Goldman Sachs tech conference highlights AI spending outlook

Investing.com -- Nvidia's Jensen Huang reiterated his forecast for AI infrastructure spending to reach $3 trillion to $4 trillion by 2030 during the third day of the Goldman Sachs Communacopia + Technology Conference.

Supply chain constraints continue across both upstream components and downstream datacenter capacity, land, and power resources as companies add capacity to meet higher demand levels. Goldman Sachs analysts noted that downstream constraints may prove more significant.

Semiconductor equipment and foundry companies reported substantially increased orders and backlog levels. The analysts described the visibility as historically unprecedented across the sector. Commentary from wafer fabrication equipment companies indicated that 8 to 10 new fabrication facilities are expected to come online in 2027.

AI inference is driving higher data usage for context windows, which increases demand for mass storage. The shift toward multi-chip integrated packages in AI infrastructure is also creating higher growth in advanced packaging and printed circuit board structures.

Companies presented concrete examples of implementing AI in internal business processes to generate revenue growth through new product development and faster innovation cycles in services. Internal AI tools are also being used to drive cost efficiencies.

EPAM Systems expects headwinds to continue through the remainder of the year amid muted client spending in certain verticals. The company anticipates maintaining solid gross margins through a combination of pricing improvements and a shift toward fixed-price contracts.

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