Daniel Ives Highlights Nvidia and SpaceX as AI’s Next Wave Still Has Room to Run

Wall Street’s conversation about artificial intelligence is shifting from whether the technology will scale to how far its economic impact can spread. In that context, analyst Daniel Ives argued that Nvidia and SpaceX have more room to run, framing both companies as beneficiaries of an AI-driven buildout that extends beyond software and into the hardware and systems needed to run and support AI workloads.

For Nvidia, the case rests on its position in the compute stack. The company is widely associated with the chips and platforms that power AI training and inference, meaning its results typically track the intensity of demand from data centers deploying AI systems. Ives’ point, as presented in the report, is that this demand may not have fully played out and could continue to create incremental opportunities for Nvidia.

The report also elevates SpaceX in an AI-forward narrative, tying the company to the broader infrastructure required for global communications and data movement. While Nvidia is positioned as a direct supplier of compute, the argument for SpaceX appears more indirect: AI growth increases the need for connectivity, bandwidth, and network capacity, and SpaceX is often discussed in the satellite and launch ecosystem that supports those needs. The emphasis in Ives’ comments is that AI expansion can raise the ceiling for companies providing the enabling infrastructure.

Ives’ assessment is delivered in a comparative framing, with the implication that not all of the market’s winners have reached their long-term endpoints. The report characterizes the AI industry’s expansion as fast enough to keep raising expectations about its eventual economic footprint, and it places Nvidia and SpaceX among the names that could see benefits beyond near-term cycles.

The broader theme aligns with how investors think about AI exposure on multiple layers. On one layer are semiconductor suppliers and the data center equipment that runs AI models. On another are the logistics and communications systems that move data and connect networks at scale. That multi-layer view is a key reason AI equity narratives often extend to firms outside pure-play software and chip design.

Still, the report does not provide granular disclosures in the way a full earnings call or detailed investor presentation would. It does not break down specific price targets, model-by-model demand forecasts, contract wins, or quantified timelines for either company in the excerpted discussion. As a result, investors looking for confirmation on how quickly the runway is likely to translate into results would need more concrete data from company filings, investor materials, or subsequent analyst updates.

For Nvidia shareholders, the next checkpoint is whether data center and AI-related demand keeps showing durability across quarters, including any updates on orders, product transitions, and capacity commitments. For SpaceX, the watch items are similarly tied to how infrastructure needs evolve alongside AI-driven connectivity demand, though the company’s disclosure practices differ from public peers. In both cases, the market will likely continue tracking indicates that separate enduring demand from temporary build cycles.