Why GTM Teams Fail at AI Enablement
Most GTM teams don’t fail at AI because of the tech. They fail because there’s no clarity, coaching, or standards. Tools alone create chaos. Winning teams are building systems, not hype.
There is a hard truth sitting beneath all the AI hype washing across the tech world right now: most organizations are failing at AI enablement, and they don’t even realize it. The failure isn’t the technology. It isn’t the tools. It isn’t even employee resistance. It’s leadership, design, and operating discipline.
Executives are buying AI platforms at a historic rate. According to Gartner,
spending on AI software is projected to exceed $300 billion by 2027.
The adoption curve is steep, loud, and urgent.
Yet a separate Gartner study shows that over 70 percent of enterprise AI initiatives fail because organizations underestimate the cultural, operational, and workflow transformation required.
It is the same pattern we’ve seen in every major technical disruption over the past 20 years, but AI has accelerated the consequences.
The story inside most revenue organizations looks like this: leadership rolls out an AI mandate with vague directives like “use AI more” or “let AI help you.” Teams experiment with little guidance. Managers are left out of the equation entirely. No one creates standards, no one defines quality, and no one builds the behavioral infrastructure around the technology. When results are inconsistent (or embarrassing), leaders quietly decide AI isn’t ready yet.
It isn’t AI that isn’t ready. It’s the organization.
This article examines why GTM teams repeatedly fail at AI enablement, the operational gaps that create chaos, the ethical and practical risks that emerge from poor implementation, and the blueprint for building an effective AI GTM strategy that actually drives outcomes. It closes with a real story from my own career, where I rebuilt an AI initiative from the ground up after leadership unintentionally created confusion, misalignment, and operational risk.
The Pattern Is Clear: Everyone Buys Tools, Almost No One Builds Enablement
The average revenue team today is operating in two parallel realities.
In one reality, executives believe AI is a multiplier. They believe the technology will accelerate sales cycles, improve content quality, reduce manual work, and provide “productivity gains” the moment it’s switched on. In the other reality, frontline teams log into poorly trained internal models, struggle with inaccurate outputs, and receive no coaching or standards for how to use AI in their daily workflow.
This disconnect is not theoretical. It shows up in performance.
A 2024 McKinsey study found that while 65 percent of companies adopted at least one form of AI, only 7 percent had embedded AI into their core workflows in a way that produced measurable business-wide impact.
That gap speaks to the central failure of GTM organizations today: buying AI tools is easy, but building the human system around them is hard.
Sales, marketing, and technical teams cannot improve simply because software exists. AI adoption requires behavior change, and behavior change requires enablement. Without purpose, without structure, and without coaching, AI tools become expensive shortcuts to nowhere.
