Yahoo Finance: Qualcomm points to multi-year data center growth as AI chips gain traction

A market commentary published by Yahoo Finance on June 30 suggested that the next three years of growth in artificial intelligence computing may not be centered on the most widely discussed chip names. Instead, it highlighted Qualcomm, saying the company is forecasting strong expansion in its data center business driven by traction in AI chips.

In the article’s framing, Qualcomm’s opportunity is tied to inference, the phase of AI work where models run to generate outputs such as recommendations, classifications, and other real-world responses. Inference differs from training, which generally requires far more intensive compute. The piece implies that companies building for inference at scale could benefit as demand for AI-enabled services keeps rising.

Qualcomm, according to the commentary, is looking at data center growth that extends over the coming three-year period. The note connects that outlook to improving adoption of Qualcomm’s AI chip offerings, positioning the company to capture spending linked to inference workloads rather than only training workloads.

The author’s headline explicitly indicates that the “biggest gains” could come from a company other than NVIDIA or Broadcom. That comparison matters because both NVIDIA and Broadcom are frequently associated with AI infrastructure, whether through graphics processing units, networking, or other accelerators. The commentary suggests Qualcomm’s growth narrative is different in emphasis, leaning toward inference-oriented demand.

Still, the post as presented provides limited detail on the size of Qualcomm’s forecast, the specific product lines behind the forecast, or whether the outlook reflects signed customer commitments versus expectations for future adoption. It also does not break down revenue by customer segment, geography, or workload type, which are the elements investors typically scrutinize when evaluating multi-year growth claims.

To be clear, the market note does not offer a direct, quantified valuation thesis in the information provided here. It is best read as a directional pointer to where the author believes AI inference-related spending could translate into business momentum for Qualcomm, rather than as a complete fundamental forecast.

For context, the semiconductor supply chain is increasingly split between training and inference. Training can be dominated by large-scale compute clusters, while inference is often deployed across cloud and enterprise environments where efficiency and deployment costs can matter as much as raw performance. Any company that can align chips, software support, and time-to-deployment with inference needs can be positioned to ride that shift, even if it is less visible in mainstream headlines.

What to watch next, based on the kind of claim the article makes, is whether Qualcomm continues to articulate growth targets for data centers, provides updated milestones for AI chip adoption, and delivers disclosures that separate inference-related opportunities from other lines of business. Additional clarity on customer traction and product utilization would help determine whether the multi-year outlook described in the commentary is gaining real-world support.