AI-Era Software Stocks: Why Software Shares Are Rising and Which Nasdaq Names Belong on a Long-Term Watchlist

Software stocks are rebounding because investors are no longer asking whether AI kills SaaS. They are asking which software companies become more essential when AI moves into production.

The AI trade started with chips. That made sense: before a company can deploy copilots, AI agents, and model-driven workflows, someone has to buy GPUs, servers, networking, memory, and cloud capacity.

But by May 2026, the story has started to widen. The better question is no longer only “who sells the compute?” It is also “who captures the software dollars once the compute is installed?”

That is why software stocks are rising again. Not because the AI risk has disappeared. It has not. The rebound is happening because investors are becoming more selective. Companies that sell shallow, seat-based software for standardized tasks may still face pricing pressure. But companies that sit inside cloud infrastructure, data pipelines, cybersecurity, identity, chip design, developer workflows, and enterprise decision systems may become more valuable as AI usage grows.

This is general market commentary, not personal investment advice. Prices, earnings estimates, and risk conditions can change quickly.

Why software stocks are rising now

The software rally has three big drivers.

First, AI spending is expanding beyond hardware. Gartner forecasts worldwide AI spending of $2.59 trillion in 2026, up 47% year over year. Its same forecast estimates AI software spending at about $453 billion in 2026, while AI infrastructure remains the largest category. Gartner’s broader IT-spending forecast also expects global software spending to reach about $1.44 trillion in 2026, up 15.1% year over year. That gives software investors a cleaner narrative: after infrastructure comes the application, security, data, monitoring, and workflow layer.

Second, earnings have started to show proof rather than promises. Datadog reported first-quarter 2026 revenue of $1.006 billion, up 32% year over year, while Microsoft said Microsoft Cloud revenue reached $54.5 billion, up 29% in its fiscal third quarter. Atlassian reported third-quarter fiscal 2026 revenue of $1.787 billion, up 32%, and said customers were connecting teams and workflows on its AI-powered platform. These are not vague product-launch headlines. They are financial signals.

Third, investors are rotating from “AI destroys software” to “AI separates software.” Reuters reported on May 19, 2026 that U.S. software shares were rebounding after being battered earlier in the year on fears of AI disruption. The key idea: markets are drawing a line between companies that may be replaced by AI and companies whose products become more important because of AI.

The core shift: from SaaS seats to AI control points

Old software investing often centered on seat growth: sell more subscriptions to more employees.

AI complicates that model. If agents automate work, some seat-based tools may lose pricing power. But AI also creates new control points:

• Cloud platforms host models and AI workloads.
• Observability software monitors cloud, GPU, application, and agent behavior.
• Cybersecurity and identity platforms secure humans, machines, and AI agents.
• Data platforms and databases organize the information AI systems need.
• EDA software helps design the chips that power AI infrastructure.
• Workflow software coordinates work between people, systems, and agents.

The winners are not simply “software companies.” The winners are software companies that become harder to remove as AI gets embedded deeper into the enterprise.

Nasdaq software stocks to watch in the AI era

The cleanest watchlist is not the longest one. In the AI era, a software stock deserves attention only if AI makes the product more necessary, not merely more fashionable.

1. Microsoft: the distribution moat

Microsoft is not a pure software stock anymore. It is a cloud, productivity, enterprise security, developer, and AI infrastructure platform. That is exactly why it belongs on any Nasdaq AI-software watchlist.

In fiscal Q3 2026, Microsoft reported $54.5 billion in Microsoft Cloud revenue, up 29%, and Azure and other cloud services revenue growth of 40%. That matters because AI demand is landing across Microsoft’s stack: cloud infrastructure, Microsoft 365, Dynamics, GitHub, security, and enterprise AI tools.

The risk is also clear. Microsoft has to keep proving that heavy AI infrastructure spending can become durable, high-margin revenue. For long-term investors, the question is not whether Microsoft is exposed to AI. It is whether AI improves returns across the whole platform.

2. Datadog: the observability winner investors suddenly understand

Datadog has become one of the more interesting AI-era software stories because it sells something AI systems need after the demo: visibility.

AI applications are not simple. They involve APIs, models, cloud workloads, GPUs, databases, prompts, agents, permissions, latency, and cost controls. A business running AI in production needs to know what broke, why it broke, how expensive it is, and whether it is secure.

Datadog’s first-quarter 2026 results showed that this demand is not theoretical. Revenue grew 32% year over year to $1.006 billion, and the company launched products including GPU Monitoring, MCP Server, and Bits AI Security Agent. This is the kind of software that can benefit as AI workloads move from prototypes to production.

The risk: Datadog is tied to cloud usage. If customers aggressively optimize cloud spending, usage growth can cool. But among Nasdaq software names, Datadog has a strong claim to being a practical AI infrastructure software play rather than a hype proxy.

3. Cybersecurity and identity: AI creates a larger attack surface

AI does not reduce the need for security. It changes what must be secured.

CrowdStrike reported fiscal 2026 ending annual recurring revenue of $5.25 billion, up 24% year over year, and described AI as creating a growth opportunity across layers from GPU to agent to prompt. Fortinet reported first-quarter 2026 revenue growth of 20% and said an increasingly complex threat environment was being intensified by AI. Okta’s first-quarter fiscal 2027 release framed AI agents as a new workforce that must be secured and governed alongside human users. Palo Alto Networks also announced its intent to acquire Portkey, an AI gateway company, to help secure autonomous AI agents.

That is the cybersecurity thesis in one sentence: every AI agent becomes a new identity, a new permission set, and a new risk surface.

The strongest names in this bucket are not just selling “AI security” as a slogan. They are trying to become control planes for the agentic enterprise. CrowdStrike, Fortinet, Palo Alto Networks, and Okta all belong on the research list, though investors should compare growth, free cash flow, valuation, and execution quality rather than buying the whole group blindly.

4. Cadence and Synopsys: software behind the AI chip boom

Some of the most important AI software companies do not look like traditional SaaS companies.

Cadence and Synopsys sell electronic design automation software, the tools engineers use to design and verify chips and complex systems. If the AI era leads to more custom accelerators, more advanced semiconductor designs, and more system-level complexity, EDA software becomes more strategic.

Cadence reported first-quarter 2026 revenue of $1.474 billion, record backlog of $8.0 billion, and raised its 2026 revenue outlook to roughly 17% year-over-year growth. Synopsys reported fiscal second-quarter 2026 revenue of $2.276 billion, up from $1.604 billion a year earlier, and said AI is scaling semiconductor demand and chip complexity.

This bucket is attractive because it is not as exposed to the “AI replaces software seats” debate. The risk is different: semiconductor cycles, export controls, integration risk, and valuation discipline.

5. Adobe and Atlassian: application software must prove AI pricing power

Adobe and Atlassian are useful because they show both sides of the AI application debate.

Adobe reported record fiscal Q1 2026 revenue of $6.40 billion, up 12% year over year, and said AI-first ARR more than tripled year over year. That supports the bull case: AI could increase content creation, productivity, and customer-experience spending. The bear case is also serious: generative AI can commoditize parts of creative production, so Adobe must prove its distribution, brand trust, workflow depth, and enterprise relationships are enough to protect pricing power.

Atlassian reported third-quarter fiscal 2026 revenue of $1.787 billion, up 32%, with AI agents embedded into Jira and broader workflows. Atlassian’s advantage is that it sits inside team collaboration, software development, service management, and enterprise workflow history. If AI agents need a system of record for work, Jira and Confluence can matter more, not less.

For application-layer software, the test is blunt: does AI make customers pay more, use more, and stay longer? If the answer is yes, the stock may deserve a premium. If the answer is no, AI can become a margin and pricing threat.

A practical AI-era software stock filter

Instead of asking “Which software stocks must I own?” ask these five questions:

1. Does AI expand the company’s market, or automate away its core value?
   AI is bullish when it creates more usage, more data, more security needs, or more workflow dependence. It is bearish when it makes the product easier to copy.

2. Is the company close to a control point?
   Cloud, identity, security, observability, databases, chip design, and enterprise workflows are stronger control points than lightweight productivity features.

3. Is there financial evidence?
   Look for revenue acceleration, rising remaining performance obligations, ARR growth, free cash flow, larger customers, or explicit AI-linked adoption. Product announcements alone are not enough.

4. Does the company have pricing power?
   AI can raise costs. The best companies can pass some of that value into price, usage, or larger contracts.

5. Has valuation already priced in perfection?
   Great businesses can become poor stocks if expectations get too extreme. After a sharp rally, entry price matters.

My working watchlist

For a durable AI-era Nasdaq software watchlist, I would group the names like this:

Core platform exposure: Microsoft, Datadog, Palantir
Security and identity exposure: CrowdStrike, Palo Alto Networks, Fortinet, Okta
AI chip design software: Cadence, Synopsys
Application-layer upside with disruption risk: Adobe, Atlassian, MongoDB, Workday

The highest-quality list will depend on valuation and time horizon. A conservative investor may prefer profitable platforms with cash flow. A growth investor may accept more volatility in exchange for faster revenue growth. A thematic investor may build a basket across cloud, security, identity, observability, and EDA rather than betting on one winner.

Bottom line

Software stocks are rising because the market is moving past the lazy version of the AI story.

The lazy version says AI will replace software.

The better version says AI will punish replaceable software and strengthen software that controls infrastructure, data, identity, security, chip design, and enterprise workflows.

That is the real opportunity. Not “buy every SaaS stock.” Not “AI fixes everything.” The opportunity is to own software companies that become more essential when AI stops being a demo and becomes part of daily business operations.

FAQ

Why are software stocks rising in 2026?

Software stocks are rising because investors are reassessing earlier fears that AI would broadly disrupt SaaS. Strong earnings from selected software companies, rising AI-related IT spending, and evidence of demand for security, observability, cloud, and workflow tools have improved sentiment.

Are all software stocks good AI investments?

No. AI may help some software companies and hurt others. Companies tied to mission-critical workflows, proprietary data, infrastructure, cybersecurity, identity, and monitoring appear better positioned than companies selling standardized tools that AI agents can cheaply replicate.

Which Nasdaq software stocks are most relevant to the AI era?

Microsoft, Datadog, CrowdStrike, Fortinet, Palo Alto Networks, Okta, Cadence, Synopsys, Adobe, Atlassian, MongoDB, and Palantir are among the most relevant Nasdaq-listed software or software-related names to research. They are not equally risky or equally valued.

Is cybersecurity a software winner in the AI era?

Cybersecurity is one of the clearer AI-era software themes because AI increases the number of identities, permissions, agents, prompts, APIs, and machine-to-machine interactions that enterprises must secure. CrowdStrike, Fortinet, Palo Alto Networks, and Okta are key Nasdaq-listed names in this bucket.

Should investors buy software stocks after a rally?

A rally does not automatically make a stock attractive. Investors should compare revenue growth, free cash flow, valuation, RPO or ARR trends, customer growth, and whether AI is producing measurable business results. Position sizing and risk management matter.

Sources

• Gartner: Worldwide AI Spending to Grow 47% in 2026 — Used for AI spending and AI software market forecast.
• Gartner: Worldwide IT Spending to Grow 13.5% in 2026 — Used for total IT spending and software spending forecast.
• Reuters: U.S. Software Stocks Rebound as Investors Reassess AI Risks — Used for market sentiment and rebound context.
• Microsoft FY26 Q3 Earnings Release — Used for Microsoft Cloud and Azure growth.
• Datadog Q1 2026 Financial Results — Used for revenue growth, customer metrics, and AI-related product launches.
• Adobe Q1 FY2026 SEC Exhibit — Used for revenue, AI-first ARR, and subscription growth.
• CrowdStrike FY2026 Q4 and Full-Year Results — Used for ARR, revenue, and AI security commentary.
• Fortinet Q1 2026 Financial Results — Used for revenue growth and AI-intensified threat environment.
• Okta Q1 FY2027 Financial Results — Used for revenue, RPO, free cash flow, and AI-agent identity framing.
• Palo Alto Networks: Portkey Acquisition Announcement — Used for AI gateway and agent-security context.
• Cadence Q1 2026 Financial Results — Used for revenue, backlog, AI demand, and 2026 outlook.
• Synopsys Q2 Fiscal 2026 Financial Results — Used for revenue and AI-related semiconductor demand.
• Atlassian Q3 Fiscal 2026 Results — Used for revenue growth and AI workflow/product updates.
• MongoDB Q1 Fiscal 2027 Results via PRNewswire/MarketScreener — Used for MongoDB revenue and Atlas growth.
• Palantir Q1 2026 Results — Used for Palantir revenue growth and AI platform context.