AI adoption isn't linear. A small, 1% improvement in model capability can be the critical step that clears a usability hurdle, transforming a "toy" into a production-ready tool. This creates sudden, discontinuous leaps in market adoption that are hard to predict from capability trend lines alone.

Unlike previous tech waves that trickled down from large institutions, AI adoption is inverted. Individuals are the fastest adopters, followed by small businesses, with large corporations and governments lagging. This reverses the traditional power dynamic of technology access and creates new market opportunities.

Unlike previous top-down technology waves (e.g., mainframes), AI is being adopted bottom-up. Individuals and small businesses are the first adopters, while large companies and governments lag due to bureaucracy. This gives a massive speed advantage to smaller, more agile players.

Anthropic's Cowork isn't a technological leap over Claude Code; it's a UI and marketing shift. This demonstrates that the primary barrier to mass AI adoption isn't model power, but productization. An intuitive UI is critical to unlock powerful tools for the 99% of users who won't use a command line.

Unlike COVID's growth, which had a hard population limit, AI's potential is tied to energy and computation, which have vast room to expand. However, its real-world application will manifest as a series of S-curves, as different technologies and industries hit temporary plateaus before the next breakthrough occurs.

Unlike electricity or the internet itself, which required massive physical infrastructure build-outs over decades, AI can be "downloaded" instantly by 5+ billion people. The internet acts as a pre-built carrier wave, enabling a rate of adoption never before seen in technological history.

The history of AI tools shows that products launching with fewer restrictions to empower individual developers (e.g., Stable Diffusion) tend to capture mindshare and adoption faster than cautious, locked-down competitors (e.g., DALL-E). Early-stage velocity trumps enterprise-grade caution.

The recent explosion in AI adoption wasn't solely due to better models, but because the chat interface made the technology accessible to anyone. For the first time, non-technical users could interact with a powerful AI without prescriptive instructions, making its capabilities feel tangible and widespread.

Unlike Web3, which required building an entirely new ecosystem, AI's power lies in its seamless integration into existing workflows. Because there's no friction to adoption and the cost of creation is dropping to zero, its societal impact will be faster and more widespread than previous technological shifts.