The debate around network effects in ChatGPT‘s growth model highlights a critical business strategy question for OpenAI as it seeks to maintain market dominance in the rapidly evolving large language model landscape. The company’s massive $300 billion valuation rests partly on assumptions about how network effects will help it secure lasting competitive advantage, though these effects appear weaker than those seen in other tech platforms.
The big picture: OpenAI is banking on two types of network effects to maintain its competitive edge in the large language model (LLM) market, though both appear to be weaker versions of patterns seen in other successful tech platforms.
- Data network effects from growing user interactions are helping improve the product, similar to but less potent than those powering Google’s search dominance.
- Cross-side network effects between users and GPT builders resemble the dynamic between iPhone users and app developers, though with less strength.
Why this matters: These network effects form a central pillar in justifying OpenAI’s extraordinary $300 billion valuation, suggesting investors believe the company can establish lasting market leadership.
Behind the numbers: Unlike traditional platform businesses where network effects create overwhelming market dominance, the LLM market may see more fractured competition if these effects prove weaker than anticipated.
- Google’s search dominance came from powerful data network effects where more users generated better search results, creating a self-reinforcing cycle difficult for competitors to match.
- Apple’s iOS ecosystem thrived on strong cross-side network effects where more users attracted more developers, which in turn attracted more users.
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