Top AI Stocks to Watch as Tech Valuation Reaches New Heights
With Anthropic filing for an IPO and OpenAI following close behind, we analyze the top AI stocks, infrastructure providers, and cloud giants to watch.
The announcement of Anthropic’s confidential IPO filing at a potential $1 trillion valuation marks a turning point in public market history. As the first pure-play generative AI giant prepares to go public, investors are scrambling to identify the companies best positioned to capture the value of this technological shift.
For years, investing in AI was limited to buying mega-cap cloud giants or hardware vendors. With pure-play model developers entering the public markets, the landscape is shifting. Here are the top categories and stocks to watch.
The Infrastructure Layer (Hardware & Fabricators)
Without chips, there is no AI. The hardware layer remains the most profitable segment of the AI economy:
- NVIDIA (NVDA): The undisputed leader in AI chips. While competitors are emerging, NVIDIA’s software stack (CUDA) remains a powerful competitive moat.
- TSMC (TSM): The semiconductor fabricator responsible for manufacturing almost all advanced AI chips.
- ASML: The sole manufacturer of extreme ultraviolet (EUV) lithography systems needed to print advanced chips.
The Cloud Providers (Compute & Distribution)
Training and serving frontier models requires massive cloud infrastructure. These giants also benefit by owning a share of the model builders:
- Microsoft (MSFT): The primary host and distributor of OpenAI’s models, alongside its own in-house MAI-Thinking-1 model.
- Amazon (AMZN): A major investor in Anthropic, integrating Claude directly into AWS Bedrock.
- Alphabet (GOOGL): Hosting Gemini and investing heavily in Anthropic’s cloud compute needs.
At $1 trillion, Anthropic’s IPO is a massive bet on whether AI software margins can scale to match the capital expenditures spent on hardware.
The Pure-Play Software Layer
As Anthropic and eventually OpenAI list on public exchanges, investors will finally have direct access to pure-play AI software. The key metric to watch will be inference economics—whether model builders can lower the cost of serving queries fast enough to turn a profit on enterprise API contracts.
