### ‘Selling coffee beans to Starbucks’ — how the AI boom could leave AI’s biggest companies behind
The AI revolution is here, and at its heart are the giants investing billions to develop powerful foundational models and the infrastructure to run them. These companies, the creators of the cutting-edge “brains” of tomorrow, seem poised to dominate. Yet, an intriguing parallel to the coffee industry suggests a different future: they might become the digital equivalent of coffee bean suppliers, while others capture the lion’s share of value by building the “Starbucks.”
Imagine the company that sells raw, high-quality coffee beans. Their product is essential, requiring significant investment in farming, processing, and logistics. But the brand that grinds those beans, brews them into a specific drink, creates an experience, and sells it directly to the customer – Starbucks – commands a vastly higher margin and brand loyalty.
In the AI landscape, the “coffee bean” producers are the developers of large language models, image generators, and the underlying cloud compute. They pour immense resources into R&D, data acquisition, and training, creating the raw intelligence that fuels the boom. Without their innovations, nothing else is possible.
However, the true value capture might increasingly shift to the “Starbucks” companies: those building specialized, user-facing applications on top of these foundational models. These are the firms integrating AI into specific workflows, creating niche solutions for particular industries, or developing consumer products that solve precise problems. They brand these solutions, own the customer relationship, and provide the tailored “experience.”
As foundational models become more powerful and, crucially, more accessible (through APIs, open-source alternatives, or even fine-tuned versions), the underlying intelligence itself risks commoditization. When multiple companies can offer similar levels of basic AI capabilities, the differentiator shifts from the raw “beans” to the refined “coffee.” The application layer, with its focus on user experience, unique integrations, and specialized problem-solving, can command premium pricing and build defensible moats.
While the foundational AI companies are indispensable, their ultimate challenge will be to avoid becoming solely a utility provider. Without strategic moves into the application layer or innovative value capture models beyond mere API access, they risk watching others transform their expensive, complex “beans” into highly profitable, branded “coffees,” leaving the originators with the essential but potentially less lucrative role in the AI supply chain.