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3 Beaten-Down Tech Stocks That Could Soar 33% or More, According to Wall Street

FIGTEAMDUOLMSFTNFLXZMNOWSPGIMDB
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The article highlights sharp stock declines in Figma, ServiceNow, and MongoDB, but argues Wall Street sees 33%+ upside for MongoDB and roughly 60%+ upside for ServiceNow, with Figma's average target about 114% above the current price. Key concerns are Anthropic's Claude Design threatening Figma, the 'SaaSpocalypse' pressuring ServiceNow, and MongoDB's weaker-than-expected revenue guidance, though all three are framed as long-term fundamentally strong. The piece is mostly analyst commentary and sentiment framing rather than new company-specific catalysts.

Analysis

The market is treating all three names as if AI is uniformly disintermediating software, but the dispersion matters. The more important read-through is that AI appears to be shifting value from generic application layers to workflow control points and data infrastructure: that is constructive for NOW and, to a lesser degree, MDB, while FIG is the cleanest target if design becomes embedded inside model-native tools. In other words, the selloff is less about demand destruction and more about investors repricing where pricing power sits in an AI-native stack. ServiceNow looks like the best risk/reward because AI is likely to increase, not reduce, workflow complexity in the near term. Enterprises will need orchestration, governance, and auditability to connect copilots, agents, and legacy systems, which should lift seat expansion and module attach rates over the next 6-18 months. The near-term risk is multiples staying compressed if the market keeps punishing software duration, but operationally NOW has the cleanest path to surprise on durable expansion rather than just revenue stabilization. Figma is the highest-beta battleground: if Claude Design is mostly a feature, the stock can rerate sharply; if it becomes a workflow endpoint, downside remains open because design is a fast-moving, low-friction category where switching costs are more behavioral than technical. MongoDB’s issue is different: guidance softness can persist for a couple of quarters even if the AI database thesis is intact, because investors will want evidence that consumption re-accelerates before rewarding the story. The contrarian takeaway is that the market may be overestimating near-term AI cannibalization and underestimating how often AI expands software budgets by creating new workloads, compliance needs, and data sprawl.