The larger your GTM org, the harder it is to adopt AI.
When every role and process is part of a complex, enterprise motion, you can’t just throw technology at the problem.
You need to lead the transformation.
A clear vision is two things: understanding how an AI-first GTM motion works and a plan to bring your team through the change from how they’re working today. If you have a clear destination, an understanding of where the team is starting, and a plan to cross the distance, you’re ready to lead your AI transformation.
What the most advanced AI-native teams actually do and the patterns underneath. The only way to stay current with AI is to copy from the best and learn by doing.
Field noteA vision only counts when it connects to the org you run today. This is the route between the two - plotted in phases, each concrete enough to start on.
Field noteThe teams winning with AI in GTM focus on projects that address bottlenecks in the revenue model. AI transformation isn’t a separate workstream from hitting your number - it’s the capability your team develops quarter over quarter to unlock accelerating growth. The model below is illustrative - it runs on six assumptions, not necessarily these six, but six your plan already makes. Pick the lever your quarter is stuck on.
Your positioning, ICP, and prioritized plays go into one canonical context, and the campaigns that draw on it run themselves: research, personalized builds across web, email, and paid, and the follow-up - generated many-at-once, with a human only on the decisions. Build that loop once and every program after runs at a fraction of the cost, so the same budget buys more qualified pipeline.
Field noteAttribution is never clean and the dollars here are illustrative. What’s real is that AI-native firms build for outcomes this size.
Short of assigning real targets, AI will always be stuck in pilot mode.
Set the targets your team would sign, and build a culture and discipline of holding AI initiatives accountable to revenue outcomes. When the impact compounds quarter over quarter, AI stops being an initiative - it’s how your team runs.
The systems put your go-to-market on AI: one shared context, builders on your team, functional AI running the work between the calls. The culture holds every initiative to a revenue number, quarter over quarter, until AI is simply how the team runs.
We install both from inside your team. A four-to-six-week discovery maps where AI moves your numbers. Focused quarters build it. An embedded year compounds it. And every project is designed to roll off - your people own the engine, and the work keeps running after we leave.
Fresh Context leads AI transformation for enterprise go-to-market. We built this operating model inside a real revenue organization before we ever sold it, and our own firm runs on it today - this page included.
Sam Gong, Charles Baakel, and Kaitlin Davis. We’ve run this operating model in production, at enterprise scale, carrying the number. Meet the team
We share our experiences and the findings behind them at the intersection of AI, modern go-to-market, and enterprise transformation.
