Goldman Sachs Sees Bigger SaaS Market From AI, Upending Bear Case

(P1) A Goldman Sachs report is pushing back against the "SaaS doomsday" theory, arguing that artificial intelligence will expand the industry's addressable market far beyond current software budgets. After meeting with about 40 software companies, analysts led by Gabriela Borges assert that the narrative of AI as a value destroyer for the sector is significantly overstated.

(P2) "The software business model is shifting from selling features and seats to selling 'labor or productivity units'," Gabriela Borges, an analyst at Goldman Sachs, wrote in the report. This change allows software companies to tap into corporate labor budgets, a market substantially larger than traditional IT spending.

(P3) The report details a structural shift where economic value is moving from foundational AI models to the software application and runtime layers. Companies are actively building "model-agnostic" software ecosystems, using open-source or smaller proprietary models to avoid dependency on a single provider, lower inference costs, and gain pricing stability.

(P4) This pivot suggests a fundamental re-evaluation of the long-term valuation logic for SaaS stocks. The core argument is that as compute power becomes the main constraint, the software layer that orchestrates AI agents, routes requests, and controls costs will capture a larger share of the value chain, directly benefiting incumbent software vendors.

AI Expands Market, Doesn't Destroy Value

The central thesis from Goldman Sachs is that the integration of AI is not a zero-sum game for Software-as-a-Service companies. By repricing their products based on productivity metrics—such as "labor units" or automated workflows—SaaS providers can penetrate the vast pool of enterprise labor costs, representing a quantum leap in their total addressable market (TAM).

Value is also migrating up the stack from the large language models (LLMs) themselves. As the performance of foundational models begins to commoditize and inference costs fall, the software that manages and deploys these models becomes more critical. According to the report, enterprises are wary of being locked into a single LLM provider like OpenAI or Google, fearing unpredictable price hikes if subsidies on tokens are removed. This is driving the adoption of independent software layers that can manage multiple models.

AI-Native Startups Target Workflow Gaps

The analysis also found that new AI-native startups are not attacking established SaaS giants like Salesforce or Workday head-on. Instead, they are focusing on the "white space" between existing software categories, building products around specific business processes and workflows that have been underserved by traditional tools.

This dynamic creates a more additive competitive landscape. Rather than a direct battle for market share, the ecosystem is evolving with three distinct players: foundational model providers, incumbent SaaS leaders embedding AI, and AI-native startups filling niche roles. Goldman Sachs suggests this will lead to overall market growth rather than cannibalization.

Divergence Remains as Bears Await Proof

Despite the bullish report, market sentiment has not fully turned. JPMorgan trading desk commentary recently described the software sector's rally as a "tactical" short-covering bounce rather than a move based on fundamentals. A subsequent weak guidance from ServiceNow reinforced this caution, hitting the stock and dragging down the sector.

Goldman Sachs acknowledges the debate is not settled, noting that the key question is which layer of the AI stack—foundational models, applications, or AI-native tools—can most effectively address its weaknesses. While the report argues for a "plus-sum game," the thesis will be tested as the current earnings season unfolds and provides concrete data on AI's true impact. The firm highlighted Salesforce (CRM), CrowdStrike (CRWD), Guidewire (GWRE), Samsara (IOT), and Rubrik (RBRK) as companies with structural advantages in this new landscape.

This article is for informational purposes only and does not constitute investment advice.