Rahul Tripathi is SVP & GM of the Service Operations Business Unit at ServiceNow, responsible for ITSM, ITOM, and CMDB/ServiceGraph. Previously he served as CPTO at Skytap and CTO at Nutanix.
I've spent the better part of three decades building technology products—at Cisco, HP Enterprise, Nutanix, and now ServiceNow. Long enough to have watched a lot of bold claims get quietly walked back when they met real enterprise IT at scale.
So when I say I'm proud of our G2 rankings this spring, I want you to understand what I mean. I'm not proud of a number on a slide. I'm proud of what the number represents: tens of thousands of IT practitioners—people who live inside these tools every day, who deal with the incidents at 2 a.m. and the budget conversations in the boardroom—choosing to say, publicly, that ServiceNow works.
"These aren't scores we gave ourselves.
They're scores you gave us."
That's different from a press release. That's different from a well-produced demo. That's someone putting their name on it.
What the numbers say
Across G2's Spring 2026 Grid Reports, ServiceNow has claimed the #1 position in four enterprise IT categories:
- IT Service Management (ITSM) — #1 Overall
- IT Operations Management (ITOM) — #1 in AIOps, Enterprise
- IT Asset Management (ITAM) — #1 Enterprise
- Strategic Portfolio Management (SPM) — #1 Overall
These are scores you gave us. G2 rankings are derived from verified user reviews—people who've gone through procurement, implementation, and years of live operation. The platform earned these by solving real problems for real organizations, not by winning a feature checklist comparison.
Together, these four products represent the backbone of what we call Autonomous IT and Security: the idea that your IT estate—service requests, infrastructure health, asset lifecycle, portfolio priorities—should run as an integrated, AI-native system. Not four islands of tooling. One platform, with your team in control of the guardrails.
The question every IT leader should be asking right now
Enterprise IT is at an inflection point. Everyone—and I mean everyone—is showing up with an AI story. Some of those stories are genuinely exciting. Some are well-funded. Some have great marketing teams.
But here's the question I'd encourage any IT leader to sit with: How many of those vendors have done this at scale, in production, in your industry, for more than a product cycle?
There's a category of technology companies that built their reputations somewhere else entirely—in CRM, in productivity suites, in consumer applications—and are now, quite loudly, announcing that they've cracked enterprise IT. They're smart companies. Capable engineers.
But capability in one domain doesn't transfer automatically to another. Enterprise ITSM and ITOM aren't just technically hard. They're operationally complex in ways that take years to understand at depth: the nuance of a major incident during a quarterly close, the politics of a CMDB that three different teams own, the challenge of getting a 50,000-person company to adopt a new change management workflow.
Then there's another category: AI-native startups and model providers who can demonstrate extraordinary capabilities in controlled settings. I find this work genuinely fascinating—I follow it closely. But there's a gap between a compelling proof-of-concept and an AI system you can run your enterprise on with the governance, auditability, and reliability your board expects. That gap is called production. It's where promises meet SLAs.
G2 rankings are a measure of what's actually working, at scale, for real enterprise customers. That's why I think they're one of the most honest signals available to an IT buyer.
"Capability in one domain doesn't transfer automatically to another. Enterprise IT is operationally complex in ways that take years to understand at depth."
Why platform breadth matters more than it used to
Earlier in my career, the "best of breed vs. platform" debate was mostly theoretical. You could wire together best-of-breed tools and, with enough integration work, get something that mostly functioned.
AI changes that math fundamentally.
When AI agents are making decisions—prioritizing incidents, routing requests, triggering automated remediations—the quality of those decisions depends entirely on the quality of the data and context they can see. A siloed ITSM tool with AI bolted on doesn't know what your CMDB says about the affected CI. It doesn't know that the asset that just failed is two weeks from end-of-life. It doesn't know that the affected service supports your most revenue-critical process.
Effective AI in enterprise IT depends on a unified data model. That’s a systems architecture requirement. ServiceNow has spent years building toward that model. ITSM, ITOM, ITAM, and SPM run on the same platform and share context and operational data—our Common Service Data Model. When customers rank ServiceNow #1 across all four categories, they’re recognizing the value of that integrated foundation. Each capability strengthens the others because they were designed around the same view of how modern IT should operate.
A note on what 'proven' actually means
When I joined ServiceNow, one of the things that stood out to me was the depth of the customer relationships. You tell us how they feel in an honest, ongoing dialogue that produces real product improvement. The reviews on G2 are a public artifact of that conversation. You include praise alongside sharing the things we still need to get better at. That's healthy. That's what earning your trust looks like over time.
Outside of work, I spend time as a certified breath meditation instructor with the Art of Living Foundation. There's a concept I come back to often: the idea that sustained practice—not a single moment of brilliance, but consistent, disciplined effort over time—is what produces outcomes that last. I think that applies to enterprise software. The rankings we earned this spring are the product of sustained practice. Of listening to customers, shipping improvements, and doing the unglamorous work of making complex systems actually reliable.
If you're an IT leader evaluating where to place your bets in this AI moment, I'd encourage you to look hard at proof over promise. Ask who's been doing this work for years, not months. Ask who your peers—the ones who've already gone through implementation and are now in year three or four of live operation—are actually recommending.
The G2 rankings will tell you part of that story. So will the 10,000+ verified reviews behind them.
Read more about the rankings, including product breakdowns, here.
