The so-called “SaaSpocalypse” narrative is losing momentum, at least in the near term, as software equities stage a broad rally driven by stronger-than-expected earnings and a reassessment of how artificial intelligence is reshaping enterprise demand rather than simply displacing it.
The rebound was anchored by results from Snowflake and Okta, which together helped reset expectations across a sector that had been heavily sold over fears that AI tools would commoditize traditional software layers.
The iShares Expanded Tech-Software ETF climbed 8% this week and closed May up 21%, its strongest monthly performance since October 2001. That comparison is not merely a historical curiosity. The earlier period reflected a post-bubble rebound, while the current move is occurring amid structural uncertainty about whether AI represents substitution or expansion for enterprise software demand.
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For much of the past year, sentiment has been dominated by concerns around “vibe coding”, a shorthand for AI systems from companies such as OpenAI and Anthropic that allow users to generate applications with minimal traditional programming. That trend raised the prospect that application-layer software firms could face erosion in pricing power and slower developer-driven demand.
This week’s earnings cycle complicated that view.
Snowflake delivered the most forceful counterargument. The company surged nearly 50% over four sessions after announcing a $6 billion cloud and chip partnership with Amazon and raising guidance. The market reaction was not just about revenue upside, but about demand visibility: AI workloads appear to be increasing the intensity of data processing rather than reducing reliance on data infrastructure providers.
Chief Executive Sridhar Ramaswamy described accelerating customer adoption of AI tools that require more frequent data access, transformation, and orchestration.
“We’re also seeing customers deploy and scale workloads at a faster pace,” Ramaswamy told analysts on the company’s earnings call.
The implication is that AI is not bypassing data platforms; it is expanding their workload footprint.
Okta’s surge added another dimension. The company rallied 30% after reporting stronger results and framing AI as a driver of identity complexity rather than simplification. Chief Executive Todd McKinnon highlighted the rise of AI agents operating across enterprise systems, increasing the need for authentication, authorization, and machine-to-machine security controls.
“AI products are going to take longer, but every organization is going to build and deploy agents,” McKinnon told CNBC. “It’s fundamental infrastructure that’s going to be required over the next few years.”
That shift is becoming a broader theme in enterprise software: AI does not eliminate workflow layers, but it multiplies the number of actors, both human and non-human, interacting with those systems. That expands the surface area for security and governance tools.
The rally extended beyond single names. Atlassian gained 26% for the week, while ServiceNow advanced more than 20%, reflecting renewed investor confidence in workflow automation platforms that sit between enterprise systems and AI interfaces.
Consumer and enterprise application platforms also participated. Shopify, Workday, and Asana each rose at least 14%, suggesting a broad-based re-rating rather than isolated earnings-driven moves.
In the infrastructure-adjacent segment, Oracle jumped 16%, and Microsoft rose nearly 8%. Microsoft remains down about 7% year-to-date, underscoring that even within AI-exposed mega-cap software, performance is increasingly bifurcated between perceived beneficiaries and perceived disruptive layers.
The broader market interpretation is shifting. Earlier in the year, the dominant thesis was that AI would compress software margins by automating coding, reducing headcount needs, and lowering switching costs for enterprise customers. That view drove valuation compression across much of the sector.
The current re-pricing suggests a more nuanced framework is taking hold.
First, AI is reducing the cost of software creation but increasing the complexity of software deployment at scale. That favors platforms that manage data, identity, security, and orchestration rather than point applications.
Second, AI adoption is expanding the total volume of software usage inside enterprises, particularly through agents, automation layers, and continuous data processing. That increases consumption of backend infrastructure even if individual applications become easier to build.
Third, the distribution of value is shifting upward in the stack. Tools that sit closest to governance, compliance, and system integration are increasingly positioned as structural beneficiaries of AI rather than casualties of it.
Still, the rebound does not resolve the longer-term structural question. If AI continues to commoditize application development, pricing pressure could eventually migrate upward from low-end tools into higher-margin enterprise systems. The current rally reflects a repricing of risk, not a conclusion of the debate.
For now, however, investors appear to be moving from a “software displacement” narrative to an “AI enablement cycle” view. The difference is not semantic. It is driving capital flows back into a sector that, only weeks ago, was being positioned as one of AI’s primary casualties.