Alongside cybersecurity, ServiceNow is building its case as a larger force in CRM, placing it in more direct competition with Salesforce and other established front-office technology suppliers. The vendor has been viewed primarily as an IT service management (ITSM) company with growing ambitions beyond the back office. Now, it is making a much more direct play, arguing that enterprise AI is changing what organizations expect from CRM platforms.
During the company’s second-quarter earnings call, Bill McDermott, ServiceNow’s Chairman and CEO acknowledged that ServiceNow’s rivals are deeply embedded in the enterprise market, but said the company is gaining ground as an “operational CRM platform” that connects sales, service, configure, price, quote (CPQ), field operations and AI through enterprise-wide workflows.
While some investors are questioning whether AI could weaken the position of traditional software as a service (SaaS) vendors by allowing enterprises to build more software themselves, industry analysts suggest the early reality of enterprise AI deployment may strengthen platforms such as ServiceNow.
“The market has overestimated the threat of AI to ServiceNow and other SaaS providers,” said Rebecca Wettemann, CEO and Principal Analyst at Valoir.
“As organizations have struggled to put AI into production, they’ve realized that vibe coding isn’t a realistic or cost-effective option to packaged software – they still need the underlying software and data for the context to make AI work effectively.”
Rather than presenting AI as another assistant layered on top of customer data, ServiceNow is arguing that AI delivers greater value when embedded within operational workflows that span multiple departments.
McDermott: ServiceNow Is Already a $2BN CRM Player
“We also get asked, ‘Is ServiceNow gaining traction in the CRM marketplace?’ Here’s the answer,” McDermott said. “The market participants in the enterprise are very good. They’re really good companies. Let me be clear, they’re not going away. Having said that, we’re doing very well.”
ServiceNow’s CRM business is already a $2BN annual contract value (ACV) operation, McDermott said. The company expects to process more than 2 billion customer service cases during the year.
McDermott cited several recent competitive wins, including a partner-led replacement of a major CRM platform completed in two months, a North American automotive marketplace that selected ServiceNow after its previous CPQ platform failed to cope with increasing transaction complexity, and a regional financial institution consolidating loan-origination workflows onto the company’s CRM platform.
A North American telecommunications infrastructure provider also chose ServiceNow to connect commercial and field operations. According to McDermott, the deployment is expected to triple quote volumes without increasing headcount while reducing repricing from weeks to hours.
ServiceNow cited these as examples of organizations looking beyond traditional CRM functionality toward workflow automation that extends across sales, service and operations.
Customer Deployments Suggest Enterprises Want AI That Executes Work
ServiceNow’s recent customer announcements reinforce that message.
Alongside its earnings results, the company unveiled a five-year expansion agreement with Experian, a strategic partnership with TeamViewer, new public-sector deployments across nearly all 50 U.S. states and a large employee experience transformation at Leidos.
The announcements illustrate where many enterprise AI projects appear to be heading. Rather than introducing another generation of customer-facing chatbots, the projects focus on embedding AI within operational processes.
Experian plans to combine its data and decisioning capabilities with ServiceNow workflows to support customer and employee operations. TeamViewer is integrating remote connectivity with ServiceNow’s AI platform to allow AI agents to identify IT issues, establish secure remote access and carry out remediation. Leidos will use the platform to streamline HR, IT and workplace services for approximately 50,000 employees, while government deployments focus on modernising internal operations rather than simply improving citizen self-service.
The common thread is AI that performs work instead of simply recommending the next action. That does not necessarily mean autonomous enterprise AI has arrived. Many organizations are still working through governance, security and change-management challenges before allowing AI to execute business processes independently. But buyers are increasingly evaluating AI as part of broader workflow transformation initiatives rather than standalone productivity tools.
McDermott also pointed to voice AI as an area where ServiceNow believes it can differentiate itself.
“Voice is the next frontier, we’re winning it,” he said, highlighting a large airline that has deployed ServiceNow’s AI-powered CRM voice agents.
“This is live in production and handling 5 million annual voice calls in year one alone. The results speak for themselves. Customer satisfaction is off the charts.”
ServiceNow Pushes Back on Outcome-Based AI Pricing
ServiceNow is also making pricing a central part of its argument against competitors, including Salesforce, as vendors experiment with consumption, token-based and outcome-based AI models.
“We’ve been very clear in terms of keeping our pricing very customer friendly,” Amit Zavery, President, Chief Product Officer, and Chief Operating Officer at ServiceNow, said. “Hybrid pricing structure, which we introduced, where it’s combination of license and usage directly applies to giving the customer predictability and flexibility.”
“When you use more, that means you are getting good outcomes, otherwise you will not use more,” Zavery added. “Outcome is already tied in the underlying assumption of usage.”
ServiceNow’s position is that outcome-based commercial models can make contracts harder to measure and manage in enterprise environments.
“Trying to define another metric, which is very hard to understand or measure, and then have to go back and forth in terms of contracts and everything else in enterprise software doesn’t work,” Zavery said.
McDermott added that customers continue to favor predictable seat-based commercial terms even as non-seat-based consumption expands.
“We keep seat-based pricing because customers prefer it for predictability, particularly now, where a lot of pricing out there has been less than predictable.”
At the same time, McDermott noted that 50% of the company’s net new business is already non-seat based, reflecting growing demand for AI-driven consumption models without abandoning predictable commercial structures.
ServiceNow’s Secret Weapon: Workflow Context
Beyond pricing, ServiceNow believes its biggest advantage lies in enterprise context. Unlike AI vendors that retrieve and process customer data outside their own operational systems, Zavery argued that decades of operational workflow data provide richer context for AI decision-making.
“Our context is for us to really get a better result for our customers. Our competitors don’t get access to it, neither do LLMs. That’s really where the secret sauce is.”
“[W]hen we run 7 trillion workflows on our platform, we are collecting so much intelligence, which can really change the game for our customers from the usage perspective and the results perspective. That’s where the differentiation comes in, and nobody else has that today,” Zavery added.
Wettemann said ServiceNow’s workflow heritage remains a key advantage as enterprises work out where AI is genuinely needed, and where traditional automation is cheaper and more reliable.
“ServiceNow is a workflow leader, and that hasn’t changed. It’s important to remember that a declarative workflow is always more cost-effective than an LLM call if a workflow can do the job, which plays to ServiceNow’s advantage. Early AI efforts have shone the light on automation opportunities that don’t need probabilistic AI and there’s a lot of opportunity for the ServiceNow platform there.”
ServiceNow is also seeking to keep its own AI costs low by selecting the most appropriate model for each task, rather than treating frontier large language models as the default option.
“Large language models are getting commoditized,” Zavery said. “There is no reason for using some of the most expensive ones.”
The vendor uses a mix of open-weight, proprietary, domain-specific and frontier models, depending on the workload. “We really optimize across the board to ensure we’re getting the best outcome while keeping the costs low,” Zavery explained.
ServiceNow’s CRM Push Is Really an Enterprise-Control Play
ServiceNow’s message is ultimately that AI adoption is making fragmented enterprise technology environments harder to govern, and that its workflow platform gives it a route to address those problems beyond ITSM.
McDermott said the company is increasingly becoming relevant to senior executives because it can sit above disconnected systems and connect AI to business processes.
“Many of them have such a fragmented enterprise that they need to take advantage of our workflow automation above the mess and click in that AI engine into this unbelievable platform and really begin running.”
“The higher you go in the C-suite, the more relevant we are,” McDermott added. “The more the C-suite realizes that we’re in the bull’s eye of what has to happen to fundamentally be the control tower for reinventing these businesses.”
Whether that strategy is enough to displace established CRM incumbents remains an open question. Salesforce and other market leaders remain deeply embedded in enterprise sales and service organisations, and AI alone is unlikely to change that overnight. But the competitive debate is clearly expanding beyond CRM features.
