The rise of verticals
For years, the default playbook in tech was to go wide. Build a platform, serve everyone, scale horizontally. It worked brilliantly for a generation of companies. But something has shifted. In the age of AI, the smartest builders are going narrow, and they're winning.
Horizontal scaling hit a wall
Horizontal scaling, building products that serve broad, cross-industry use cases, is genuinely hard. Whether you're talking about cloud infrastructure or software niches, the challenge is the same: the wider you go, the thinner your differentiation becomes. In SaaS, horizontal products like general-purpose CRMs, project management tools, and writing assistants face a brutal competitive landscape. You're competing against entrenched incumbents (Salesforce, Asana, Notion) and a wave of AI-native disruptors. Many horizontal AI startups have been labeled "thin wrappers," products that sit on top of foundation models without enough unique value to survive long-term. Jasper AI, once valued at $1.5 billion, had to cut its valuation as the gap between its output and what ChatGPT could do out of the box shrank to nearly nothing. The core issue is defensibility. When your product is a layer on top of a general-purpose model, what stops the model provider from eating your lunch?
Even the giants are going vertical
Here's the telling part: even OpenAI and Anthropic, the companies building the most powerful horizontal AI models, are investing heavily in vertical applications. OpenAI has pushed aggressively into enterprise with tailored solutions for specific workflows. Anthropic's Claude has carved out deep positions in coding, legal analysis, and financial modeling. These aren't generic chatbot plays. They're deliberate moves into verticals where domain-specific accuracy and workflow integration matter more than raw model capability. When the companies with the best horizontal technology choose to go vertical, it tells you something important about where the value accrues.
Why verticals win in the AI era
The shift toward vertical AI isn't just a trend. It's a structural change driven by several reinforcing factors. Domain context is the real moat. In regulated industries like healthcare, finance, and legal, generic AI falls short. You need compliance controls, specialized data pipelines, and deep understanding of professional workflows. A vertical AI company that understands how a radiologist reads an image or how a paralegal reviews a contract has an advantage that no foundation model can replicate overnight. The "last mile" is long and messy. Better Tomorrow Ventures describes a useful framework: the longer the "last mile" between a general model's output and a production-ready workflow, the more defensible a vertical company becomes. Marketing copy generation? Short last mile, easily absorbed by foundation models. Contract analysis with regulatory compliance? Long last mile, room to build a real business. Vertical AI expands the market. Traditional SaaS was priced per seat, capping revenue at a percentage of employee salary. AI changes this equation entirely. When software doesn't just optimize a workflow but actually performs the work, pricing shifts to value delivered. A vertical AI agent that handles insurance claims processing isn't worth $20/seat/month. It's worth a fraction of every claim it processes. Scale Venture Partners argues this market-expanding nature of AI is the most profound shift, turning "small" verticals into massive opportunities. Less competition, more greenfield. Many vertical markets still run on manual processes or legacy on-premise software. Where horizontal SaaS is now on its third or fourth generation of competition, many verticals have barely seen their first wave of modern software. The opportunity to leapfrog straight to AI-native solutions is enormous.
The numbers tell the story
The data backs up the thesis. Vertical AI agents as a category are projected to grow from roughly $4.2 billion in 2024 to $52 billion by 2030, a compound annual growth rate of 52%. Enterprise buyers are increasingly prioritizing "hard ROI" over soft productivity gains, and verticalized solutions, with their built-in domain context and compliance controls, deliver faster and more predictable returns than horizontal platforms. Investor behavior has followed. As Scale Venture Partners noted, "I never would have imagined every venture fund having a vertical strategy even three years ago, but here we are." The firm argues we're only at the beginning of a significant secular trend.
What this means for builders
If you're starting something new, the implications are clear. Pick a specific audience and go deep. The age of building "AI for everyone" is largely over unless you have billions in funding and frontier model capabilities. For everyone else, the winning move is to pick a specific industry, learn its pain points intimately, and build something that a general-purpose tool simply cannot replicate. Combine SaaS infrastructure with AI intelligence. The most defensible companies will blend deterministic workflows (traditional SaaS) with probabilistic intelligence (AI). Start from either side, but aim for both. A vertical SaaS company that layers in AI, or a vertical AI company that builds reliable workflow infrastructure, creates compounding advantages. Think about value pricing, not seat pricing. If your AI agent actually does the work rather than just helping a human do it faster, your pricing model should reflect the value delivered. This is how "small" verticals become large businesses. Move fast while the window is open. Vertical markets are still underserved, but that won't last. The companies that build deep domain expertise and customer relationships now will be very hard to displace later.
The bottom line
The era of horizontal dominance in tech isn't over, but the growth edge has shifted. In a world where foundation models are increasingly commoditized and general-purpose AI tools converge toward similar capabilities, the differentiation moves upstream to domain expertise, workflow integration, and industry-specific data. The builders who recognized this early, who chose depth over breadth, are the ones quietly building the most valuable companies of the next decade. The rise of verticals isn't a contrarian bet anymore. It's the new consensus, and it's still just getting started.
References
- Scale Venture Partners, "Which AI verticals will have the next unicorn?" scalevp.com/blog/which-ai-verticals-will-have-the-next-unicorn
- Scale Venture Partners, "The next decade of software is verticals and AI" scalevp.com/blog/the-future-of-ai-is-vertical
- Sapphire Ventures, "Vertical(ai) is the New Horizontal" sapphireventures.com/blog/vertical-ai-is-the-new-horizontal
- Better Tomorrow Ventures, "Will Vertical AI Survive?" better-tomorrow-ventures.ghost.io/will-vertical-ai-survive
- Futurum Group, "Should SaaS Vendors Prioritize Verticalized or Horizontal AI?" futurumgroup.com
- Startupik, "Niche AI Startups: 5 Arenas Beyond the Hype Set to Explode in 2026" startupik.com/niche-ai-startups-exploding
- Andrew Oved, "Vertical SaaS vs. Vertical AI: a distinction with a key difference" linkedin.com
- Microsoft Source, "What's next in AI: 7 trends to watch in 2026" news.microsoft.com
- ARK Invest, "AI Progress Is Accelerating" ark-invest.com/newsletters/issue-497