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ServiceNow and Salesforce shares now look like buys, as ‘Armageddon’ fears are too extreme, analyst says

Artificial IntelligenceAnalyst InsightsCompany FundamentalsInvestor Sentiment & Positioning
ServiceNow and Salesforce shares now look like buys, as ‘Armageddon’ fears are too extreme, analyst says

Guggenheim upgraded ServiceNow and Salesforce, arguing AI fears have been overstated and valuations are now “too depressed.” Shares are down 33% (ServiceNow) and 38% (Salesforce) in 2026, and the analyst views the selloffs as creating a more attractive entry point despite the AI threat remaining real.

Analysis

The actionable signal here is not that AI is “safe” for enterprise software, but that the market has likely moved from pricing disruption to pricing a near-term earnings reset plus de-rating. That usually creates tradable upside when the underlying business still has enough switching costs to avoid outright churn; in other words, the first leg of pain is multiple compression, while the second leg only comes if renewal metrics start rolling over. For CRM and NOW, the key question is whether AI changes deal size and sales-cycle length more than it changes net retention — that distinction matters much more than the headline AI threat.

Relative winners are the platforms with embedded workflow and data gravity; they can defend seat economics better than point-solution SaaS because AI tends to be added into the workflow rather than replacing the workflow itself. The spillover loser set is broader: any software name where growth depends on expansion revenue or cross-sell can trade as a proxy for AI substitution risk, and that includes several IGV constituents even if they are not named here. If CRM/NOW stabilize, expect dispersion to improve and the market to stop treating all software as equally vulnerable.

Near term, this is mostly a positioning and sentiment trade over days to weeks; the real catalyst path is the next earnings season and any guidance language around cRPO, large-deal conversion, and renewal rates over 1-3 months. The contrarian miss is that the market may still be underestimating how slow AI monetization is in enterprise software: customers adopt copilots before they re-platform budgets. But if managements start cutting FY guidance or mention longer procurement cycles, this becomes a value trap quickly, and the re-rating thesis fails.

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