ServiceNow AI Adoption Lifts Price Targets Amid Pricing Doubts

Analysts turn more optimistic

Two Wall Street firms raised their price targets on ServiceNow this week, citing signs that customers are using the company's AI features more heavily. Stifel analyst Brad Reback lifted his target from $120 to $160 and kept a Buy rating. UBS analyst Karl Keirstead raised his target from $110 to $150 but held a Neutral rating. 1

The split in ratings is telling. Both firms see improving fundamentals, but only one is ready to recommend buying. Reback described a modest sequential improvement in ServiceNow's enterprise spending environment, supported by elevated deal activity, healthy renewals and growing uptake of the company's Advanced SKUs, its higher-tier packages that bundle AI capabilities. 1 He also said early indicators show consumption trends gaining momentum, broadly in line with what management expected. 1

The caveat came in the same note. Some customers remain unsure about ServiceNow's AI-enabled products and how they are priced. 1 For a company betting on AI to drive its next phase of growth, that uncertainty is the main risk.

The numbers behind the enthusiasm

ServiceNow has supplied its own figures to support the bullish case. According to the company, AI usage rose ninefold from the first quarter to the second, more than 50 customers now pay over $1 million for its new AI packages, and it raised its 2026 AI target from $1 billion to $1.5 billion. 2

The company has also pointed to customer outcomes. It cites a 65% reduction in IT service-desk costs for Raleigh and potential savings of more than $5 million for a European energy company from agentic workflows. 2 These are vendor-reported figures and should be read that way. Still, they show the pitch ServiceNow is making: AI agents that measurably cut operating costs, rather than copilots that are merely nice to have.

Speaking at Citi's TMT conference, ServiceNow's Mastantuono said customers are starting to look past productivity gains toward business-model innovation and new revenue. She also acknowledged that security and risk management are consistently the biggest obstacles customers raise when they consider deploying AI at scale. 2

Products aimed at the adoption bottleneck

ServiceNow's recent product announcements look designed to address the hesitations analysts are hearing. The AI Control Tower is meant to help enterprises secure, govern and manage AI agents across platforms. It also lets them monitor costs, control spending and measure return on investment. 2 That covers both concerns raised in the analyst commentary: customers worried about risk, and customers unsure what they are paying for.

The company also introduced AI Workflow Factory and Autonomous Engineer. Together they combine process discovery, AI-assisted development and workflow execution in a single system. 3 Workflow Factory links Process Mining, Autonomous Engineer, Build Agent and App Engine:

• Process Mining finds processes worth improving based on business metrics.
• The development tools build and test changes.
• App Engine runs the resulting workflows at scale. 3

ServiceNow calls this a "continuous workflow improvement loop," in which the results of one improvement point to the next opportunity instead of each change starting as a separate project. 3

This framing matters commercially. Many enterprises have struggled to move AI beyond scattered pilots. A system that keeps generating new automation targets would also tend to generate steady consumption, which is the trend Stifel says is building. 1

Reading the signals

All three accounts point in the same direction. AI usage on ServiceNow's platform is rising, larger customers are paying for premium AI tiers, and the company is building governance and automation tooling to keep that growth going. Where they differ is emphasis. The company's own messaging focuses on scale and savings. The analyst view is more cautious, noting that customers are still confused about pricing. 12

My reading is that the cautious view deserves more weight. Consumption-based AI pricing is still new for enterprise software buyers used to predictable seat licenses. Rising usage is good for ServiceNow's revenue, but it can make budgets harder for customers to forecast. A cost-monitoring dashboard like the Control Tower helps, but it also suggests customers need help understanding their bills. UBS's decision to stay Neutral while raising its target fits that view: the business is improving, but how customers will respond to AI pricing over time is still uncertain. 12

If ServiceNow can turn early savings stories into clear, repeatable ROI and simplify how it charges for AI, the higher targets may prove conservative. If pricing confusion persists, adoption could stall at the governance and procurement stage, where many enterprise AI projects already slow down.