2 AI Stocks With 85% and 70% Upside to Buy During a Software Bear Market

The article argues that ServiceNow and Salesforce are better positioned than many SaaS peers to benefit from agentic AI because they sit at the center of customer data and workflows. ServiceNow is projected at $160 per share, implying more than 85% upside on a 10x P/S multiple, while Salesforce is modeled at $300 per share, implying 70% upside on a 6x P/S multiple. The piece is bullish on the long-term AI positioning of both companies, though it is primarily an analyst-style commentary rather than new company-specific news.

Analysis

The market is still treating AI as a reason to short SaaS multiple durability, but the deeper issue is control points. Vendors that own workflow state, permissions, and auditability become the enforcement layer for agents; that makes them harder to displace than front-end apps even if code generation gets cheaper. The second-order winner is not generic SaaS, but vendors whose data gravity lets them sit between LLMs and enterprise systems of record.

NOW looks better than CRM in the nearer term because orchestration is a budget line item enterprises are already paying for, while CRM’s upside depends more on data cleanup and integration projects that tend to elongate sales cycles. If agentic adoption accelerates, spend likely shifts from seats to governance, observability, and workflow automation, which expands the addressable wallet for platform vendors even as headline seat counts flatten. That implies the bearish “fewer licenses” narrative is directionally right on units but wrong on revenue mix; the real risk is price compression, not outright demand collapse.

The contrarian miss is timing: this is a 12-24 month monetization story, not a next-quarter earnings catalyst. Near term, both names remain vulnerable to multiple compression if buyers keep waiting for AI to show up in booked revenue, and the market may punish any sign that AI features are still experimental. The clearest disconfirming signal would be enterprise proof of rapid AI-driven workflow expansion without corresponding services drag or security incidents; absent that, the best setup is to own the control plane and fade the wrappers.

PLTR is the cleanest beneficiary from the “trusted data + workflow” thesis, but it is already priced as if the platform victory is obvious, so upside is more fragile than NOW/CRM. INFA is a more interesting sleeper because data governance becomes more valuable when agents proliferate, but integration risk and execution complexity cap near-term multiple expansion. BABA is a separate optionality bucket: if its AI stack improves enterprise trust in its cloud/data tools, it can benefit indirectly, though that path is less visible and more execution-dependent.

Key Decisions for Investors

• Long NOW vs short a basket of UI-light SaaS names for 3-6 months; own the control-plane winner and fade companies most exposed to seat-count erosion. Target 1.5-2.0x relative outperformance if AI spend shifts toward governance/orchestration.
• Buy NOW 6-12 month call spreads on pullbacks; structure for upside to a re-rate while defining risk if the market keeps discounting AI monetization. Prefer strikes that monetize a move toward the next multiple expansion regime rather than a full fundamental rerating.
• Pair long CRM / short a high-duration software basket for 6-9 months only if you want data-platform optionality with less binary AI hype risk than PLTR. CRM is the cleaner “picks-and-shovels” beneficiary if enterprises prioritize data hygiene before agent rollout.
• Avoid chasing PLTR here; if already long, consider trimming into strength and rotating into NOW or INFA for better asymmetry. PLTR has more narrative beta but less valuation slack if adoption takes longer than expected.
• Watch INFA on any pullback as a delayed-beneficiary candidate over 12-18 months; initiate only if the market prices it as an integration asset rather than a platform compounder. Risk/reward improves if enterprise data-governance spend accelerates faster than core app spending.