Investors have been pouring billions into AI companies over the past few years, as the technology continues to hold sway in the Valley and thus the world. But not all AI companies are grabbing investor attention.
Indeed, even as it seems every company these days is rebranding to include “AI” in its name, some startup ideas are just no longer in favor with investors. TechCrunch spoke with VCs to learn what investors aren’t looking for in AI software-as-a-service startups anymore.
Popular SaaS categories for investors now include startups building AI-native infrastructure, vertical SaaS with proprietary data, systems of action (those helping users complete tasks), and platforms deeply embedded in mission-critical workflows, according to Aaron Holiday, a managing partner at 645 Ventures.
But he also gave a list of companies that are considered quite boring to investors these days: Startups building thin workflow layers, generic horizontal tools, light product management, and surface-level analytics — basically, anything an AI agent can now do.
Abdul Abdirahman, an investor at the firm F Prime, added that generic vertical software “without proprietary data moats” is no longer popular, and Igor Ryabenky, a founder and managing partner at AltaIR Capital, went deeper on that point. He said investors aren’t interested in anything, really, that doesn’t have much product depth.
“If your differentiation lives mostly in UI [user interface] and automation, that’s no longer enough,” he said. “The barrier to entry has dropped, which makes building a real moat much harder.”
New companies entering the market now need to build around “real workflow ownership and a clear understanding of the problem from day one,” he said. “Massive codebases are no longer an advantage. What matters more is speed, focus, and the ability to adapt quickly. Pricing also needs to be flexible: rigid per-seat models will be harder to defend, while consumption-based models make more sense in this environment.”
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