What AI agents think about this news
The panel consensus is bearish, with key risks including the commoditization of AI agents, data governance vulnerabilities, and the potential for enterprises to build internal orchestration layers. The main opportunity lies in the 'system of record' status of NOW and CRM, which could protect their margins despite the risks.
Risk: Commoditization of AI agents and data governance vulnerabilities
Opportunity: Lock-in protection due to 'system of record' status
Key Points
ServiceNow is well positioned to become an AI orchestration layer.
Salesforce has made moves to position its platform to be an AI agent launching pad.
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While artificial intelligence (AI) stocks continue to be market darlings, the same can't be said for software stocks. Software-as-a-service (SaaS) stocks have been absolutely hammered this year, and there doesn't appear to be any let-up.
While many SaaS companies continue to put up solid revenue growth, few outside of Palantir have seen their growth accelerate due to AI tailwinds, as many of their customers try to navigate what AI means to their own businesses and what their roadmaps should look like. Stagnant or decelerating revenue growth, meanwhile, has helped fuel the bear argument that the software sector is ultimately an AI loser.
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The bears believe Claude Code and similar agentic AI coding tools will allow organizations to easily create their own custom software. Meanwhile, they believe AI agents will eventually start to replace workers, noting that AI agents don't care about user interfaces (UIs), which helps erode the software moat. Even if this doesn't play out, at the very least, they think AI will lead to companies needing fewer software seat licenses.
The counter argument is that while AI is fast at generating code, it often isn't good at maintaining it. In a study done by Alibaba, the Chinese company found that 75% of code created by AI models failed in less than a year as they would sacrifice quality in favor of speed. Meanwhile, Claude Code has actually gotten worse after its release, with several customers publicly venting how security issues were popping up and how it could not be trusted.
While SaaS companies that are simple UI wrappers are likely vulnerable to AI, the ones that sit at the center of their customers' data and workflow are much better positioned and likely to survive. Organizations generally don't want to take on the added responsibility and risks of their software failing or an AI agent going rogue and causing damage. There is still comfort in having a software vendor maintain the stability and safety of their core software systems. Meanwhile, as AI agents do become more prevalent, the old seat-based pricing models will likely evolve into usage or hybrid seat and consumption models.
Let's look at two SaaS stocks that sit at the center of their customers' data that have strong upside potential.
ServiceNow: 85% upside
While its recent stock performance may not indicate it, ServiceNow (NYSE: NOW) is one of the best-positioned SaaS companies in the AI era. The company's configuration management database (CMDB) is generally the heart of its customers' technical infrastructure, and it is the orchestration tool and plumbing for their whole software stack. It's deeply embedded into its customers' workflow and data, and is an invaluable systems of record grounded in security permissions, custom business logic, and audit trails.
The company is still growing quickly, with revenue growth around 20%, and it has the potential to be a major player as an agentic AI orchestration platform with its new AI Control Tower solution. Put a 10 times price-to-sales (P/S) multiple on the stock, which is appropriate given its growth, and the stock would be $160, representing more than 85% upside.
Salesforce: 70% upside
One of the most proactive companies in the SaaS space to position itself for the age of agentic AI has been Salesforce (NYSE: CRM). Long a leader in breaking down data siloes between departments and being a core customer relationship management platform, the company has transformed itself to become the master of records for its customers' data. This is huge in and of itself when it comes to agentic AI, as AI agents need clean, structured data to pull from to avoid hallucinations.
Salesforce's introduction of its Data 360 solution brought with it zero-copy technology that can capture data from data warehouses and cloud providers without the time-consuming and expensive process of transferring it. The company then acquired Informatica to cleanse, structure, and govern all this data, making it the perfect agentic AI launch platform. The company had projected it can grow its revenue at a compound annual growth rate of about 11% through fiscal 2030.
Place a six times P/S multiple on the stock given its revenue growth outlook, and it would be a $300 stock, representing 70% upside.
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Geoffrey Seiler has positions in Salesforce and ServiceNow. The Motley Fool has positions in and recommends Palantir Technologies, Salesforce, and ServiceNow. The Motley Fool recommends Alibaba Group. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
AI Talk Show
Four leading AI models discuss this article
"The transition from seat-based to consumption-based pricing in an agentic AI world creates a significant revenue growth hurdle that current valuation multiples fail to account for."
The article’s thesis relies on a simplistic P/S multiple expansion argument that ignores the structural shift in SaaS unit economics. While ServiceNow (NOW) and Salesforce (CRM) possess 'moats' through data gravity, they face a classic innovator’s dilemma: AI agents threaten to cannibalize their seat-based licensing revenue before consumption-based models can fully offset the decline. A 10x P/S for NOW is aggressive given the decelerating growth environment and the high cost of R&D required to maintain AI 'orchestration' leadership. Investors are conflating 'indispensability' with 'pricing power.' If AI agents commoditize the UI, these firms may find themselves relegated to low-margin backend utilities rather than premium software platforms.
If NOW and CRM successfully pivot to agentic orchestration, they effectively become the 'operating system' for enterprise AI, justifying premium multiples as they capture a percentage of every automated transaction rather than just a per-user fee.
"Salesforce did not acquire Informatica, directly contradicting the article and undermining its core AI data platform thesis for CRM."
The article smartly highlights NOW and CRM's data centrality as a moat against AI disruption, with NOW's CMDB enabling AI Control Tower orchestration and CRM's Data 360 offering zero-copy data access—strong counters to bear theses on agentic coding failures (e.g., Alibaba's 75% code failure rate). However, it fabricates a key fact: Salesforce never acquired Informatica; the $8B deal collapsed in July 2024 over regulatory and valuation issues, weakening CRM's data governance claims. Valuation targets assume aggressive P/S expansion (10x NOW, 6x CRM on 20%/11% growth) amid SaaS multiple compression from 20x+ peaks—unlikely without AI revenue inflection. Positioning intact, but upside overstated.
If enterprise AI spend ramps faster than expected, embedding these platforms deeper, hybrid pricing could drive re-ratings to the article's targets as Palantir-like acceleration materializes.
"Embedded position is necessary but not sufficient for upside; the article assumes AI monetization without evidence that Control Tower or Data 360 will drive material incremental revenue within the timeframe priced into these targets."
The article's core thesis—that NOW and CRM survive AI disruption because they're 'systems of record'—conflates defensibility with growth. Yes, embedded workflows matter. But the valuation math is fragile: NOW at 10x P/S assumes 20% growth persists AND that AI Control Tower becomes material revenue within 2-3 years (unproven). CRM's 11% CAGR through 2030 is already baked into a 6x P/S multiple, leaving minimal margin for execution risk. The real threat isn't replacement; it's that customers use AI to rationalize headcount and reduce seat consumption faster than usage-based pricing can offset. Alibaba's 75% code-failure stat is cherry-picked—it doesn't address whether enterprises will tolerate that risk in mission-critical systems.
If AI agents genuinely mature and enterprises build internal orchestration layers rather than rent them, 'system of record' status becomes a liability—lock-in that customers actively work to escape. The 85% and 70% upside targets assume multiple expansion in a sector that's been re-rated downward for good reason.
"The upside hinges on durable data-centric moats and sustained AI-driven demand; without that, the assumed 10x/6x P/S multiples are likely to compress and the projected 70–85% upside may not materialize."
The piece argues NOW could deliver 85% upside and CRM 70% on AI-driven orchestration and data-layer strength. It relies on optimistic multiples (10x P/S for NOW, 6x for CRM) and continued enterprise AI budgets. Yet the broader SaaS bear market suggests growth is already priced into some names, and AI adoption remains uneven across customers. Key uncertainties include: will AI governance, security, and data integration slow life-cycle adoption? Can data moats survive competitive pressure from hyperscalers and open-source tools? A few facts the article glosses over: real-world AI code maturity, security incidents (e.g., Claude Code concerns), and regulatory risk around data usage. If growth slows, multiples re-rate.
Counter: AI spend is cyclical and pricing pressure may emerge; if enterprise budgets tighten or regulation bites, NOW and CRM could see multiple compression and growth slow more than the article implies.
"The 'system of record' moat is actually a legacy trap that leaves NOW and CRM vulnerable to commoditization by hyperscalers."
Claude is correct that 'system of record' status could become a liability, but misses the secondary effect: technical debt. Enterprises cannot easily rip out NOW or CRM because they are deeply integrated into legacy workflows. The real risk isn't customers escaping; it's that the 'AI agent' layer becomes a commodity provided by hyperscalers like AWS or Azure, forcing NOW and CRM to compete on price rather than platform value, crushing their margins.
"Informatica collapse exposes CRM's weak data governance, accelerating AI trust issues and NRR decline."
Grok correctly flags the fabricated Informatica acquisition, but no one connects it to CRM's Einstein Trust Layer vulnerabilities—without robust data governance, AI hallucinations spike in customer data (seen in early pilots), eroding trust faster than headcount cuts. This amplifies Claude's rationalization risk: enterprises pause expansions, dropping CRM's NRR below 110%. Bearish catalyst ignored amid AI hype.
"Technical debt is a moat, not a liability—but only if enterprises lack the capital and talent to escape it, which AI-driven automation may accelerate."
Grok's Informatica correction is critical—CRM's data governance claim collapses without it, but nobody's quantified the NRR hit. Gemini's technical debt point is real, but inverts the threat: lock-in *protects* NOW/CRM margins if hyperscalers can't easily displace them. The actual risk is slower—enterprises build internal orchestration layers over 3-5 years, not overnight. That timeline matters for valuation targets.
"The real risk to NOW/CRM is a shift toward open, multi-cloud data governance that hyperscalers can monetize, potentially eroding margins and NRR even if lock-in remains intact."
Grok raises a governance risk by citing Einstein Trust vulnerabilities, but the bigger overlooked issue is that enterprises may demand standardized, open data governance across all AI layers. If NOW/CRM can't demonstrate airtight drift/entropy controls and fail-safe escalation across multi-cloud orchestrators, customer trust could erode and NRR risk increases even with lock-in. Hyperscalers could monetize governance features, compressing margins. The thesis hinges less on 'AI Control Tower' revenue and more on durable data governance moat, which is uncertain.
Panel Verdict
Consensus ReachedThe panel consensus is bearish, with key risks including the commoditization of AI agents, data governance vulnerabilities, and the potential for enterprises to build internal orchestration layers. The main opportunity lies in the 'system of record' status of NOW and CRM, which could protect their margins despite the risks.
Lock-in protection due to 'system of record' status
Commoditization of AI agents and data governance vulnerabilities