Despite fears that cheaper, open-source models would commoditize the market, the opposite is happening. While token usage for cheaper models is rising, the actual share of economic value (wallet share) is increasingly flowing to expensive frontier labs like Anthropic and OpenAI.

OpenAI and Anthropic form a powerful duopoly at the "frontier" of AI, commanding premium prices like Apple. A second, commoditized tier of open-source and lagging models exists, where value is captured through compute and services, not the model itself. This creates a clear market separation between premium and "good enough" AI.

Large AI firms like Anthropic are advocating for stringent government regulation under the guise of safety. However, these proposed rules also serve to raise the barrier to entry, making it more difficult for cheaper, open-source models and startups to compete, thus protecting the incumbents' market share.

Leading AI companies, like Anthropic, are accused of manufacturing fear about AI's dangers to push for a pre-approval system for new models. This creates a regulatory moat that protects their market lead by boxing out smaller startups that can't navigate the bureaucracy.

Creating frontier AI models is incredibly expensive, yet their value depreciates rapidly as they are quickly copied or replicated by lower-cost open-source alternatives. This forces model providers to evolve into more defensible application companies to survive.

As enterprises replace expensive proprietary models with cheaper open-source alternatives, frontier labs like OpenAI and Anthropic face an existential threat. Their strategic response could be to lobby for regulations that effectively make open-source models illegal, creating a protective moat.

The breathless talk about AI's dangers from leaders of large AI labs isn't just about safety; it's a business strategy. By encouraging regulation, established players like Anthropic can create a 'regulatory moat' that makes it harder for smaller competitors to enter the market.

The long-term success of AI business models depends on a central tension: can providers like Anthropic control the 'dials' on token usage to maximize profit, or will transparent marketplaces and user choice commoditize compute? This determines whether AI becomes an incredible business or a low-margin utility.

The push for AI regulation, often led by companies like Anthropic, is likely leading toward an attempt to ban open-source models. The justification will be that open models lack guardrails and are therefore dangerous, effectively cementing the power of a few closed-source providers.