Vertical AI Founder Warns That Even the Best Products Can't Overcome a Broken GTM
Luke Sophinos stated that even with the best vertical AI products on Earth, one cannot overcome a broken go-to-market (GTM) mechanism.
AI cannot solve issues such as long sales cycles, poor industry segmentation, and bureaucratic procurement hell. While Silicon Valley VCs are excited about vertical AI, partly justifiably (especially products that can eliminate W-2 and cut into labor costs), the "tourist" VCs overlook the customer acquisition pain points in most industries. The GTM in the education sector is very poor, and even the best products take ten years to scale; the government sector is even harder, with successful GovTech often resulting from mergers or enduring for over 15 years. He has not seen EdTech or GovTech startups reach $10 million ARR within three years. The core lesson is: unless one is highly comfortable with the GTM and customer acquisition timelines in a vertical field, do not go all-in on vertical AI. Entrepreneurs need to invest in GTM with the same rigor and innovation as they do in their products.
This serves as a public reminder from vertical AI practitioners that the focus on the product has led to neglecting distribution, shifting attention to the realities of customer acquisition and time costs. Founders who delve into GTM benefit from a pragmatic perspective, while purely product-driven investments are pressured by discrepancies in scaling expectations.
Source: Public Information
ABAB AI Insight
In the vertical AI craze, capital is often attracted by the narrative of "replacing labor costs," but underestimates the length and complexity of traditional industry procurement decision chains. Education and government, as typical high-barrier verticals, have historical data proving that rapid scaling is extremely rare.
On the capital path, successful cases often rely on long-term relationship accumulation or mergers and integrations, rather than just product advantages. The motivation is to remind founders and investors to weigh GTM and product equally during the due diligence phase.
Similar to the lessons learned during the early SaaS transition from horizontal to vertical, we are currently in a phase where "AI amplifies product potential but does not change the essence of distribution."
Essentially, this involves a transfer of pricing power: value shifts from pure technological leadership to a complete closed loop of "technology + feasible distribution," with the mechanism directly accounting for customer acquisition friction in the true ROI of vertical AI.
ABAB News · Law of Cognition
No matter how strong the product, it cannot overcome a broken customer acquisition path.
The sales cycle in vertical industries is often longer than technological iterations.
Truly scalable vertical AI must first solve the distribution problem.