What Is the Rule for Picking AI Winners? | The a16z Show

TL;DR

The rule for identifying AI winners is to evaluate scale, value capture, adoption, and where enterprises will fund rising AI costs. Anthropic and OpenAI are already adding more monthly revenue than Meta, Google, or Microsoft, while diffusion into the real economy remains below 5%. Read on for the revenue benchmarks, adoption signals, cost pressures, and business changes shaping the opportunity.

Transcript

Anthropic and OpenAI are adding more revenue per month than Meta, Google or Microsoft. And I wouldn't be surprised if the combination of those two companies is [music] doing 200 billion of revenue run rate. Between 2020 and 2024, top 1% exit started at $10 billion. We updated those numbers in February this year, $20 billion. We just updated them ye... Read More

Key Insights

• Anthropic and OpenAI are adding more monthly revenue than major tech companies like Meta and Google.
• AI's current diffusion into the real economy is less than 5%, indicating vast growth potential.
• Enterprises will need to allocate significant resources to integrate AI, impacting their profit structures.
• The future of AI includes both open-source and proprietary models, with cost being a critical factor.
• The rapid pace of AI development suggests a shift from reactive to proactive business applications.
• Native AI companies operate differently, focusing on product innovation rather than solely on automation.
• The AI market is expected to grow significantly, with top 1% company exits increasing tenfold in recent years.
• Supply constraints, such as data center capacity, currently limit AI expansion, reducing bubble risks.

Questions & Answers

Q: What is the rule for picking AI winners on The a16z Show?

Evaluate both scale and value capture. The discussion focuses on how quickly AI companies add revenue, how little the technology has diffused into the real economy, and where enterprises will find the money to pay for adoption.

Q: How quickly are Anthropic and OpenAI growing revenue?

Anthropic and OpenAI are adding more revenue per month than Meta, Google, or Microsoft. The speaker says their combined revenue run rate could reach $200 billion by the end of this year.

Q: How widely has AI diffused into the real economy?

AI diffusion into the real economy is described as less than 5%. Adoption is more advanced in coding and tech-forward companies, but most other enterprise functions remain far from full utilization.

Q: Why could enterprise AI adoption produce extraordinary outcomes?

Leading AI companies are already adding more revenue than the hyperscalers while economic diffusion remains below 5%. The speaker expects usage to take off when models and the products built around them become very good.

Q: How could AI spending affect Fortune 500 profits?

The Fortune 500 or S&P 500 collectively generates about $2 trillion in profit per year. A $200 billion combined revenue run rate for Anthropic and OpenAI would represent roughly 10% of that profit, before including open source and other vendors.

Q: Why could open-source and local AI become important?

Enterprises will have to determine where the money for AI purchases comes from. The speaker says cost will make open-source and local options important sooner than previously expected.

Q: Which jobs show early signs of AI adoption beyond coding?

The speaker sees early adoption in other white-collar work, including legal. Legal is smaller than coding, but it illustrates how usage can rise when models and surrounding products improve.

Q: How will native AI applications change enterprises?

Companies have barely begun changing how they are run because of AI. At strong companies, resources are directed mainly toward products and new initiatives rather than automating existing operations, because the product opportunity is viewed as larger.

Summary & Key Takeaways

• Definition: AI winners are assessed through scale and value capture, including revenue growth, diffusion, enterprise spending, and product adoption.

• Number: AI diffusion into the real economy is less than 5%.

• Number: Anthropic and OpenAI could combine for a $200 billion revenue run rate by the end of this year.

• Number: Fortune 500 or S&P 500 companies collectively generate about $2 trillion of profit per year.

• Number: The projected AI revenue run rate equals roughly 10% of Fortune 500 profit.

• When: Between 2020 and 2024, the top 1% exit threshold started at $10 billion.

• When: The top 1% exit threshold was updated to $20 billion in February and then to $32 billion yesterday.

• Compare: Anthropic and OpenAI are adding more monthly revenue than Meta, Google, or Microsoft.

• Compare: AI adoption is advanced in coding and tech-forward companies but remains limited across most other enterprise functions.

• Tool: Open-source and local AI options become more important as enterprise costs rise.

• Who: Strong companies devote resources mainly to products and new initiatives rather than automating how they operate.

• When: Adoption across additional organizational functions and verticals is expected over the next 12 months.