As artificial intelligence shifts from a buzzy conversational tool to an autonomous execution engine, enterprise software giants find themselves at a critical juncture. For ServiceNow—often dubbed the “IT workflow workhorse”—this transformation is not just a technological pivot, but a fundamental evolution of how businesses operate.

At the company’s first-ever World Forum held in India, Shireen Bhan of CNBC-TV18 sat down with ServiceNow’s Head of Engineering and Technology to decode the company’s aggressive India expansion, the stock market’s misunderstanding of AI enterprise software, the shifting paradigm of tech jobs, and the very real threat of AI agents “going rogue.”

The India Engine: From Talent Hub to Top-Three Market
ServiceNow’s decision to host its inaugural World Forum in India underscores a strategic reality: India is no longer just a back-office talent hub; it is a massive growth driver. Currently holding the company’s second-largest employee base outside the United States, India is on track to become a top-three market for ServiceNow globally.

The local traction is undeniable. ServiceNow is deeply embedded within India’s largest banks, telecom providers, healthcare systems, and both state and federal governments. Beyond consumption, India is actively building the platform’s future. Indian engineering teams have been central to developing flagship AI innovations, including:

The AI Control Tower: A governance product designed to discover, manage, and secure a company’s AI investments, ensuring rogue agents don’t wreak havoc on enterprise systems.

The Autonomous Engineer & Workflow Factory: Tools that allow rapid application development with built-in governance, automating entire life cycles of workflow management.

Localized Voice Capabilities: Building nuanced voice interactions tailored for the Indian market’s diverse languages and accents.

As the company takes specialized solutions built in India—like financial sector innovations—and exports them to markets like Southeast Asia and Australia, India has firmly established itself as a co-innovation powerhouse.

Defending the Moat: Why the Stock Market Misunderstands AI
Despite consistently meeting or beating financial estimates and raising its AI product revenue guidance from $1 billion to $1.5 billion (a massive 50% jump), ServiceNow’s stock has faced market pressure. According to the company’s engineering leadership, this disconnect stems from Wall Street lumping all software companies into the same vulnerability bucket.

The prevailing market fear is the “SaaS Apocalypse”—the idea that Large Language Models (LLMs) from frontier companies like OpenAI or Anthropic will make traditional enterprise software obsolete. ServiceNow firmly rejects this premise.

“Less than 10% of our product is the LLM,” the engineering head noted. “The rest is all IP I have built for years—understanding how workflows work, the business requirements, the context of why a decision was made. Those things are not replicable by any LLM.”

While LLMs are excellent at intelligence, reasoning, and summarization, they lack enterprise execution capabilities. ServiceNow views LLMs not as competitors, but as interchangeable commodities—much like computer chips. By running 100 billion workflows and 8 trillion transactions a year, ServiceNow owns the proprietary context and data that frontier models simply cannot access. In this era, context is the ultimate moat.

The Evolution of Work and Pricing Models
As AI fundamentally alters software development and deployment, business models are adapting. The traditional “seat-based” licensing model is fading. Over the last year, 50% of ServiceNow’s net new revenue came from non-seat-based pricing. Customers are moving toward consumption and outcome-based metrics, demanding that software directly tie to value creation, cost savings, or SLA achievements.

But what does this hyper-efficiency mean for the human workforce?

While fears of massive job displacement persist, ServiceNow views the shift as a reallocation of human potential. As AI handles routine tasks end-to-end, companies are not necessarily shrinking their headcounts; instead, they are investing those saved resources into new growth areas.

The nature of the job, however, is changing drastically. We are rapidly transitioning from “prompt engineers” to “AI managers.” Developers who used to be measured by lines of code are now measured by how many autonomous AI agents they manage. Managing a fleet of 8 to 10 AI agents requires a completely different design, security, and governance mindset than traditional coding.

The “Breaking Bad” Scenario: When AI Agents Go Rogue
Perhaps the most urgent warning from the dialogue centered on the unbridled deployment of AI agents. As we move into an “agentic future” where AI acts autonomously 24/7, the threat of these agents going rogue is real and present today.

Comparing unchecked AI agents to the trajectory of the show Breaking Bad, ServiceNow’s leadership warned that agents can start out with good intentions but quickly turn destructive if they are allowed to persist across digital networks without guardrails. A rogue agent in the financial or industrial sector doesn’t need to present a sci-fi existential threat to humanity to cause catastrophic digital and economic havoc.

This reality makes governance tools like the AI Control Tower essential. ServiceNow welcomes the push for industry structure and regulation—whether from the US or Europe—arguing that putting up guardrails doesn’t slow down innovation; it simply ensures that businesses survive it.

Looking Ahead
As the dust settles on the initial generative AI hype cycle, the winners will not be the companies that simply wrap a chatbot around a database. The winners will be platforms deeply entrenched in the enterprise operating system that combine cutting-edge, interchangeable LLM intelligence with decades of proprietary business context. For ServiceNow, betting big on India’s engineering talent and market demand is a crucial pillar in securing its place at the top of the AI-native future.