Every AI platform is selling to engineering and CX. Meanwhile, the function that controls the systems, workflows, and procurement decisions where AI agents would actually run (RevOps) isn't even in the conversation.
Here's something I keep noticing that nobody seems to talk about.
Every AI company in the world right now is racing to sell to two groups: engineering teams and customer experience teams. The pitch decks are polished. The demos are impressive. The landing pages are gorgeous. But the conversation stops at the high-level vision. Nobody is showing up with solutions to the tactical, operational problems these teams face every day. And the enterprise sales motions are aimed squarely at CTOs, Heads of Support, and VP Engineering.
But there's a function sitting right in the middle of every scaled revenue organization that controls the very systems, workflows, and tooling where AI agents would create the most immediate value. And almost nobody is selling to them.
That function is RevOps. And the adjacent motion is GTM.
RevOps teams at scaled tech companies make 200+ workflow decisions per week. They own Salesforce, Gong, Outreach, pipeline analytics, territory modeling, comp design, and the cross-functional alignment with Finance, Security, Legal, and the CRO/CFO office that governs how tools get adopted.
This is the orchestration layer of the GTM machine. And it's being systematically ignored by the platforms that could transform it.
I've been on both sides of this equation. I've led a multi-billion dollar P&L where RevOps drives daily decision-making: territory design, pipeline accuracy, capacity planning, the whole machinery of how revenue gets generated. And I've sold enterprise platforms where getting past the CRO required understanding the operating machinery underneath.
No AI company has approached me as a RevOps buyer. Despite the fact that my function makes 200+ workflow decisions per week that agentic tools could transform today. Not tomorrow. Not in some future state. Today.
That gap between where the need is and where the selling is happening is where there needs to be more education and context shared broadly to spur development.
It's not malice. It's pattern-matching. AI platforms default to the personas they understand: developers (because they build things) and support teams (because the use cases are obvious). RevOps doesn't fit the template. The work is too cross-functional. The systems are too interconnected. The buying process involves too many stakeholders.
But that complexity is exactly why it's such a high-leverage wedge once you're in.
| How AI Platforms See It | What's Actually True | |
|---|---|---|
| Buyer | CTO or VP Support | RevOps leader controls procurement for 8 to 12 tools where AI creates immediate value |
| Use Case | Code generation, ticket deflection | Territory modeling, pipeline analytics, comp design, board prep, forecasting |
| Complexity | "Too messy, too many stakeholders" | The messiness is the moat. Once embedded, switching costs are enormous |
| Entry Point | Top-down platform sale | Single workflow win → expand → orchestrate |
RevOps controls the operating system of revenue. Salesforce, Gong, Outreach, the analytics layer, the comp models, the forecasting cadence, the executive reporting rhythm. Every one of those systems generates workflow decisions that an AI agent could accelerate, automate, or augment today. The tools already exist. The workflows already exist. What's missing is someone actually selling to the people who run them.
And here's the kicker: RevOps leaders are sophisticated buyers. They understand systems thinking. They can evaluate ROI. They have budget authority. They're not going to get dazzled by a demo that doesn't map to their actual workflow pain. Which is exactly why most AI companies avoid them. The bar for relevance is higher.
The opportunity isn't just "sell AI to RevOps." It's that RevOps is the natural land-and-expand entry point for AI across the entire go-to-market org. Win a single workflow (pipeline hygiene automation, territory rebalancing) and you've proven value in the system of record. From there, expansion is organic because the adjacent workflows are all connected.
This is not a story about four workflows. It is a story about entire functions. Every major discipline in the revenue org carries structured, repeatable, systems-bound work that agents can accelerate today. Here is the full map.
Notice what these functions share: structured inputs, system-connected workflows, measurable outputs, and a gap between the sophistication of the work and the primitiveness of the tooling. The people doing this work are not unsophisticated. The tools they have been given are. That is where agents fit.
This isn't a "build better demos" problem. It's a motion problem. Here's what I'd tell any AI platform trying to crack this market, from the perspective of the buyer they're not talking to.
Don't pitch a platform. Pick a single workflow that's painful, manual, and measurable. Pipeline hygiene is the obvious one. Prove you can do it better than a spreadsheet + Slack combo. That's the wedge.
RevOps leaders are allergic to shelfware. We've seen too many tools get bought with big promises and die in Q2. If your AI isn't being used daily in actual workflows, you've already lost. The metric is DAU, not ARR.
RevOps doesn't operate in isolation. Getting a tool adopted means navigating Finance (for budget and comp implications), Security (for data access), Legal (for compliance), and the CRO/CFO office (for strategic alignment). If your sales team can't hold those conversations, they'll stall at the POC stage.
The RevOps teams that adopt tools successfully do it with implementation partners who sit alongside the team, understand the workflows, and drive adoption from inside. Two to three workflow specialists per account. This is what "customer success" should actually look like.
This isn't an abstract market opportunity. There's a real window, and it's closing.
Boards at every scaled tech company are now demanding measurable AI ROI from operating functions, not just engineering. That's a 12 to 24 month clock. The RevOps teams at every major scaled tech company have established functions, complex GTM motions, and board-level mandates to operationalize AI. Whoever embeds first in those workflows becomes the default.
First mover wins. Not because of technology lock-in, but because of workflow lock-in. Once an AI agent is woven into your pipeline cadence, your territory model, your forecast assembly, switching is not a tech decision. It's an operational disruption nobody will choose.
The opportunity is simple: start where workflows already exist, land with measurable wins, and expand as the orchestration layer for AI-assisted GTM.
RevOps and GTM are the functions most ripe for agentic solutions. The workflows are structured. The data is rich. The pain is quantifiable. The buyers are sophisticated. And the market is wide open.
The irony is that the very platforms building the most capable AI agents in the world haven't figured out how to sell to the people who would benefit from them most. That's not a technology problem. That's a go-to-market problem. And it's one worth solving.