Will AI Kill SaaS? Not Entirely—But It's Reshaping Who Wins and Loses.
Short answer: AI will retire some horizontal tools in the hands of capable, mid-to-large tech-first companies. It will also make great vertical SaaS more valuable than ever. Everyone else will mostly keep buying software.
When Voi CEO Fredrik Hjelm recently posted "RIP Tableau" on LinkedIn, it wasn't just another hot take—it was a preview of SaaS's future. His company had ripped out their expensive Tableau deployment, saving at least €500,000 annually while achieving 100x faster insights through a custom AI-powered solution built around LLMs in Slack and Sheets.
The question isn't whether AI will impact SaaS—it's which companies will thrive and which will become obsolete in this new landscape. At Kirra Capital, we're firm believers that AI and advancing technologies will accelerate value creation in SaaS, but only for companies built for the right customer size, with vertical focus and relentless innovation. The market won't die—it will bifurcate.
The Tableau Takedown: A Blueprint for SaaS Disruption
Voi's transformation illustrates the perfect storm for SaaS displacement. Like many legacy tools, Tableau had become "expensive, clunky and slow." Ad hoc requests created analyst backlogs, local teams across 100+ cities waited weeks for insights, and costs spiraled while productivity plummeted.
But Voi's success wasn't just about swapping tools—it required three critical foundations:
Years of data governance: Every metric had clear ownership, quality checks, and definitions, enabling reliable LLM-to-SQL translation
Clear requirements focus: They defined what they actually needed (single source of truth, real-time streaming, self-serve access) rather than paying for bloated feature sets
LLMs as the intelligent bridge: Custom AI that translates natural language into SQL queries and returns insights in seconds
The results: millions saved, universal self-serve access, and decision-making that jumped from weeks to seconds. Klarna has taken a similar path with parts of its stack, replacing expensive vendor tools with internal AI-powered systems.
A Simple Decision Framework: Where AI Replaces SaaS
If you're evaluating "build vs. buy" with AI, the math becomes clear across five key dimensions:
Spend: Are you paying enough in licenses and people time to justify the build? Six figures annually is a useful filter—Voi's €500k+ made the ROI obvious.
Scope: Narrow, well-defined problems favor building. Broad, mission-critical workflows usually stay bought.
Data: Do you have governed data with owners, definitions, and quality checks? Without this foundation, AI agents fail. Voi's success started here.
Capability: Can you productionize prompts, enforce permissions, and maintain UI and integrations? This isn't a weekend project.
Risk: What happens if the agent is wrong or down? Who owns accountability?
Companies like Voi—mid-to-large, tech-forward, with strong data foundations—check all these boxes for horizontal tools.
The Great SaaS Divide: Customer Size Determines Fate
The Goldilocks Zone of Disruption
Enterprise giants like KPMG or Coca-Cola aren't building custom solutions anytime soon. These organizations need vendor accountability, 24/7 support, and compliance guarantees. They'll adopt AI through controlled vendor roadmaps, not greenfield rebuilds.
Small businesses—gym owners, roofers, sports clubs—remain safely in SaaS territory. They're still transitioning from paper processes and lack the time, talent, or budget to build and maintain bespoke AI stacks. Buying software remains cheaper, faster, and safer.
But mid-to-large tech-first companies represent the disruption sweet spot. Organizations like Voi have engineering talent, meaningful budget pressure, and organizational agility to build solutions that perfectly match their needs. This segment increasingly views generic horizontal SaaS as an unnecessary middleman.
The Fault Line: Horizontal vs. Vertical SaaS
Horizontal Tools: Easy Targets
Standalone horizontal products like Slack, Calendly, DocuSign, or basic scheduling tools have narrow surface areas that AI can readily replicate. Google now ships Calendar "Appointment Schedule," pressuring Calendly-style tools. In capable organizations, LLM agents can draft availability emails, read responses, and book directly—closing the usability gap further.
The pattern is clear: when horizontal tools become bottlenecks, AI's ability to automate workflows makes replacement feasible. These platforms solve isolated problems without deep integration into core business processes.
Vertical SaaS: Compounding Value and Network Effects
Vertical SaaS tells a dramatically different story. Consider Toast's restaurant management platform—it runs point-of-sale, payments, online ordering, payroll, marketing, and more across ~148,000 restaurant locations. That breadth creates real switching costs and rich product surfaces for AI enhancement.
Toast's "Sous Chef" AI assistant generates sales insights, automates operations, and leverages aggregated restaurant data to benchmark performance. This isn't just software—it's a competitive moat built on specialized data and domain expertise that individual restaurants could never replicate.
Prism.fm exemplifies vertical network effects in entertainment venues. By focusing exclusively on live events, they offer unique analytics like talent booking ROI predictions based on cross-platform data. The more customers use it, the better the benchmarking becomes—something an individual venue cannot build alone.
Vertical data creates unbreachable moats. When platforms focus on single industries, they accumulate datasets that benefit every customer while becoming impossible to replicate internally.
The Innovation Arms Race: Talent and Roadmap Advantages
Even when AI levels the playing field, focused software teams ship faster and safer than internal business teams. At Kirra Capital, we believe the winners will be SaaS companies that invest heavily in engineering talent and modern AI pipelines—they'll out-iterate DIY efforts consistently.
Leading vertical players are already building agent features, automating workflows, and linking models to trusted metrics. Toast continues rolling out AI-assisted tools alongside its core OS, leveraging deep restaurant domain context to apply AI across multiple jobs-to-be-done.
Under-invested platforms are the exception. Products milked for cash and starved of R&D become vulnerable. Customers will migrate to ambitious competitors or justify building in-house where scope is tight and savings are obvious.
Kirra Capital's Investment Thesis: Where AI Accelerates SaaS Value
At Kirra Capital, we see AI as a massive accelerant for the right SaaS companies—not a threat. Our investment focus targets companies that will become more valuable, not less, in an AI-first world:
Customer Size Sweet Spots: We back companies serving small businesses (who lack DIY capability) and true enterprises (who value vendor support), while avoiding the vulnerable middle market where custom builds make sense.
Vertical Depth Over Horizontal Breadth: We prioritize platforms with multiple layers of value, deep integrations, and industry-specific data that create network effects. These companies use AI to expand moats, not just add features.
Relentless Innovation: We invest in teams with aggressive AI roadmaps that ship continuous improvements. Companies that deploy emerging technologies so effectively that customers couldn't keep pace even if they tried.
Data Network Effects: The most compelling opportunities combine vertical focus with unique datasets that improve as customer bases grow—making individual replacement efforts futile.
What This Means for SaaS Founders and Buyers
For Horizontal SaaS: Expect consolidation and pricing pressure. Build strong moats through network effects or deep integrations—or expect replacement by LLM agents or comparable alternatives.
For Vertical Platforms: Lean into end-to-end workflows, payments, and deep integrations. Use AI to reduce operational toil, surface unique insights, and create data network effects that customers cannot reproduce alone.
For Product Teams: Keep shipping. The winners will be teams that apply AI to real operator pain points and release improvements continuously, not one-off demos.
The Bottom Line: Bifurcation, Not Destruction
AI will replace expensive, single-purpose horizontal tools in companies with talent and data foundations to build alternatives. But AI will also make the best vertical platforms more valuable by enabling breadth, integrations, and shared data advantages that individual customers cannot match.
The SaaS market won't die—it will bifurcate. The "DIY with AI" crowd will build where it makes financial and technical sense. Everyone else will buy from vendors who continuously earn the right to exist through innovation and value creation.
At Kirra Capital, we're betting on the companies that use AI not as a replacement for SaaS, but as a force multiplier that makes great vertical platforms indispensable. The future belongs to those who can innovate faster than their customers can replicate.
The question isn't whether AI will kill SaaS—it's whether your SaaS company will use AI to become irreplaceable.