What does the AI-Native GTM org actually look like?
As a new CMO, I'm thinking about this often. Every GTM leader I know is too. It's early and the shapes are forming now in role specs, org charts, and job changes.
Laurel ($150M funded) just posted "AI Ops & Strategy, GTM."
This fits a new pattern: Agent Operators
Laurel’s post is another example of dedicated AI builders inside the GTM org. They build agents, automate workflows, and help everyone else use AI better. One strong builder lifts the whole team. It's taking different names, but the same idea is showing up in forward-thinking companies.
Zapier created a Director of GTM Innovation role. Lindsay Rothlisberger promoted from Director of RevOps. Her mandate, in her words: "How AI can make revenue teams faster and sharper, and customer experiences smoother."
Ramp is hiring an "Agentic Operator, Growth Marketing." $168-231K. JD requires you to be "extremely AI-pilled." I wrote this one up earlier this month.
xAI named theirs "Head of GTM Systems & Agents." $200-400K base. The JD line that stopped me when I wrote about this in February: "deploying AI agents that directly generate revenue."
Anthropic posted "Head of GTM Systems" that naturally has a large AI builder bent.
Across the 200 top AI companies I track, "GTM Systems" is often found in the title and the JDs point to the centralized AI builder and agent operator duties. Sometimes it's a RevOps evolution. Other times it's a new function.
AI GTM Jobs tracker → adamgtm.com/jobs
Aaron Levie has been arguing for the umbrella version. I like his framing best, from his April 13 Tweet:
"the more enterprises I talk to about AI agent transformation, the more it's clear there is going to be a new type of role in most enterprises going forward. The job is to be the agent deployer and manager."
He draws this picture:
Source: Aaron Levie
He predicts 500K to 1M of these roles coming online. I buy it.
Profound's push: The "Marketing Engineer"
Profound (one of the hottest companies on my AI GTM 100) is pushing a specific version of the role. Their CEO posted a well-executed manifesto: "Today we introduce a new role to the marketing org: The Marketing Engineer." Social media loved it. 1,532 likes, 17x his baseline.
Two days later, Marvin Chow, VP of Consumer & AI Marketing at Google, posted "marketing engineers are the hire of 2026. period." Quite an endorsement.
I agree with the insight. I'm just not latching onto the specific title yet.
My approach as a new CMO: Maximize the edges first. Centralize on GTM.
Maximize the edges. I want AI adoption on the edges to be on fire. Every individual cranking in single player mode. That's the condition for a centralized Agent operator / AI builder to actually work. Otherwise that builder is just pushing the rock up the hill alone. Emily Kramer calls this kind of person a "Gen Marketer." A marketing generalist expert at using AI across all of marketing. Same idea.
For centralization, "GTM" is stickier than "Marketing." Clay's GTM Engineering movement is implicitly silo-breaking. The role is scoped across sales, marketing, and CS from day one. I've argued it should reach further into the full marketing lifecycle. This is the desirable direction. If marketing hires a "Marketing Engineer," sales hires a "SalesOps Engineer," CS hires a "CSOps Engineer," and you end up with agent stacks repeating the flaws of siloed SaaS stacks. That's the world we've spent 10 years fighting with. We're done clicking around.
Centralized context & tools, then roles. Being a six-person team collapses the debate for us. Everyone builds with AI on the edges. Together we created a set of centralized tools and resources -- gtm-context knowledge base, skills repo, weekly live build sessions. We're going to keep building that core. It's a set of projects today that multiple people improve and expand. In the future, I see the agent operator role forming and I'll probably lean toward "GTM Ops" in title.
What I'm watching
Two things in parallel. Centralized AI builder & agent operator teams. Plus high standards for AI fluency and adoption in every role.
I want to see examples and role models on both sides.
This will be a competitive advantage for orgs that get it right quickly. AI seems to bring compounding advantages over teams clicking around SaaS tools all day. This is playing out in engineering already. The AI-Native teams can run circles around their competitors and the gap seems to widen with time.
It will take many shapes in titles and GTM org charts. In my team right now, it's six AI-Native generalists building on the edges with a first set of centralized tools and resources. We're going to learn fast and keep watching Ramp, Zapier, and Intercom.
Curious to watch this one evolve.
What does the AI GTM team look like in your company?