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Big Technology Podcast · 3 min · Jul 30, 2025

Enterprise customers may value model improvements more than consumers

Dario Amodei says Anthropic prioritizes business users because model improvements can create more value for firms than consumers. His biochemistry example explains why enterprise buyers may pay for capabilities most consumers barely notice.

Dario Amodei

Dario Amodei is CEO of Anthropic.

Co-founded Anthropic, the AI safety company behind Claude; earlier led OpenAI's GPT-2 and GPT-3 research.

  • Alex Kantrowitz, Host · Founder, Big Technology

    Former BuzzFeed News senior tech reporter and author of Always Day One.

About this segment

Dario Amodei says Anthropic prioritizes business users because model improvements can create more value for firms than consumers. His biochemistry example explains why enterprise buyers may pay for capabilities most consumers barely notice.

From “Anthropic CEO Dario Amodei: AI's Potential, OpenAI Rivalry, GenAI Business, Doomerism”, Jul 30, 2025. Watch the full episode

“Our view is that, if anything, the enterprise use of AI is going to be greater even than the consumer use of AI, right?”
Dario Amodeiat 24:10 · Big Technology Podcast24:10

Takeaways

  1. Anthropic focuses on businesses, developers and power users.
  2. A higher biochemistry skill level could matter greatly to a pharmaceutical company.
  3. Enterprise buyers may pay for improvements most consumers do not notice.

In this episode

Full episode
  1. 3:28AI timelines hinge on an exponential, not an AGI label6:22
  2. 29:46Each model can make money while the company spends at a loss6:46
  3. 58:51Safety needs to advance alongside increasingly capable AI6:31
  4. 11:36Context windows can cover some continual-learning gaps3:43
  5. 16:13Anthropic kept fixed pay levels during Meta's recruiting push4:08

  6. 23:34Enterprise customers may value model improvements more than consumers2:49

  7. 36:35Open weights do not make AI models work like open-source software3:38Up next
  8. 53:54Anthropic publishes safety policies for rivals to adopt2:56

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

  1. 23:39

    Like, you know, OpenAI might be betting on ChatGPT and Google might be betting on the fact that no matter where the technology goes, it can, you know, integrate into Gmail and Calendar. So why have you made this bet on this, the pure bet on the tech itself? Yeah, I mean, I would say I wouldn't quite put it that way. I think we've, I would describe it more as we've bet on business use cases of the model, more so than we've bet on the API per se.

  2. 24:03

    And it's just that the first business use cases of the model come through the API. So, you know, as you mentioned, OpenAI is very focused on the consumer side. Google is very focused on kind of the existing products that Google has. Our view is that, if anything, the enterprise use of AI is going to be greater even than the consumer use of AI, right? I should say the business use because it's enterprise, it's startups, it's developers and it's kind of, you know, power users using the model for productivity.

  3. 24:32

    I also think that being a company that's focused on the business use cases actually gives us better incentives to make the models better. A thought experiment that I think is worth running is, you know, suppose I have this model and it's, you know, it's as good as an undergrad at biochemistry. And then I improve it and it's as good as a PhD student at biochemistry. If I go to a consumer, right, if I give them the chat bot and I say, great news, I've improved the model from, you know, undergrad to graduate level in biochemistry, you know, maybe, I don't know, 1% of consumers care about that at all, right?

  4. 25:12

    99% are just going to be like, I don't understand it either way. But now suppose I go to Pfizer and I say, you know, I've improved this from undergrad at biochemistry to grad at biochemistry. Like this is going to be the biggest deal in the world, right? They might pay 10 times more for something like that. It might have 10 times more value to them. And so the general aim of making the models solve the problems of the world to make them smarter and smarter, but also able to bring many of the positive applications, right?

  5. 25:41

    The things I wrote about in like Machines of Loving Grace of like solving the problems of biomedicine, solving the problems of geopolitics, solving the problems of, you know, of economic development, you know, as well as more prosaic things like finance or legal or productivity or insurance, I think it gives a better incentive to kind of develop the models as far as, as, as, as. as far as possible. And I think in many ways, it's like it may even be a more positive business.

  6. 26:15

    So I would say we're making a bet on the business use of AI because it's most aligned with kind of