Markets hover near highs as AI earnings spotlight turns to ASML and Nvidia’s supply chain

U.S. stock index futures pointed to another cautious session after recent gains, with the S&P 500 and the Nasdaq described as trading near their highs. Even as daily moves created some “chop,” the broader tone in the market remained focused on whether this AI-linked rally can hold without a deeper reset in expectations.

Attention is shifting to semiconductor earnings, which are increasingly viewed as a real-time check on how strongly artificial intelligence infrastructure is being built and upgraded. ASML, a critical supplier of chipmaking lithography equipment used to manufacture advanced processors, and Taiwan Semiconductor Manufacturing are set to kick off the next phase of results that investors will use to gauge the health of the AI supply chain.

In this setup, Nvidia sits at the center of the narrative even though it does not lead the initial announcements mentioned in the market outlook. As a major designer of graphics processing units and related accelerated computing platforms used for AI training and inference, Nvidia’s demand outlook is often treated as a proxy for what cloud and enterprise customers are willing to spend on AI hardware. Any read-through investors try to draw from upstream equipment and foundry commentary can influence how they think about Nvidia’s growth trajectory.

The market backdrop also reflects how quickly sentiment can change around AI trades. When investors believe semiconductor guidance implies sustained data center spending, dips are more likely to be framed as opportunities rather than indicates of a demand slowdown. Conversely, if chipmaking equipment orders, utilization rates, or production plans are described conservatively, traders typically reassess whether the most expensive AI-linked names have already priced in a full cycle of demand.

ASML’s results matter because lithography tools are among the most essential bottlenecks in advanced chip production. When equipment vendors speak about order timing, backlog, and chipmaking intensity from major customers, it can quickly filter into expectations for leading-edge processor output. Those expectations, in turn, affect how the market imagines the speed at which AI accelerators and the servers that house them can be manufactured and scaled.

Taiwan Semiconductor Manufacturing’s earnings also carry extra weight because it is a key contract manufacturer for advanced chips. Foundry commentary about capacity, customer demand, and the cadence of new production ramps often becomes a focus point for investors trying to separate temporary hiccups from structural changes in demand. Even without company-specific numbers in the immediate market preview, investors generally treat foundry results as a window into the stability of AI-related orders.

Nvidia, for its part, has used its public newsroom to outline how it is approaching the AI build-out, including the way it packages hardware and software for data centers and enterprise deployments. The company’s broader messaging typically emphasizes the tight link between accelerating compute and the systems needed to run modern AI workloads, which can make its own subsequent guidance especially sensitive to what customers and suppliers are indicating in the earlier semiconductor round.