Read my latest article in The AI Insider – Read the story here
Most vertical AI founders think their biggest GTM problem is volume: more sequences, more channels, more signals, more “air cover.” In 2026, that feels intuitively right. Clay can surface thousands of hyper-specific accounts in minutes, Persana can assemble multi-threaded sequences at scale, Gong can dissect every call, and 6sense can tell you who’s warming up before you even knock.
The tools are extraordinary. The dashboards look great. Pipeline “activity” charts are moving in the right direction. And yet, almost no one is getting to $10M—let alone to the $25M threshold that separates serious enterprise players from “interesting” startups.
In this piece, Mark M.J. Scott argues that the problem isn’t the AI GTM stack; it’s what founders are putting into it. He calls it the “megaphone paradox”: when you point industrial-strength GTM automation at a weak or unfinished narrative, you don’t get better results—you just burn more runway, faster, while teaching an entire market to ignore you. The more you automate, the more invisible you become.
The article dissects three specific GTM failures that are quietly killing vertical AI startups right now. They’re not the usual suspects like “lack of product–market fit” or “hiring the wrong VP Sales.” They’re deeper structural gaps: markets that haven’t been taught how to think about a new problem, buying committees that lack language to evaluate risk, and credibility signals that never materialize because no one has intentionally designed them. In that context, AI outreach becomes a fog machine—lots of motion, no traction.
Scott then re-frames market shaping as the missing foundation for AI-native go-to-market. Instead of evangelism theater or random thought leadership, he defines it as the deliberate work of engineering how a vertical understands its problems, evaluation criteria, and proof.
That means constructing the POV that explains what changed, the positioning that holds up under CFO and CIO scrutiny, the proof points that travel inside large organizations, and the third-party reinforcement that makes a risky new vendor feel safe.
Once those pieces exist, the entire role of AI GTM automation flips. The same tools that previously amplified noise become leverage on a carefully architected narrative. Outreach suddenly lands because it references proof and language the market has already been primed to recognize. Content stops attracting low-intent “tourists” and starts pulling in stakeholders with budget, urgency, and internal influence. Salespeople stop doing remedial category education and start closing deals.
If you’re a founder staring at beautiful GTM dashboards but stubbornly flat new ARR, this article is a diagnostic. It will help you see whether you’re actually building a market, or just funding activity at scale. More importantly, it outlines what, exactly, needs to be true before your AI GTM stack can behave like the force multiplier you bought it for—instead of a very expensive way to get ignored faster.
Read the story here
Startup GTM for AI & Deep Tech | Series A to $25M | Northern Pixels 
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