Who builds what, and why it matters
Every city needs foundations, power, roads, buildings, and people using them. AI is the same, just faster and more expensive.
Written by Matthew Bernath
Before any AI can run, someone has to build the specialised hardware. Normal chips can't handle it. AI needs to do millions of calculations at once, not one at a time.
Makes the leading AI chip (the GPU). Almost everyone uses them. The arms dealer of the AI war.
Makes competing chips. Cheaper than NVIDIA and catching up fast.
Trying to get back in the game after being late to AI. A turnaround story.
Actually manufactures the chips NVIDIA and AMD design. Nobody else builds at their scale. The factory everyone depends on.
Makes the machines that make the chips. One company, total monopoly, Dutch. No ASML, no modern chips.
Designs the chip architecture blueprint that almost every device uses. They license the design, they don't build the chips.
Make the networking chips that connect all those AI chips together at speed. The glue between the GPUs.
Make the memory chips. AI needs to store and retrieve data at extreme speed. These companies make that possible.
AI data centres use enormous amounts of electricity. A single large data centre can use as much power as a small city. Someone has to generate that power reliably.
Makes fuel cells that can power data centres without relying on the grid. Always on, no outages.
Nuclear and alternative energy plays. AI needs baseload power that solar can't guarantee on its own.
You need physical buildings stuffed with chips, cooled constantly, and connected to the internet at enormous speed. This is the real estate of the AI economy.
Own the biggest data centres on earth through AWS, Azure, and Google Cloud. They rent compute power to everyone else.
A newer data centre company built specifically for AI workloads. Rents NVIDIA GPUs at scale to anyone who needs them.
Started as crypto miners. Already own the buildings, power contracts, and cooling systems. Now pivoting to rent that infrastructure to AI companies.
Data has to move between chips, servers, and data centres at very high speed. These companies build the pipes and roads that make that movement possible.
Builds the switches that move data around inside data centres. The internal road network.
Make photonics components. Fibre optic connections that move data at the speed of light between data centres.
Satellite connectivity infrastructure. The long range road that connects remote areas and emerging markets.
This is where the actual AI gets built and run. The companies building the models that everyone else uses, and the platforms hosting those models.
Built Gemini. Owns DeepMind. Has the best data in the world via Search. The incumbent with the most to lose and the most to gain.
Built Llama (open source). Owns Instagram and WhatsApp, which generate enormous training data. Playing a different game to everyone else.
Owns a large stake in OpenAI (ChatGPT). Azure is how most businesses access AI. The enterprise distribution channel.
A lesser known European AI cloud company rebuilding from Russian tech origins. Early stage but interesting positioning.
Data platforms. AI is useless without clean, accessible data. These companies store, manage, and serve that data to the AI.
Companies building useful products on top of the AI models. These are the applications people and businesses actually interact with.
AI analytics for governments and large enterprises. Heavy defence and intelligence contracts. Controversial but deeply embedded.
Enterprise workflow software baking AI into everything. The quiet but essential layer of corporate IT.
Enterprise software with AI automation. Slower moving and less exciting, but well embedded in large organisations.
As much an AI company as a car company. Full Self Driving and the Dojo supercomputer are massive AI bets sitting inside a car manufacturer.
Fintech that benefits from retail enthusiasm around AI stocks. A meta play on the whole trend.
AI applications in biotech and insurance. Niche bets on AI transforming specific industries.
More AI means more attack surface. More data means more to steal. AI powered attacks need AI powered defence. The security layer grows in direct proportion to everything else.
Uses AI to detect and stop threats in real time. The endpoint security leader. Every laptop in a big company is probably running this.
Broad cybersecurity platform covering networks, cloud, and endpoints. One of the most comprehensive security stacks available.
Cloud native security. Protects companies where the perimeter no longer exists, when everyone works from anywhere.
Autonomous AI security platform. Detects and responds to threats without needing a human in the loop.
Founder & CEO, Alternata
Investor & portfolio thinker
I run Alternata, a data monetisation company built on a simple premise: most organisations are sitting on data assets they don't fully understand, let alone profit from. We help them change that.
The AI ecosystem is where I spend a lot of my thinking time, both as a practitioner building on these technologies and as an investor trying to understand where the real durable value gets created. There's a lot of noise. Most of it is either hype or fear. The actual story is more interesting than either.
My view is that the infrastructure layer (chips, power, data centres, connectivity) is where the most defensible businesses are being built right now. The application layer will produce enormous winners too, but it's harder to pick them early. The picks and shovels tend to win regardless of who discovers the gold.
This explainer is my attempt to map the ecosystem in plain language. Not for analysts. For anyone who wants to understand what's actually being built and why it matters.