Software Sector Under Pressure, But These 3 Names Offer Shelter From AI Disruption

As artificial intelligence threatens to upend traditional software workflows, the broader software sector faces mounting headwinds. Yet according to market strategist Kuran Francis, three companies are uniquely positioned to thrive in this turbulent environment: CrowdStrike Holdings, Zscaler, and Datadog—each benefiting from structural shifts that AI adoption will accelerate rather than undermine.

The concern gripping software investors is straightforward: AI tools may cannibalize demand for legacy software solutions, rendering traditional subscription and seat-based licensing models obsolete. This dynamic has created divergence in the sector, with investors now differentiating between software companies built for the AI era and those exposed to disruption. Understanding this emerging hierarchy is critical for portfolio positioning as the software landscape transforms.

The Three Names Positioned to Win

Francis identifies three distinct competitive advantages that shield these companies from AI-driven disruption:

CrowdStrike benefits from rising cybersecurity demand. As artificial intelligence becomes more prevalent across enterprise infrastructure, the attack surface expands exponentially. AI-enabled threats and sophisticated cyberattacks create an expanding moat for advanced endpoint protection and threat intelligence providers. The company's cloud-native security platform becomes increasingly critical as organizations grapple with securing AI workloads and preventing AI-driven attacks. This represents a structural tailwind rather than headwind for the cybersecurity leader.

Zscaler is positioned at the forefront of a critical architectural shift: zero-trust security adoption. Traditional perimeter-based security models are becoming obsolete as cloud adoption and distributed AI workloads fundamentally change how enterprises must approach network security. Zero-trust architecture—which assumes no user or device is trustworthy by default—is transitioning from emerging trend to essential requirement. This architectural migration creates durable demand for Zscaler's cloud-native security platform, independent of broader software cycle dynamics.

Datadog benefits from a fundamentally different business model: usage-based pricing. Unlike traditional seat-based or feature-based licensing, Datadog's consumption-oriented approach aligns perfectly with the AI economy. As organizations deploy more AI models and data-intensive workloads, Datadog's platform automatically scales revenue with customer value creation. This structural alignment means AI adoption directly drives revenue growth rather than threatening it. The company essentially becomes a beneficiary of the compute and data expansion that AI catalyzes.

The Vulnerability Exposed: Seat-Based Licensing Models

Contrasting these three winners, Adobe exemplifies the vulnerability Francis highlights. Adobe's traditional seat-based subscription model—where customers pay per user or per deployment—faces significant disruption risk from AI tools that may streamline or replace design workflows. As generative AI tools offer increasingly capable alternatives for image generation, video editing, and design automation, the economics of expensive per-seat subscriptions become harder to justify for cost-conscious enterprises.

Adobe's exposure differs fundamentally from the three favored names. While CrowdStrike, Zscaler, and Datadog benefit from AI adoption expanding their addressable markets and driving usage, Adobe faces the opposite dynamic: AI tools may reduce the number of seats required or eliminate the need for expensive creative software subscriptions entirely. This represents a structural headwind rather than tailwind.

Market Context: The Software Sector Reckoning

The software sector currently faces a critical inflection point. The broad software index has declined amid concerns that AI disruption will impair earnings growth and margin expansion across legacy software businesses. However, this sector-wide pressure masks significant divergence between business models.

Key dynamics reshaping the software landscape include:

• Architectural migration: Zero-trust security adoption is reshaping cybersecurity spending from perimeter-based to architecture-agnostic approaches
• Threat expansion: AI-enabled attacks and sophisticated threat vectors are expanding cybersecurity budgets faster than overall IT spending
• Consumption economics: Usage-based pricing models outperform seat-based licensing in environments with variable, unpredictable workloads
• Workflow disruption: AI tools are directly competing with traditional software in design, content creation, and routine business processes
• Infrastructure intensity: Modern AI workloads require sophisticated observability and monitoring platforms, creating structural demand growth

This environment rewards companies aligned with how enterprises actually deploy and consume technology in the AI era, while punishing those dependent on legacy licensing assumptions.

Investor Implications: Strategic Sector Rotation

For investors holding broad software positions, Francis's analysis points toward necessary portfolio rebalancing. The indiscriminate software selloff creates opportunity to differentiate between structural winners and vulnerable legacy players.

The implications for equity investors include:

• $CRWD (CrowdStrike): Cybersecurity spending accelerates as AI-driven threats multiply. The company's endpoint protection and threat intelligence become non-discretionary infrastructure investments.
• $ZS (Zscaler): Zero-trust architecture adoption is mandatory as cloud and AI workloads expand. This represents a multi-year secular trend independent of broader software cycle concerns.
• $DDOG (Datadog): Consumption-based pricing creates positive optionality as customers expand AI workloads. Revenue scales directly with customer success and adoption.
• $ADBE (Adobe): Exposure to AI-driven workflow disruption creates earnings risk. Investors should carefully assess whether seat-based subscription models can maintain pricing power in an environment where AI tools offer capable alternatives.

Broader software indices may face continued pressure as investors reprices risk, but disciplined stock selection can identify companies where AI adoption is a revenue accelerator rather than headwind. This divergence suggests the sector is less broken than misunderstood—and that patient capital willing to differentiate will find compelling opportunities.

The Path Forward: Structural Winners Emerge

As artificial intelligence reshapes software economics, the companies thriving in this transition share a common characteristic: their business models become more valuable as AI adoption accelerates. Whether through expanding threat surfaces driving cybersecurity investment, mandatory architectural migrations toward zero-trust security, or consumption models that scale with workload intensity, these companies are positioned as infrastructure plays in the AI economy.

The broader software sector's pressure reflects a necessary repricing of risk and value. Companies clinging to legacy licensing and business models face structural challenges, while those built for modern cloud and AI-native deployments emerge as the sector's next generation leaders. For investors navigating this transition, distinguishing between these two categories is becoming the essential work of software portfolio management.