When Anthropic’s Claude Cowork rattled global SaaS stocks recently, many enterprise software companies saw their valuations dip. But for ServiceNow, the market reaction does not reflect business reality, says Sumeet Mathur, Senior Vice President and Managing Director of ServiceNow’s India Technology and Business Centre.
Calling the downturn an “overreaction”, Mathur points to strong earnings, rising AI-led revenues, and a workflow-first AI strategy that he believes positions the company differently from both hyperscalers and foundation-model players.
“We had an awesome quarter and an awesome year,” Mathur said in an interview on the sidelines of the India AI Impact Summit 2026. “We not only beat estimates, but we also raised guidance.”
Despite this, the company’s shares fell 11% on January 29, even after forecasting annual subscription revenue above Wall Street estimates. In its latest quarterly results, ServiceNow reported $3.466 billion in subscription revenue for Q4 2025, up 21% year-on-year.
AI Investment vs AI Outcomes
Mathur argues that while governments and enterprises are investing heavily in AI, outcomes remain elusive.
“Everybody is investing in AI. But investment does not automatically lead to outcomes,” he says.
He adds that AI’s promise has yet to translate into real execution, largely because it is not embedded into core enterprise processes and day-to-day operations.
That, he argues, is precisely where ServiceNow holds an advantage. The company runs nearly 80 billion workflows annually across 85% of Fortune 500 companies, giving it deep integration into enterprise operations
“When you use AI in these workflows with seamless data, security, and governance built in, you can scale AI to provide services to your customers at a scale that has never been established before,” he adds.
The SaaS Selloff: ‘An Overreaction’
Asked about recent stock market volatility triggered by AI infrastructure narratives, Mathur’s response was direct.
“Capital markets do what capital markets do. Personally, I think it’s an overreaction,” he says. “AI is a new technology. It will take time for people to parse out which companies are truly adding value and which business models may get cannibalised.”
He points to ServiceNow’s strong performance metrics, including surpassing the widely cited ‘Rule of 40’, which states that a company’s revenue growth rate and profit margin should together total at least 40%.
“We are well above 40, closer to 55. That means we’re growing revenue and doing it profitably,” he says.
ServiceNow has projected that Now Assist, its generative AI solution, could reach $1 billion in annual contract value by 2027. In the latest quarter, it surpassed $600 million in annual contract value, more than doubling year over year.
Partnerships, Not Competition
Despite market narratives positioning foundation-model companies such as OpenAI and Anthropic as competitive threats to SaaS firms, Mathur frames the dynamic differently.
“Everybody is our partner,” he says. “Whether it’s NVIDIA, Microsoft, Google, Anthropic, or OpenAI, our architecture is flexible and extensible.”
Mathur reveals that ServiceNow integrates with multiple LLMs and cloud platforms, allowing customers to choose their infrastructure while layering AI on top of enterprise workflows.
“Most large language models are reasoning ones. But reasoning only works when it’s rooted in a business context, in your data and your processes,” he says. “We turn intelligence into action.”
Practising What It Preaches
To demonstrate real-world value, ServiceNow deploys its AI products internally first, a philosophy Mathur refers to as ‘Now on Now’.
“We have over 27,000 employees globally. We use our own products first. If it works for us, it will work for our customers,” he said.
According to Mathur, these internal AI deployments have generated approximately $325 million to $350 million in annualised savings.
“More than 70% of our IT cases are now auto-resolved,” he says, referencing the company’s autonomous L1 digital worker initiative. AI agents are also active across HR help desks, customer support, and developer productivity workflows.
“When we look across IT, HR, customer support, and developer velocity, the productivity gains are significant,” he adds.
Securing Agentic AI and Making Enterprise Data Usable
As enterprises adopt agentic AI, Mathur said the challenge is no longer experimentation but control.
He notes that while pilots are easy to execute, production deployment raises governance concerns. “It’s very easy to do PoCs on AI. It’s very hard to get it into production. Because as soon as you get into production, security comes into play, risk comes into play.”
To address this, he points to ServiceNow’s acquisition of Veza and its Access Graph capability. “It is able to provide you with who is accessing, with what permission, what resources, at what time, so you can provide the security layer on top of your agentic AI,” he says.
The company’s acquisition of Armis extends that security layer beyond software users. “Today, we talk about agentic AI on the surface. But there is IoT, medical devices, and other sensors that are also getting agentified. It is increasing the threat level of your enterprise,” Mathur says. Armis, according to him, provides “one singular place where you can have a security graph… for all things in your enterprise, beyond your software and humans.”
On the data side, ServiceNow has also expanded through acquisitions such as Moveworks and Pyramid Analytics to improve how enterprises extract business value from disparate systems. “You need to understand the semantic value of that data, not just the raw data and how it is relevant in your business process,” he says.
He explains that this allows enterprises to query data conversationally while preserving business context. “Pyramid Analytics provides that data analytics layer… so that a human-like interface can ask questions and get responses in a conversational way. That is data-driven.”
Why ServiceNow Believes It Has an Edge
Compared with hyperscalers and foundation model providers, Mathur argues that ServiceNow’s competitive advantage lies in its two decades of managing enterprise workflows.
“They don’t have the 20-year context of business processes and workflows,” he says. “Large enterprises require extensibility and integration across multiple vendors. That’s what we enable.”
The company operates across infrastructure layers, supporting AWS, Azure, and Google Cloud, while maintaining neutrality in model choice and governance.
Tool for Inclusivity
For Mathur, India represents not just a market opportunity but a societal use case for AI.
“In India, the power of AI is not just automation—it’s inclusivity,” he says.
He argues that AI-embedded workflows can democratise personalised services at a population scale, across banking, healthcare, or public services.
“For decades, personalised services were reserved for the privileged,” he says. “With AI and workflows combined, you can provide personalised service at a national scale.”
Moreover, ServiceNow has also committed to enabling one million learners by 2027 on its platform, with over six lakh active learners already. The company has partnered with 26 universities and industry bodies to expand AI and workflow skills training.
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