Bhawna Mittal

I'm the Head of Operations at Netomi, where we're building AI as the execution layer for enterprises. But the thing I actually work on is older than AI: why brilliant organizations, full of capable people, so often fail to do the thing they already know how to do. I came to Silicon Valley from India, and from the business side rather than the technology side, which meant I was never quite dazzled by the technology the way the people around me were. I noticed something else instead. I'd sit in rooms full of brilliant people, a customer asking for something we could absolutely build, the capability sitting right there on the table and nothing moving. Not because it was hard. Because no one owned it. My question was always the naive one: so who's actually driving this forward? It took me years to understand that it isn't a naive question. In most organizations it's the only one that matters. I think I saw it because of where I come from. I grew up first generation, in a household where someone always had to own the outcome. There was no slack, no "someone will handle it." You learn early that clarity about who's responsible isn't bureaucracy, it's how anything gets done at all. That's the lens I bring to AI. Everyone wants to talk about the models. I want to talk about the org underneath them. Because AI execution isn't a technology problem, the technology is ready. It's an accountability problem: who owns the outcome when the model acts, whose job actually changes, who's answerable when it's wrong. Enterprises are spending fortunes and seeing almost nothing move, and it's almost never the tech. It's that no one redesigned the organization around it. I've spent my career in that gap. At ServiceNow I helped scale the business from roughly $7B to over $11B in ARR. At Automation Anywhere I worked at the intersection of automation, enterprise workflows, and transformation at scale. Same pattern every time: the pilot succeeds, the demo impresses, and then the work quietly absorbs it and nothing reaches the P&L, because no one owned the change. I'm most interested in the conversations one level up from the hype: board level questions about AI governance and accountability, what an AI-native enterprise is actually structured like, and how leadership teams operationalize this beyond the pilot. If you treat AI as infrastructure for execution rather than a tool you bought, we should talk. Someone has to own the outcome. I usually volunteer.