Written by: Rita
Tide Guide
Over the past two years, the software sector underperformed the Nasdaq by 40% and the S&P 500 by 30%. Expectations that AI will reshape industries continue to build, yet the market remains pessimistic about software stock valuations, focusing only on survival value and overlooking long-term growth potential.
Morgan Stanley released a 170-page in-depth report on the software industry, concluding that current pessimistic expectations are overpriced, and maintained an "attractive" rating for the software sector.
The report establishes a new analytical framework: moat measures a company’s current competitive foundation, while journey assesses its long-term growth potential. Companies possessing both advantages offer higher allocation value. Morgan Stanley has selected eight high-conviction overweight picks: Microsoft, Palo Alto Networks, CrowdStrike, Shopify, Cloudflare, ServiceNow, Datadog, and Snowflake. Adobe and Workday have been downgraded to underweight, as institutional analysts expect their AI monetization timelines to exceed market expectations.
The AI value focus should be on the workflow layer. This is the core conclusion of this report.
Dual Perspective Framework: Identifying the Core Competitiveness of Software Companies in the AI Era
This analytical framework is logically structured and effectively distinguishes between companies' growth prospects.
The moat represents short-term defensive capabilities, evaluated by factors such as whether the business is mission-critical, functions as a core record-keeping system, the cost of customer switching, and the depth of proprietary data and industry expertise. High-quality targets exhibit strong customer stickiness, with systems deeply embedded in enterprise operations, where service interruptions would directly impact daily business activities.
The journey represents long-term growth potential, evaluated across modern product architecture, a clear and actionable AI development roadmap, the potential to transition pricing models to usage-based billing, and the ability to build an agent ecosystem.
Past market investment decisions primarily focused on moats, but a single, static barrier is insufficient to sustain valuations over the long term. In the context of the AI industry transformation, only companies with deep barriers that can continuously iterate are positioned to realize sustained value. Among the 81 companies covered by institutions, only five meet both criteria: Microsoft, Palo Alto Networks, CrowdStrike, Shopify, and ServiceNow. These companies have solid operational foundations and significant long-term growth potential.
Analysis of Core High-Quality Assets: Clarifying the Growth Logic of High-Confidence Assets
Morgan Stanley has identified eight companies as top conviction overweight picks, each with distinct growth narratives.
Microsoft possesses a strong moat and significant growth potential. Morgan Stanley believes Azure’s growth constraints stem from capacity supply, while demand remains robust. Enterprise adoption of Copilot continues to rise, with 88% of CIOs planning to deploy M365 Copilot within the next 12 months, up from 72% last year. The market underestimates Microsoft’s AI monetization potential, as revenue extends beyond model API sales to encompass the full Azure AI Foundry platform ecosystem, including databases, storage, and development tools. With a FY28 P/E ratio of 16x and sustainable EPS growth exceeding 20%, Microsoft’s valuation is attractive.
Palo Alto Networks and CrowdStrike are the two leading players in cybersecurity. AI has spawned entirely new security threats, driving sustained growth in protection demand, while companies are simultaneously consolidating vendors and favoring integrated platform solutions. Palo Alto’s platform strategy is steadily taking shape, with platform customer net retention rates reaching approximately 120%, significantly higher than those of standard customers. CrowdStrike’s Falcon Flex ARR has surpassed $1.9 billion, representing a 99% year-over-year increase.
Shopify is the only e-commerce SaaS provider on the list. Leveraging the Sidekick AI website builder, barriers to entry continue to decline, expanding the customer base from established merchants to individual entrepreneurs. The company’s FY27 free cash flow implies a valuation multiple of 46x, aligned with a 25% revenue CAGR and a 30% free cash flow CAGR, yet the valuation has not fully reflected the value of its business transformation.
Snowflake and Datadog are positioning themselves in the infrastructure space. Snowflake, as a data cloud platform, meets enterprises' data infrastructure needs for AI transformation. Datadog focuses on observability, aligning with operational demands following large-scale deployment of agents, as vast numbers of agents continuously generate logs and tracing data, driving steady growth in operational requirements.
Industry underlying logic: Workflows serve as the core vehicle for AI value.
This is the most fundamental judgment in the entire report.
Morgan Stanley cited a joint study by Harvard Business School and BCG on the "sawtooth frontier." The study set up a controlled experiment, assigning business analysis tasks to consulting consultants—one group equipped with AI tools and another without. The results showed that teams using AI tools had a 19-percentage-point decline in the accuracy of their conclusions. AI excels at text generation, brainstorming, and structured writing, but tends to produce biases in complex business scenarios requiring cross-verification of information and multi-criteria trade-offs, leading users to overly rely on its outputs.
Frontier model capabilities continue to evolve, but adoption progress for complex enterprise business scenarios has entered a plateau. Models are well-suited for standardized tasks such as code adaptation and general content creation, where data is abundant and outcomes are easy to validate. Enterprise workflow scenarios differ significantly, lacking standardized documentation and relying on subjective evaluation criteria with no universal standard answers.
Workflows are central to realizing AI's value. Proprietary data, access controls, audit trails, business process systems, and industry expertise together form this value ecosystem. Companies that control workflows maintain ongoing pricing power.
This logic supports the view that Shopify, ServiceNow, Datadog, and Snowflake are favored, as these four companies control critical nodes in industry workflows.
Industry cycle rotation: Infrastructure leads the way, applications await a turning point
Morgan Stanley reviews the evolution of cloud computing, which has successively gone through stages of SaaS adoption, pilot cloud solutions, architectural standardization, and in-house application development.
The AI industry is currently entering a phase of autonomous development. Infrastructure software has led the way in capturing increased demand, with data and operations vendors such as Snowflake, Datadog, and MongoDB reporting continued improvement in new orders. Cybersecurity is following closely, as AI has generated new security risks, accelerating the pace of platform integration.
The pace of software performance realization is slower. ServiceNow is closer to an industry inflection point, while Shopify continues to advance its AI commercialization. Salesforce, Workday, and Intuit require longer adjustment periods, as enterprises face multiple challenges including pricing model transitions, competition from AI-native vendors, and pressure on gross margins.
Within the application sector, Adobe and Workday have received low ratings. Adobe is facing pressure from lightweight customers being diverted by various AI tools, along with leadership transitions and business model transformation. Workday’s AI commercialization is progressing slowly, and high compliance requirements for HR and financial processes mean customers won’t switch their core systems based solely on AI capabilities.
Tide View
The most critical signal in this report is that the investment thesis for the software industry is undergoing a systemic shift. While the market previously favored high-valuation, high-growth standout assets, the current phase favors well-rounded, balanced assets with greater certainty. This represents a systemic revaluation of industry valuation metrics—far beyond mere sector sentiment recovery.
The common characteristic of these eight high-confidence targets is that they all occupy the middle layer of AI implementation. Leveraging their accumulated advantages in customers, data, and processes, they serve as essential nodes in enterprise AI transformation, with their value continuously unlocking as AI applications deepen.
Industry differentiation will intensify further. Companies with deep barriers to entry and continuous evolution capabilities will continue to expand their advantages during this round of industry consolidation. Companies excelling in only one dimension will gradually lose their long-term competitiveness.
The underperformance of Adobe and Workday conveys an important investment insight: In the AI era, time cost is also a core valuation variable. If market-anticipated growth fails to materialize into actual earnings over time, the mere act of waiting can erode significant returns. The benchmark for quality assets must consider both long-term growth potential and the pace of earnings realization.
Disclaimer
This article is a compilation and interpretation by Chaoxiang Research of a third-party brokerage research report (Morgan Stanley, July 21, 2026). The ratings, price targets, earnings forecasts, and related judgments cited herein reflect the views of the brokerage’s analysts and represent the position of their respective institution only; they do not reflect the views of Chaoxiang Research nor constitute any investment advice. The market carries risks, and decisions must be made independently. This article should not be used as a basis for buying or selling any securities.