Generative AI to Expand Google Cloud TAM, Driving GPU/ASIC Demand Through 2030
Bernstein projects generative AI will expand the total addressable market for infrastructure services, boosting demand for GPU/ASIC and CPU capacity across major hyperscalers like Google Cloud through 2030. Within PaaS, AI-native database solutions will drive migration from on-premise to cloud, creating new revenue layers and reinforcing Google’s software ecosystem resilience.
1. Long-Term Growth Drivers
Bernstein’s outlook projects generative AI to expand the total addressable market for cloud infrastructure by fueling demand for specialized compute resources. Google Cloud is positioned to capture a growing share of GPU/ASIC and CPU capacity sales as enterprises ramp up complex AI training and inference workloads through 2030.
2. Infrastructure-Layer Benefits
The Infrastructure-as-a-Service and Platform-as-a-Service layers stand to gain most from AI-driven workloads. Surging requirements for high-performance GPUs and custom ASICs will translate into higher CAPEX spending and unit sales for Google’s data center operations, underpinning sustained revenue growth.
3. PaaS and Database Migration
In the PaaS layer, AI-native database solutions are expected to accelerate migration from legacy on-premise systems to managed cloud offerings. Google Cloud’s database portfolio, including BigQuery and AlloyDB, could see heightened adoption as enterprises seek optimized performance and scalability for AI applications.
4. Strategic Implications for Google
Investors should monitor Google’s ability to bridge traditional software needs with compute-intensive AI demands. Success in scaling agentic AI infrastructure could unlock new revenue streams, reinforce Google Cloud’s competitive position against other hyperscalers, and drive valuation upside.