Bad news: your AI application isn't that special

image via TechRadar

August 13, 2026, 2:40 PM

• •The author divides the market into AI infrastructure tools such as orchestration, monitoring, and governance, and surface applications such as underwriting assistants or contract review tools.
• •He argues that infrastructure layers historically consolidate because large platforms can absorb adjacent capabilities and offer them as built-in features.
• •The piece compares the AI boom with prior technology cycles including the dot-com era, cloud computing, and the modern data stack.
• •It says falling development costs have enabled a surge of AI startups, but quality alone is no longer a durable competitive advantage.
• •The author identifies three main moats for AI application companies: proprietary operating data, distribution, and workflow integration.
• •The article concludes that competition among many AI vendors will likely transfer much of the economic value to enterprise customers.

The article argues that today’s AI market is splitting into infrastructure companies and end-user application companies, with the infrastructure layer likely to consolidate into a small number of dominant platforms. Drawing on the dot-com boom, cloud computing, and the modern data stack, the author says most standalone AI infrastructure vendors will be acquired, copied, or squeezed out by hyperscalers and model providers. He contends that AI application startups face a separate problem: low development costs and strong tools mean many products are good, but few are truly differentiated. In his view, the durable winners will be companies with proprietary data, built-in distribution, or deep integration into customer workflows, while much of AI’s value will accrue to buyers rather than sellers.

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