In recent years, investors have invested billions in AI firms as the technology remains influential in the Valley and the global landscape. Yet, not all AI companies are captivating investor interest.

In fact, as it appears that numerous companies are rebranding to incorporate “AI” into their titles, several startup concepts have fallen out of favor with backers. TechCrunch consulted VCs to determine what traits investors no longer seek in AI software-as-a-service startups.

Currently favored SaaS sectors for investors include startups developing AI-native infrastructure, vertical SaaS with exclusive data, systems of action (aiding users in completing tasks), and platforms that are deeply integrated into essential workflows, according to Aaron Holiday, managing partner at 645 Ventures. 

He also outlined a list of companies that are currently deemed rather uninspiring to investors: startups creating thin workflow layers, generic horizontal solutions, light product management tools, and superficial analytics — effectively, anything that an AI agent can now efficiently perform. 

Abdul Abdirahman, an investor at F Prime, noted that generic vertical software “lacking proprietary data advantages” is out of favor, and Igor Ryabenky, founder and managing partner at AltaIR Capital, elaborated on this sentiment. He stated that investors are wary of anything that lacks substantial product depth. 

“If your uniqueness mainly resides in UI [user interface] and automation, that’s simply not sufficient anymore,” he articulated. “The entry barrier has lowered, complicating the establishment of a genuine moat.” 

New entrants to the market must focus on “real workflow ownership and a clear comprehension of the problem from the outset,” he specified. “Extensive codebases are no longer a bonus. What weighs more is agility, concentration, and the capacity to adapt swiftly. Pricing must also offer flexibility: rigid per-seat arrangements will be more challenging to justify, whereas consumption-based pricing aligns better in this setting.” 

Jake Saper, a general partner at Emergence Capital, shared insights on ownership as well. To him, the distinctions between Cursor and Claude Code serve as the “canary in the coal mine.” 

“One governs the developer’s workflow, while the other merely performs the task,” Saper remarked. “Developers are increasingly opting for task execution over process management.” 

He noted that any product addressing “workflow stickiness” — which aims to engage numerous human users to repeatedly utilize the product — may face challenges as agents take over the workflow.

“Prior to Claude, persuading humans to use your software was a significant advantage, but if agents are carrying out the tasks, who remains concerned about human workflows?” he told TechCrunch.

He also believes that integrations are losing their allure, particularly as Anthropic’s model context protocol (MCP) simplifies the connection of AI models to external data and systems. This allows users to bypass the need to download numerous integrations or develop customized ones; they can simply employ the MCP. 

“Being the connector used to be an advantage,” Saper stated. “Shortly, it will become a utility.”

Additionally, the “workflow automation and task management tools that facilitate the coordination of human tasks are diminishing in necessity if, over time, agents solely carry out the tasks,” Abdirahman observed, citing examples, primarily public SaaS companies experiencing stock declines as new AI-native startups emerge with superior and more efficient technologies. 

Ryabenky mentioned that the SaaS companies struggling to secure funding at present are those easily replicable.

“Generic productivity applications, project management solutions, basic CRM replicas, and superficial AI integrations atop existing APIs belong to this category,” he remarked. “If the product consists mostly of an interface layer without substantial integration, proprietary data, or embedded process expertise, robust AI-native teams can replicate it rapidly. This is what prompts investors to be cautious.”

Overall, what continues to appeal about SaaS is depth and expertise, with tools integrated into pivotal workflows. He indicated that companies should currently focus on embedding AI thoroughly into their offerings and update their marketing accordingly, Ryabenky reiterated.

“Investors are redirecting capital toward businesses that control workflows, data, and domain expertise,”  Ryabenky concluded. “And away from offerings that can be duplicated with little effort.”