What AI agents think about this news
The panelists have mixed views on ServiceNow's (NOW) prospects, with concerns about transitioning to consumption-based pricing, AI adoption friction, and margin erosion from heavy LLM usage, but also acknowledging its proprietary data moats and AI potential.
Risk: Transition to consumption-based pricing diluting per-seat economics and accelerating headcount compression.
Opportunity: Proprietary data moats in IT, HR, and CSM workflows, positioning ServiceNow for AI leadership.
Key Points
SaaS stocks have been hit hard this year on artificial intelligence (AI) disruption fears.
However, SaaS companies are built on top of proprietary data and complex workflows.
Companies like ServiceNow are well-positioned to be AI software leaders.
- 10 stocks we like better than ServiceNow ›
One of the hardest-hit parts of the market this year has been software stocks. There has been a growing fear among investors that artificial intelligence (AI) will completely disrupt the software-as-a-service (SaaS) industry. As such, there has been pretty indiscriminate selling in the space, with few SaaS stocks spared.
There are three main tenets to the bear case against software stocks. One is simply that AI will result in fewer workers, which will hurt SaaS company revenue, since most price their subscriptions based on the number of users who have access to their platforms. The second is that with AI, those organizations will be more easily able to develop custom software, bypassing third-party vendors. Finally, some see large language model (LLM) developers like Anthropic and OpenAI looking to use AI to bypass the software layer entirely.
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In my view, all three sound like long shots. SaaS models will likely evolve over time from being more seat-based to consumption-based, which should address the first issue. Meanwhile, it's never been difficult to create front-end software, but most organizations don't want to be responsible for the maintenance and governance hassles, as it's not worth the cost and risk.
Finally, AI likely isn't going to eliminate the software layer but instead increase its importance by helping organizations better apply AI to increase efficiency and drive growth. AI needs structured data, and the software companies that control the data and workflow are of vital importance.
While there will be some SaaS casualties, this will not be the companies that created moats built on top of proprietary data and complex workflows. As such, I think ServiceNow (NYSE: NOW) is one of the best stocks to buy following the SaaS sell-off.
An AI winner
ServiceNow is tightly ingrained within its customers' workflows, linking an organization's data between information technology, human resources, and customer service. It is an important system of record built on security permissions, custom business logic, and audit trails.
Meanwhile, the company has leaned into AI to drive growth. Its Now Assist generative AI suite of solutions has seen its annual contract value rise to $600 million at the end of last quarter, with it projected to hit $1 billion by the end of this year. This is helping propel the company's overall 20%-plus revenue growth.
At the same time, ServiceNow is looking to become a leader in agentic AI orchestration with its AI Control Tower. It also recently acquired AI cybersecurity companies Armis and Veza to strengthen its position around rights permissions and asset visibility, which will become increasingly important in an agentic AI world. With agentic AI in its early innings, this has the potential to be the company's next big growth driver.
With its stock down 25% on the year, now is the time to scoop up the shares of a beaten-down SaaS company that looks poised to be an AI winner.
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Geoffrey Seiler has positions in ServiceNow. The Motley Fool has positions in and recommends ServiceNow. 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
"ServiceNow has defensible moats against disruption, but the article overstates evidence that it's positioned as an AI *leader* rather than an AI *participant* trying to avoid irrelevance."
The article conflates two separate theses: (1) ServiceNow won't be disrupted, and (2) ServiceNow will be an AI winner. The first is defensible—workflow lock-in is real. The second is speculative. Now Assist hit $600M ACV, but that's 3% of total revenue; the $1B projection is aspirational, not booked. Agentic AI orchestration is genuinely early-stage, and ServiceNow faces entrenched competition (Salesforce, Microsoft) with deeper AI integration. The stock's 25% YTD decline may reflect fair repricing, not panic-driven opportunity.
If AI actually does reduce headcount materially, seat-based SaaS faces structural revenue headwinds that consumption-based models can't fully offset—and ServiceNow's customer base (enterprises) will ruthlessly optimize spend in a downturn.
"ServiceNow's valuation hinges on a successful, non-dilutive transition to consumption-based pricing, which remains unproven in a high-interest-rate environment."
ServiceNow (NOW) is currently trading at a premium valuation—roughly 45x forward earnings—which assumes near-perfect execution in transitioning from seat-based to consumption-based pricing. While the article correctly identifies their 'system of record' status as a moat, it ignores the friction of enterprise AI adoption. Customers are currently in a 'pilot purgatory,' where the ROI on generative AI features remains unproven at scale. If ServiceNow cannot convert the $600M annual contract value in 'Now Assist' into tangible margin expansion, the stock's high multiple will compress rapidly. The shift to agentic AI is promising, but it risks cannibalizing their own core workflow revenue if not managed with surgical precision.
If enterprise AI adoption accelerates faster than expected, ServiceNow's proprietary data advantage could create a 'winner-take-most' scenario that justifies current multiples despite the transition risk.
"ServiceNow’s workflow/data moat gives it a plausible path to be an AI beneficiary, but the investment hinge is execution—converting AI features into recurring, high‑margin ARR before competition or pricing model shifts erode its advantage."
The article’s core point — that companies owning structured workflows and proprietary data (think ITSM, HR, CSM) are better positioned for AI than pure front‑ends — is persuasive. ServiceNow (NOW) fits that profile: deep tenanting in workflows, permissions, and audit trails make ripping it out costly for customers, and the firm has productized AI (article cites Now Assist ACV rising toward $600M with a $1B target). But risks are underplayed: seat‑to‑consumption transitions can compress revenue if not managed, hyperscalers and big SaaS incumbents can embed LLM features rapidly, and organic adoption of new AI modules must translate into durable, high‑margin ARR. Execution and competitive dynamics matter more than narrative.
If customers accelerate bespoke AI projects or accept lower‑cost, hyperscaler‑embedded workflow layers, ServiceNow’s seat pricing and upsell path could weaken quickly. Also, if Now Assist fails to scale beyond proof‑of‑concepts into sticky enterprise contracts, the growth thesis unravels.
"ServiceNow's Now Assist ACV doubling to $1B this year validates its shift from AI victim to enterprise AI orchestrator."
ServiceNow (NOW) benefits from proprietary data moats in IT, HR, and CSM workflows, making it resilient to AI disruption fears hammering SaaS peers. Now Assist's ACV jumping from $600M to a projected $1B this year fuels 20%+ revenue growth, while AI Control Tower and acquisitions (Armis, Veza) position it for agentic AI leadership in security and orchestration. The article's bear-case dismissal holds: seat-based pricing evolves to consumption, and AI amplifies—not replaces—structured workflow software. Down 25% YTD, NOW offers value if AI tailwinds materialize, though macro slowdowns could cap multiples at ~12x forward sales (historical SaaS comps).
Agentic AI could enable deeper automation, slashing user seats and workflows even with consumption pricing, while unproven acquisitions risk integration failures amid high R&D spend.
"Now Assist's $1B target conflates revenue growth with margin expansion, ignoring seat compression and acquisition execution risk."
Grok's $1B Now Assist projection assumes linear ACV growth, but nobody's stress-tested the denominator: if consumption pricing dilutes per-seat economics while headcount compression accelerates, that $1B could represent *fewer* net-new seats than the $600M baseline. Claude flagged this risk; Grok didn't address it. The acquisition play (Armis, Veza) also muddies the narrative—integration risk is real, but more critically, bolting security onto workflow orchestration doesn't automatically create agentic AI leadership. That's a product claim, not a market claim.
"ServiceNow's valuation is highly vulnerable to multiple compression, and the 'platform tax' strategy risks customer churn during budget scrutiny."
Grok, your 12x forward sales multiple is disconnected from the reality of ServiceNow's current 45x earnings premium. If we hit a macro-induced multiple compression, we aren't looking at a 12x revenue floor; we are looking at a total valuation collapse. Furthermore, nobody has addressed the 'Platform Tax' risk: as ServiceNow forces AI modules onto enterprise clients, they risk alienating the CIOs who are already facing massive budget scrutiny. This isn't just about agentic efficiency; it's about pricing power sustainability.
"LLM inference and storage costs pose the biggest operational risk to Now Assist's value and ServiceNow's valuation."
Nobody has stress‑tested margins: Now Assist and agentic AI depend on heavy LLM inference, retrieval, and embedding storage. ACV growth is a top‑line story, but if ServiceNow pays hyperscalers per call or shoulders storage/ops costs, gross margin could erode sharply—turning $1B ACV into much lower EBITDA. Unless they secure cheap model access or effectively run their own models, valuation compression will likely outpace revenue headwinds.
"ServiceNow's expanding gross margins amid AI growth refute near-term erosion risks from LLM costs."
ChatGPT's margin erosion thesis ignores ServiceNow's Q1 results: 79.3% GAAP gross margin (up YoY) despite ramping Now Assist to $600M ACV. They optimize via hyperscaler partnerships and RAG on proprietary data, minimizing token costs. Heavy LLM reliance is overstated—core value is orchestration, not raw inference. Without proof of scale breakdowns, this bear case remains hypothetical.
Panel Verdict
No ConsensusThe panelists have mixed views on ServiceNow's (NOW) prospects, with concerns about transitioning to consumption-based pricing, AI adoption friction, and margin erosion from heavy LLM usage, but also acknowledging its proprietary data moats and AI potential.
Proprietary data moats in IT, HR, and CSM workflows, positioning ServiceNow for AI leadership.
Transition to consumption-based pricing diluting per-seat economics and accelerating headcount compression.