Forget the AI Replacement Fear. Which Software Names Lead the AI Restructuring Rally?

U.S. software stocks continued their rally overnight, with AI infrastructure sectors like data foundations and cybersecurity leading the charge. The sector has already witnessed its biggest surge since 2001. The $iShares Expanded Tech-Software Sector ETF (IGV.US)$ climbed 21% in May, marking its best monthly performance since October 2001. Back then, the rally was a brief rebound following the burst of the dot-com bubble; today's surge, however, comes against a backdrop of widespread concern over AI's impact on the entire industry. The top gainers are concentrated in AI infrastructure segments such as data infrastructure and cybersecurity. $Snowflake (SNOW.US)$ and $MongoDB (MDB.US)$ have validated growing demand at the data layer, $Okta (OKTA.US)$ has proven the rising value of identity governance, while $Datadog (DDOG.US)$ , $CrowdStrike (CRWD.US)$ , $Fortinet (FTNT.US)$ , and $Palo Alto Networks (PANW.US)$ reflect the simultaneous expansion of monitoring and security needs during the scaled deployment of AI.

IGV: A Rebound from Oversold Levels

Over the past year, software stocks were battered by the so-called "vibe coding" craze—where users can now build apps and websites in minutes using products from Anthropic, OpenAI, and others. The extreme pessimism driven by the "AI replacement narrative" caused the software index IGV to retract by as much as 30% in Q1 2026. The ETF hit a 52-week low of $74.6 in early April 2026, indicating that the prior sell-off sentiment had become excessive. In early May, strong results from DDOG and Fortinet shattered the "AI eats everything" rhetoric with their resilient performance, prompting the market to start differentiating between software companies.

$Datadog (DDOG.US)$: Driven by re-accelerating growth, native AI momentum, and improved profit margins, DDOG reported revenue of $1.006 billion for Q1 2026, beating the market expectation of $960 million. This represents a 32% year-over-year increase, with an operating margin of 22%. The company raised its full-year guidance across the board, forecasting a midpoint revenue of $4.32 billion for 2026, up from the previous prediction of $4.08 billion. The number of customers with an annualized spend over $100,000 grew to 4,550. Additionally, the CEO noted that the company has secured two large hyperscale clients for its Superintelligence Lab training business.

$Fortinet (FTNT.US)$: The increasingly complex threat landscape exacerbated by AI is pushing the cybersecurity industry into a new phase. Total revenue for Q1 2026 grew 20% year-over-year to $1.85 billion, surpassing the expected $1.73 billion. Billings surged 31% to $2.09 billion, driven by the continued convergence of networking and security, as well as the escalating complexity of threats fueled by AI. Fortinet raised its full-year 2026 revenue guidance from the previous range of $7.5–$7.7 billion to $7.71–$7.87 billion, with full-year gross margins expected to reach 79%–81%. The high growth in billings indicates that customers are proactively increasing spending rather than cutting costs, effectively debunking the market view that "AI will devour cybersecurity."

Snowflake, MongoDB, and Okta Lead a New Wave of Gains

Recently, software companies like Snowflake, MongoDB, and Salesforce all delivered earnings that beat expectations. The market began to reassess how software enterprises benefit in the AI era, triggering a powerful rebound in the sector. IGV rose over 21% in a single month. Notably, Snowflake shares jumped 48.4% in a week, and Okta soared 33.6%, helping drive an 8% weekly gain for IGV. These results falsified the replacement narrative, unleashing the full elasticity of valuation recovery.

$Snowflake (SNOW.US)$:

1. Earnings Beat: For FY27 Q1, the company achieved total revenue of $1.39 billion, a 33.5% year-over-year increase, exceeding the consensus estimate of $1.32 billion. Non-GAAP operating margin improved by 3 percentage points to 11.9%, and Non-GAAP product gross margin remained at a robust 75%.

2. Customer Growth & Quality: Net Revenue Retention (NRR) increased by 2 percentage points year-over-year to 126% in FY27 Q1, demonstrating excellent customer stickiness and organic growth capabilities. Net new customers grew 38% year-over-year.

3. $6 Billion AWS Partnership to Drive Enterprise AI: The company plans to invest $6 billion over the next five years in Amazon Web Services (AWS), including AWS's self-developed Arm-based Graviton general-purpose chips and GPUs for AI workloads.

$MongoDB (MDB.US)$ :

1. Strong Atlas Cloud Database Performance: Total revenue reached $690 million in Q1 2026, up 25.2% year-over-year. Atlas revenue grew 29.4% to $510 million, with a Non-GAAP operating margin nearing 18%.

2. Expanding High-Quality Customer Base: Remaining Performance Obligations (RPO) surged 88% year-over-year to $1.46 billion in FY26 Q1, with a net Annual Recurring Revenue (ARR) expansion rate of 121%. The company added 2,500 new customers this quarter, bringing the total customer count past 67,700. Customers spending over $100,000 annually grew 15.5% to 2,895. Notably, total Atlas customers exceeded 66,400, thanks to the adoption of Vector Search and Text Search.

3. AI Workloads Driving Platform Adoption: MongoDB is well-positioned for scaled AI workloads in production environments. The adoption rate of Vector Search is outpacing the company's overall growth, and the usage of AI tools like the Model Context Protocol (MCP) server is also seeing significant increases.

$Okta (OKTA.US)$:

The company reported total revenue of $770 million for FY27 Q1, an 11.2% year-over-year increase, with subscription revenue rising 11.4% to $750 million, continuing stable growth for multiple quarters. According to Okta's earnings call, over 90% of enterprises currently have AI agents in production, yet only 22% can effectively govern them. As Agentic AI becomes common, a massive number of new "digital identities" are being generated, which will significantly boost demand for identity authentication, permission governance, and Privileged Access Management (PAM).

The Replacement Narrative is Overly Simplistic. IT Projects Require Systemic Solutions

The linear narrative that "AI devours all SaaS" does not align with real-world industrial logic. As AI moves from demonstration-level to production-grade, enterprise demand for systemic capabilities—such as observability, security, data governance, vector search, and workflow collaboration—is actually being structurally amplified.

Whether it's DDOG's monitoring capabilities, FTNT/PANW/CRWD's security prowess, SNOW/MDB's data foundation strength, or ServiceNow's workflow ecosystem, these companies are fundamentally on the critical path for the scaled deployment of AI.

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