Competing Spheres of Artificial Intelligence: Infrastructure Providing a Competitive Edge on a Global Scale
In the ever-evolving landscape of technology, the race for artificial intelligence (AI) dominance is not about building the smartest chatbot, but rather who owns the rails. This shift in focus towards infrastructure control has become increasingly apparent as application and platform companies grapple with margin pressure due to infrastructure costs.
In the telecom boom of the past, real power accrued to those who controlled undersea cables and spectrum, not to long-distance carriers. Fast forward to the present, and the same principles apply in the AI realm, with Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), IBM Cloud, Oracle Cloud, Alibaba Cloud, and SAP emerging as the key infrastructure providers.
Amazon leads the market, operating numerous global data centers and boasting the largest compute capacity. Its strength lies in distribution, making it the default choice for many startups. Google, on the other hand, integrates cutting-edge research with custom hardware, giving it hardware-level control others cannot easily replicate, thanks to its TPU stack.
Microsoft leverages its partnership with OpenAI to assert enterprise dominance and integrates AI into Office, Teams, and its hybrid cloud, ensuring it owns the enterprise gateway. Microsoft Azure ties infrastructure to enterprise workflow, with its strategy being integration as a moat.
The market organizes into a value capture hierarchy with infrastructure providers at the top, platform companies in the middle, and application developers at the bottom. This hierarchy is evident in the AI scaling success, which depends more on infrastructure control than on algorithm innovation.
As adoption scales, value capture favours infrastructure providers, forcing application companies into a strategic bind: how to differentiate when the foundation is owned by someone else. This dynamic is reminiscent of the internet wave, where companies that owned hosting, bandwidth, and operating systems endured, while most dot-com applications vanished.
SAP focuses on sovereign cloud solutions, with data centers primarily in Europe, targeting regulated sectors to meet regulatory requirements and digital sovereignty. This approach underscores the compounding nature of infrastructure, where control translates into structural and slow-moving barriers to buildouts.
In the railroad era, fortune was made by those who owned the tracks, not by the companies running train services. In the AI era, this analogy rings true, with infrastructure providers enjoying the highest margins and the deepest control. While application developers scale revenue, they remain customers of both platforms and infrastructure.
The AI race is, therefore, a battle for infrastructure control and the management of compute, data, and distribution. As we move forward, it will be interesting to see how this dynamic evolves and who will emerge as the dominant players in the AI landscape.
