Stage 3: Operator

“I think we use AI every day. It’s baked into our tech stack.”

Overview:

This is the first stage where AI adoption has led to visible team activity.  AI is showing up inside the tools your teams already use, whether it's email scoring in Outreach, smart fields in HubSpot, or recommendations in your ad platform. Leaders believe they’ve “adopted AI” simply because vendors have shipped it into the UI.

But actual usage is shallow. Adoption is inconsistent. And most teams are still running the same GTM plays they always have—just with new buttons to click. There’s no process change, no measurable impact, and no strategic planning around what AI could unlock.

It feels like progress. But under the surface, very little has changed

Cultural Signals:

• Leaders claim to use AI, but can't articulate how it’s driving outcomes
• Teams are using AI as a feature, not a workflow
• Adoption is reactive to vendor launches or roadmap updates

Risks:

• Leadership overestimates how far along the org really is
• Defaulting to what vendors provide, rather than what teams actually need
• No measurement of what’s working or why mean early wins fail to compound

How to move forward:

• Begin tracking specific KPIs tied to AI-assisted outcomes (e.g., lead response time, content production velocity)
• Audit where AI exists today (feature ≠ adoption) and gather real usage data to understand friction points and low trust or utility
• Identify 1–2 areas where AI can restructure GTM workflows, not just enhance existing ones (e.g., signal-driven account prioritization, predictive reporting)
• Begin to think of AI as a system design problem, not a checkbox feature