Navigating the Software Downturn: Why AI-Powered Datadog and Atlassian Could Deliver 100%+ Returns

The technology software sector is currently experiencing significant headwinds. The S&P North American Technology Software Index, which encompasses 111 software companies, has dropped 24% from its September 2025 peak, putting the sector firmly in bear market territory. Investor pessimism centers on concerns that artificial intelligence coding tools might cannibalize demand for traditional software solutions.

However, this market downturn may be presenting a misguided assessment. According to Morgan Stanley’s latest CIO survey data, software will remain the fastest-growing IT investment category in 2026. The research suggests that incumbent software vendors will likely serve as the primary delivery mechanism for next-generation AI capabilities rather than being displaced by them.

With this market backdrop in mind, Wall Street analysts have identified compelling investment opportunities in companies that are successfully integrating AI into their core platforms. Two standout candidates are Datadog and Atlassian, with analyst price targets suggesting potential appreciation of 102% and 170% respectively from current valuations.

Market Skepticism vs. AI Opportunity: The Case for Software Innovation

The current bear market in software stocks reflects broader investor anxiety about technology disruption. Yet the Morgan Stanley CIO survey indicates that enterprise customers remain committed to software investments, particularly those platforms leveraging advanced technologies. This disconnect between market sentiment and actual corporate spending patterns creates a window of opportunity for investors willing to look beyond short-term volatility.

Both Datadog and Atlassian exemplify this paradox: they are companies that have successfully positioned themselves not as victims of the AI revolution, but as key enablers of it.

Datadog: Building the Nervous System of Modern Infrastructure

Datadog operates in the observability software market, providing platforms that help organizations monitor their critical IT infrastructure and applications in real time. The company’s product suite includes approximately two dozen integrated tools designed to address different monitoring needs.

What distinguishes Datadog is its integrated approach to artificial intelligence. The company has deployed Watchdog, an AI engine that automates anomaly detection, incident response alerting, and root cause analysis. This capability allows IT teams to move faster when resolving infrastructure problems—a competitive advantage that becomes more valuable as systems grow in complexity.

Industry validation for Datadog’s AI strategy has been substantial. Forrester Research recently ranked the company as a leader in AI for IT operations, a category that applies machine learning to keep infrastructure stable. Gartner has similarly recognized Datadog as a leader in both digital experience monitoring and observability platforms, with specific praise for its AI-enhanced capabilities and large language model monitoring features.

From a market positioning standpoint, Morgan Stanley analyst Keith Weiss highlights that Datadog has achieved “top share gainer” status in its core observability market, driven largely by its ability to consolidate multiple monitoring tools onto a unified platform—a consolidation objective that has become a strategic priority for many IT departments.

Financial Performance and Growth Trajectory:

Datadog’s third-quarter results demonstrated solid execution. Revenue reached $886 million, representing 28% year-over-year growth and exceeding analyst expectations. More tellingly, remaining performance obligation (RPO)—a forward-looking revenue metric—jumped 53% to $2.8 billion, suggesting strong future growth momentum. Non-GAAP earnings of $0.55 per diluted share grew 20% year-over-year.

Wall Street consensus expects Datadog’s adjusted earnings to expand at approximately 19% annually through 2028. This growth projection must be evaluated against the company’s current valuation multiple of 66 times trailing earnings—a premium valuation that reflects high growth expectations.

Notably, Datadog has beaten consensus earnings estimates by an average of 13% over the past six quarters, demonstrating execution capability that could justify premium multiples if the company’s AI rollout maintains momentum. However, this same premium valuation means that near-term disappointments could result in significant downside.

Analyst Price Target: 102% Upside

Adam Shepherd at Arete Research recently set his Datadog price target at $260 per share, implying 102% appreciation from current levels near $129. While this represents compelling upside potential, investors should note that achieving such returns would require sustained earnings growth, successful AI monetization, and market multiple expansion—not guaranteed outcomes.

Atlassian: Expanding Work Management Through Generative AI

Atlassian develops work management and service management software, with Jira serving as its flagship product. Originally designed for software development teams, Jira has expanded into adjacent markets, becoming the standard platform for DevOps teams while gaining traction with non-technical departments including marketing, human resources, and finance functions.

Atlassian’s market positioning is reinforced by recent analyst recognition. Gartner ranked the company as a leader in work management software across both DevOps and marketing team categories—a distinction no other vendor achieved. Forrester separately recognized Atlassian as a leader in enterprise service management. This breadth of recognition across multiple departments and use cases provides strategic advantages for customer acquisition and expansion.

AI Strategy and User Engagement:

The company has integrated generative AI capabilities through Rovo, an AI assistant embedded across its work management platform. For development teams, Rovo assists with code generation, review, and optimization. For non-technical users, Rovo surfaces actionable insights and automates routine workflows. Last year, Gartner recognized Atlassian as an emerging leader in generative AI technologies.

A particularly compelling metric: in the September 2025 quarter, monthly active users engaging AI capabilities increased more than 50%, reaching 3.5 million. This adoption trajectory suggests that AI features are transitioning from novelty to core platform functionality.

Financial Performance and Valuation:

Atlassian reported strong September quarter results with revenue of $1.4 billion (up 21% year-over-year) and RPO of $3.3 billion (up 42%). Non-GAAP earnings increased 35% to $1.04 per diluted share—a growth rate that substantially outpaced revenue growth, reflecting operating leverage in the business model.

Wall Street estimates project adjusted earnings will grow at 22% annually through June 2027. At the current valuation multiple of 30 times earnings, Atlassian trades at a meaningful discount to Datadog and appears reasonably valued relative to its growth profile.

The stock has declined 63% from its highs during the recent software sector downturn, creating a valuation reset that appears attractive to long-term investors.

Analyst Price Target: 170% Upside

Keith Weiss at Morgan Stanley recently set his Atlassian price target at $320 per share, representing 170% upside from current levels near $118. Achieving this level would require multiple years of consistent financial outperformance and likely some expansion in valuation multiples.

Investment Framework: Balancing Opportunity Against Risk

Both companies present compelling AI narratives supported by strong market positions and growing engagement metrics. However, realistic investors should consider several factors:

For Datadog: The 102% return scenario assumes the market re-rates the stock despite its premium 66x earnings multiple. More likely, Datadog stock reaches the analyst target price through steady earnings growth combined with modest multiple expansion, requiring 4-5 years. Current valuations suggest buying only on weakness—a 20% price decline would create more attractive entry points.

For Atlassian: The 170% return scenario is more plausible given the current 30x multiple and stronger earnings growth expectations (22% annually). Atlassian appears attractive at current levels, though even this upside scenario requires sustained execution and no major market disruption.

Broader Context: Morgan Stanley’s research showing software as the fastest-growing IT sector in 2026 supports the thesis that these companies operate in favorable growth environments. The market’s pessimism around AI appears partially misplaced—rather than cannibalizing software demand, AI is becoming a core driver of software investment.

Investors with a multi-year horizon and patience for volatility should consider building positions in companies successfully monetizing AI integration. Atlassian appears more attractively valued for new positions, while Datadog offers growth potential that may eventually justify its premium, though entry points closer to $100 would offer better risk-reward profiles for most investors.