Finding Value in AI's “Five-Layer Cake”

Artificial Intelligence (AI) investment is gathering intense momentum, cementing its position as one of the most prominent focal points in global markets. However, AI is far from a standalone sector; it operates much like an evolving ecosystem. Powering this ecosystem behind the scenes are computing infrastructure, hardware chips, and data centers. On the application front, it spans diverse products and services across technology, manufacturing, healthcare, and financial services.

To uncover compelling opportunities in this new AI era, investors should evaluate the dynamics across each segment of the ecosystem. This enables market participants to discern which areas remain attractive and where structural challenges are beginning to emerge.

Nvidia coined the term "five-layer cake" to describe the AI ecosystem as a comprehensive, full-stack industrial infrastructure, encompassing the entire value chain across five key layers:

Each layer of the "cake" encompasses a distinct set of companies. With market focus shifting rapidly, different segments of the AI ecosystem rotate over time, leading to frequent changes among market leaders.

Allianz Global Investors has established an analytical framework to help investors evaluate the AI ecosystem layer by layer—addressing core questions to assess whether the investment thesis for each segment remains intact.

Applications: Does AI create measurable economic value?

For AI spending to remain structural rather than cyclical, the technology must deliver measurable economic benefits. For businesses, that means higher productivity, stronger revenue growth or lower costs.

Models: Which model providers can capture pricing power?

The profitability of artificial intelligence models is one of the biggest uncertainties in the entire ecosystem. Competition among leading model providers, the rise of more efficient lower-cost and open-source/open-weight architectures and the shifting cost of training models raise important questions about pricing power and market structure.

Infrastructure: Can AI hardware be turned into usable computing capacity?

Demand for AI applications creates economic value only when purchased hardware is converted into usable computing capacity for training and running AI models. Cumulative spending by hyperscalers (the cloud providers building the AI infrastructure) and data centre development activity across planning, construction and operational phases.

Chips: Is AI semiconductor demand growing?

This layer focuses on the scale of and growth drivers for thesemiconductor demand. Key indicators to watch include market-based measures of AI compute demand, AI accelerator shipments, shifts in demand for high-quality versus cheaper chips, GPU rental prices over time, and chip replacement cycles.

Energy: Where will the power come from to run and scale AI capacity?

AI is power hungry. Grid capacity and electricity costs play a growing role in determining how quickly new AI capacity is deployed and how efficiently existing data centres can operate.

AI presents vast investment opportunities; however, with technology advancing and commercial adoption unfolding at a rapid pace, investors must stay ahead of emerging trends to discern true, lasting value.

Source: Allianz Global Investors, 31 July 2026, “Find Value in the AI Stack”.

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