Making Money in a Bear Market: Why Software Stocks With AI Momentum Can Deliver Triple-Digit Returns

The current market environment presents a counterintuitive opportunity for savvy investors seeking to make money in a bear market. While the S&P North American Technology Software Index—which encompasses 111 software companies—has plummeted 24% from its September 2025 peak, many market participants remain overly pessimistic about the sector’s prospects. This pullback has created an attractive entry point for investors willing to look beyond the headlines.

The widespread fear centers on artificial intelligence coding tools potentially cannibalizing demand for traditional software solutions. However, research from Morgan Stanley’s fourth-quarter CIO survey contradicts this narrative, suggesting software will emerge as the fastest-growing IT sector through 2026. According to their analysis, incumbent software vendors stand to benefit significantly from AI-driven disruption, as they will ultimately serve as the delivery infrastructure for next-generation generative AI capabilities. This structural advantage creates an interesting paradox: the very technology feared by bears may be the engine driving a bear market recovery for well-positioned companies.

Spotting Opportunities in a Bear Market: The Two-Stock Strategy

When the market turns pessimistic, investors who understand how to make money in a bear market focus on identifying companies with strong competitive moats and AI catalysts. Wall Street analysts have identified two compelling candidates worthy of consideration: Datadog and Atlassian. Their combined potential returns—102% and 170% respectively according to recent analyst forecasts—highlight the asymmetric risk-reward dynamics that characterize this particular market downturn.

Datadog: Profiting From Observability Leadership

Datadog represents a case study in how to make money in a bear market through market share consolidation and AI integration. The company develops observability software designed to help enterprises monitor critical IT infrastructure and application performance. Its platform comprises two dozen integrated products that simplify what was previously a fragmented toolset.

The AI advantage proves particularly compelling. Datadog’s proprietary Watchdog AI engine automates anomaly detection, incident alert prioritization, and root cause analysis—capabilities that help technical teams resolve infrastructure problems in a fraction of the traditional timeframe. Forrester Research recently recognized Datadog as a leader specifically in AI for IT operations, while Gartner highlighted the company’s leadership in both digital experience monitoring and observability platforms, with particular emphasis on machine learning capabilities for monitoring large language models.

Morgan Stanley analyst Keith Weiss notes that Datadog’s ability to consolidate performance monitoring across a unified platform—increasingly a top IT department priority—has positioned the company as “the top share gainer in its core observability market.” This market consolidation dynamic offers a clear path to profitability growth even within a challenging bear market environment.

The financial picture supports this narrative. Datadog’s third-quarter results exceeded market expectations on both revenue and profitability metrics. Revenue climbed 28% year-over-year to $886 million, while remaining performance obligation—a leading indicator of future revenue—surged 53% to $2.8 billion. Non-GAAP net income expanded 20% to $0.55 per diluted share. Notably, earnings growth lagged revenue growth primarily due to elevated research and development investments, a common trade-off among high-growth software companies.

Wall Street consensus estimates Datadog’s adjusted earnings will expand at a 19% compound annual rate through 2028. At 66 times forward earnings, the current valuation admittedly appears stretched compared to software sector averages. Yet the company has consistently beaten consensus estimates by an average of 13% over the last six quarters, suggesting the street remains underestimating its execution capability. The ongoing rollout of AI agent capabilities could sustain this positive earnings surprise momentum.

Arete Research analyst Adam Shepherd recently established a $260 price target on Datadog shares, implying 102% upside from the recent $129 level. While such returns aren’t guaranteed and would require sustained execution excellence, the combination of market leadership, AI-driven productivity gains, and reasonable growth rates provides a foundation for meaningful appreciation.

Atlassian: Work Management as a Bear Market Shelter

Atlassian offers an alternative approach to making money in this bear market—through leadership in work management and service management software. The company’s flagship Jira platform has evolved from a niche developer tool into an enterprise-wide productivity solution spanning technical and non-technical teams alike.

Gartner’s recent analysis designated Atlassian as a leader in work management software across two distinct categories: DevOps teams and marketing teams. Notably, Atlassian represented the only vendor achieving leader status in both segments, underscoring the breadth of its platform appeal. Forrester Research similarly recognized the company’s leadership position in enterprise service management, validating its three-market dominance strategy.

This multi-department penetration creates a powerful upsell and cross-sell dynamic. Once Atlassian establishes itself with one team, it can expand relationships across marketing, human resources, finance, and operations departments within the same enterprise—a scalable growth strategy particularly attractive during a bear market when companies seek efficiency through consolidation.

Atlassian has accelerated its work management transformation through Rovo, a generative AI assistant built into its platform. For technical teams, Rovo assists with code generation, review, and optimization. For non-technical teams, the AI capability surfaces actionable insights and automates repetitive workflows. Gartner recognized this AI integration by naming Atlassian an emerging leader in generative AI technologies last year.

The financial trajectory aligns with this competitive positioning. Atlassian reported robust September quarter performance with revenue growing 21% to $1.4 billion and remaining performance obligation jumping 42% to $3.3 billion. Non-GAAP earnings expanded 35% to $1.04 per diluted share—notably, earnings growth substantially exceeded revenue growth, indicating improving operational leverage.

CEO Mike Cannon-Brookes highlighted an important metric: the number of monthly active users engaging AI capabilities increased 50% year-over-year, reaching 3.5 million. This adoption trajectory suggests customers are actively integrating AI into their daily workflows, a leading indicator of sustained revenue growth and potential for pricing expansion.

At 30 times forward earnings, Atlassian’s valuation appears considerably more reasonable than peer software companies, particularly given its 22% estimated earnings growth rate through fiscal 2027. Morgan Stanley analyst Keith Weiss recently set a $320 price target, implying 170% upside from the recent $118 level. While such returns demand exceptional execution across multiple quarters, the combination of attractive valuation, strong earnings growth, and AI-driven engagement gains provides a more straightforward path to gains than many alternative software investments.

Portfolio Strategy: Making Money in a Bear Market

The comparison between Datadog and Atlassian illustrates two distinct investment approaches within a software bear market. Datadog represents the higher-risk, higher-reward opportunity—commanding a premium valuation justified primarily by market leadership and AI innovation potential. The 102% return projection assumes continued execution excellence and multiple expansion as market sentiment normalizes.

Atlassian presents a lower-risk entry point with comparable return potential. The 63% decline from previous highs has created a valuation floor that offers more margin of safety for new investors. The 170% return projection reflects both meaningful potential share price appreciation and the possibility of valuation normalization as growth continues to surprise.

For investors seeking to make money in a bear market, the optimal approach likely involves staged entry across both opportunities. An initial position in Atlassian provides cleaner risk-reward dynamics given its more reasonable current valuation. As conviction builds and market sentiment gradually improves, adding to a Datadog position could capture both share price appreciation and the benefits of multiple expansion.

The underlying thesis remains straightforward: while market participants fixate on AI risks to software economics, well-capitalized enterprises continue investing in software solutions to drive efficiency and innovation. The companies best positioned to capture that spending—those with strong competitive positions, multiple revenue streams, and genuine AI integration—will ultimately generate substantial shareholder returns even within what appears superficially as an unfavorable bear market environment. Successful investors recognize that bear markets create opportunities for those prepared to identify and act upon them.