Americas Technology Software Highlights from GS Comm+Tech conversations

Equity Research 14 September 2026 | 3:20AM EDT

Highlights from GS Comm+Tech conversations

We hosted ~40 Software companies at our Communacopia + Technology Conference Gabriela Borges, CFA | last week. Investor sentiment was better than at any time in the prior eight months Goldman Sachs & Co. LLC and has moved to be significantly more micro/idiosyncratic focused, with questions Matthew Martino and commentary becoming much more product and tech stack specific. Generally | speaking, for companies with exposure to the inference economy, there are good Goldman Sachs & Co. LLC reasons to believe that the best part of AI product cycles are still ahead, given how Callie Valenti | early enterprises are in scaling production inference use cases. At the same time, Goldman Sachs & Co. LLC there is a fair amount of investor discomfort in a) the move higher in application software stocks, without a commensurate move higher in fundamentals or good Max Gamperl | visibility into how the next 12 months will unfold from an estimates revisions Goldman Sachs & Co. LLC standpoint; b) the potential for a wildcard change in the security narrative or Maura Hager underlying architectures, such as from frontier models entering the security TAM. | Goldman Sachs & Co. LLC Most notable incremental positive datapoints in our view were for CRWD, DDOG, Noah Naparst DOCN, DT, SHOP and SNOW; more mixed datapoints/low visibility in our view were | for CHKP, HUBS, INTU and NAVN. Goldman Sachs & Co. LLC

Greyson Sklba | Infrastructure Goldman Sachs & Co. LLC

Selina Zhang | n AI infrastructure demand remains exceptionally strong, even when Goldman Sachs & Co. LLC

accounting for mix shift between frontier and open source/weight tokens. Enterprises are increasingly moving AI workloads into production and treating compute as a strategic resource. o CoreWeave highlighted enterprise customer wins (Caterpillar, IBM), noting that customers increasingly view AI infrastructure as a strategic asset and are building dedicated clusters to support internal models and inference workloads. o DigitalOcean pointed to increasing production adoption across coding, customer experience, personal productivity, demand generation, and generative media use cases. Management argued that inference demand is increasingly tied to real business outcomes and monetization rather than venture funded experimentation, suggesting the market is progressing from proof of concept to production deployment.

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Goldman Sachs Americas Technology: Software

o Akamai highlighted sustained customer demand extending into 2028, with opportunities spanning both GPU and CPU infrastructure. Management emphasized that demand is no longer limited to model training and increasingly includes the supporting infrastructure required to operationalize AI applications. o Microsoft’s comments on capex were balanced: Microsoft already has a framework for the right long-term investments in land and power, and a good understanding of the quantum of capacity it can bring on in the next year. Instead, its focus is on how quickly it can get new supply “revenue ready”. The company reiterated its >50% reduction in dock-to-live times over the past year and pointed to efficiency gains across hardware, Azure infrastructure, and application layers that are expanding effective supply without a commensurate increase in capital intensity. With the amount of GW of new infrastructure able to come online over the NTM largely fixed, Microsoft’s focus is on accelerating the pace at which deployed capacity becomes revenue generating, effectively extracting more Azure growth from every dollar of capital already invested. n The…