“Anthropic’s growth path is a lot easier to understand than OpenAI’s. Corporate customers are devising a plethora of money-saving uses for AI in areas like coding, drafting legal documents, and expediting billing.” — The Wall Street Journal

That line captures an important dynamic in today’s AI market: two companies building similar technology, but betting on very different ways to make it sustainable.

OpenAI is chasing scale — hundreds of millions of users, a consumer-facing brand, and a growing subscription base. Anthropic, by contrast, is growing through depth. Around 80% of its revenue now comes from corporate customers using Claude in coding, legal, and operational contexts. That focus has given it a quieter but steadier business profile, reportedly reaching a $7 billion annual run rate.

It’s interesting how this divide is shaping the landscape. OpenAI’s mass-market reach gives it visibility and data, but it’s still searching for a clear long-term revenue model beyond subscriptions. Anthropic’s enterprise-first approach, while less visible, ties directly to measurable outcomes: productivity gains, cost reductions, workflow acceleration. For now, that seems to be resonating with businesses that know exactly how to calculate return on investment.

“What I’m chasing is to bring to biologists the experience that software engineers have with code generation. You can sit down with Claude and brainstorm ideas, generate hypotheses together.” — Financial Times

This next quote signals how Anthropic is trying to deepen its foothold — not just in the enterprise, but within specific domains. The company is adapting Claude for life sciences, integrating it into lab management and genomic analysis systems.

The examples are telling. Novo Nordisk reportedly reduced clinical documentation from ten weeks to ten minutes using Claude. Sanofi says most of its employees already use it daily. That’s a different kind of AI adoption — one rooted in precision, compliance, and workflow design rather than consumer habit.

What stands out is Anthropic’s framing: Claude isn’t a scientist, it’s a scientific assistant. The focus is on amplifying human work rather than automating discovery. That seems to align with how heavily regulated industries adopt new technology; slowly, methodically, but with lasting impact once trust is established. Features like audit trails, reduced hallucinations, and citation verification make Claude fit for environments where accountability matters as much as performance.

Stepping back

These two stories together hint at an evolving market structure. OpenAI, Anthropic, Google, and others aren’t just competing on model performance anymore; they’re diverging on business logic. Some are building ecosystems around mass reach and developer tools. Others, like Anthropic, are going narrower — optimizing for reliability and use-case fit within high-value domains.

It’s too early to tell which model scales more effectively. Consumer AI could unlock entirely new markets if monetization catches up. Enterprise AI could plateau if integration costs remain high. But what’s clear is that the industry is experimenting with different paths to commercial maturity.

P.S.: Claude Code remains my favorite AI tool hands-down. Anthropic has a winner here.