and South Korea. AI adoption is a global phenomenon, and the center of gravity is moving

How To Interpret This Data

The gap between how we talk about AI and how people actually use it is significant.

The headlines focus on productivity and automation. The data shows creativity and engagement are more predominant. The assumption is that AI usage is concentrated among technical professionals. The reality is that open source tools have democratized access and usage is spreading globally.

Most importantly, the shift toward agentic, multi-step AI means the ceiling on what's possible keeps rising. The AI tools of 18 months ago couldn't do what today's systems can do. And 18 months from now, the landscape will shift again.

The data from 100 trillion tokens tells a story about where AI is actually going. It's more creative, more distributed, more capable, and more accessible than the headlines suggest.

Click here for the full study research paper.