Anish Acharya: Is SaaS Dead in a World of AI?

Software companies are dying, but not for the reasons you think. While everyone debates whether AI will replace human workers, Anish Acharya from Andreessen Horowitz argues the real disruption is happening to the software itself. The traditional SaaS playbook , sticky products with high switching costs , is about to become obsolete as AI agents make migration between tools trivial.

Acharya's core thesis challenges Silicon Valley's current AI obsession. Most investors are betting on AI companies that automate execution tasks: the coding agents, the data entry bots, the workflow automators. But Acharya believes these represent the low-value end of the market. "I think a lot of the thinking work is going to be done in products like Figma," he explains, pointing to the design platform as an example of software that survives because it enhances human creativity rather than replacing human labor.

This distinction between execution-focused and thinking-focused products cuts through the noise around AI's impact on SaaS. Execution tools are commoditizing rapidly , why pay for expensive workflow software when an AI agent can just build what you need? But thinking tools, the platforms where humans collaborate and create, become more valuable as AI handles the grunt work. Figma didn't set out to be an AI-era winner, but its collaborative design environment positions it perfectly for a world where the bottleneck shifts from implementation to ideation.

The death of switching costs represents the second major disruption Acharya identifies. Traditional SaaS companies built moats through integration complexity and data lock-in. Moving from Salesforce to HubSpot meant months of painful migration work. But when AI agents can seamlessly translate between platforms and rebuild integrations overnight, those moats disappear. The competitive question becomes whether "the incumbent acquires innovation before the startup acquires distribution," as Acharya puts it, borrowing from venture capitalist Alex Rampell's framework.

This dynamic creates a new form of competitive risk for both sides. Established SaaS giants like Salesforce and HubSpot have millions of customers but face the innovator's dilemma with AI features. Meanwhile, AI-native startups have superior technology but must crack distribution before incumbents can copy their innovations. Acharya frames this as one of three fundamental risks investors must choose: competitive risk, pricing risk, or team risk. The competitive risk around incumbent versus startup battles has become the defining question for SaaS investing.

But Acharya's most counterintuitive insight concerns customer support functions. He questions why companies maintain separate teams for sales, support, operations, and collections when AI voice agents could collapse these distinctions. "Who is the person that's really good at customer support, empathetic, they're a listener, they really understand the product well. Who is really good at sales? They're more of a yapper," Acharya observes. AI agents that can switch between empathetic listening and persuasive selling within a single conversation could remake entire customer-facing organizations.

The implications extend beyond software into how we think about sustainable competitive advantages. Acharya points to Credit Karma as an example of durability that transcends technological shifts. Despite being fundamentally a simple credit score checker, Credit Karma attracts 100 million Americans who log in four times monthly. "The credit score is actually this sort of mirror that people like to look in and see how they're doing objectively as an adult," Acharya explains. The platform works because it taps into psychological needs that persist regardless of the underlying technology.

This psychological dimension reveals why some products survive technological disruption while others don't. Tools that satisfy deep human needs for feedback, status, or creative expression develop staying power. Tools that exist purely to execute tasks become vulnerable to AI replacement. The lesson for founders and investors is to build around human motivations that transcend specific technological implementations.

For founders, Acharya's analysis suggests focusing on the intersection of AI capabilities and human psychology rather than pure automation plays. The winning products will be those that make humans more creative, more insightful, or more emotionally satisfied rather than simply more efficient. As coding agents commoditize execution and AI eliminates switching costs, the SaaS companies that survive will be those that understand what makes people fundamentally tick.

Watch for this framework to reshape venture investing over the next two years. The firms that recognize the shift from execution to thinking tools earliest will capture the biggest winners in the post-SaaS world.