While general-purpose AI models like ChatGPT generate tremendous excitement and investment, another area of artificial intelligence is quietly demonstrating extraordinary business potential. As foundation models secure headlines and massive funding rounds, specialized AI companies are building sustainable businesses by solving specific industry challenges.
Unlike Horizontal AI (most common), which offers broad applications across industries, Vertical AI integrates deep domain expertise with advanced machine learning to solve industry-specific challenges. This specialization encourages greater defensibility, faster adoption, and higher value capture, particularly in sectors like healthcare, financial services, logistics, and real estate.
"We're witnessing the industrialization of AI," says Mike Schatzman, CEO & Managing Partner, Venture Forward Capital. "The companies winning aren't building general tools—they're solving concrete problems in healthcare, finance, and logistics with purpose-built AI that understands the nuances of these sectors."
Horizontal AI attempts to do many things adequately; vertical AI does one thing exceptionally well. And the market is responding.
The vertical AI market, valued at $10.2 billion in 2024, is expected to grow at 21.6% annually through 20341. But raw market size only hints at the opportunity.
What makes these companies particularly interesting to investors is their capital efficiency. While foundation model companies regularly raise nine-figure rounds just to cover training costs, vertical AI startups typically raise modest rounds of $2-8 million at pre-seed and seed stages, then quickly convert this capital into paying customers and revenue growth.
According to Bessemer Venture Partners, early-stage companies in this space are experiencing rapid funding and revenue growth.2 The increasing need for regulatory compliance and risk mitigation is further driving demand, as businesses pursue AI solutions customized to industry-specific standards rather than broad, one-size-fits-all models. Leading firms such as, NEA, and Sequoia Capital have actively backed startups in this space, attracted by their market potential and differentiated value propositions.3
The operational metrics are equally impressive. Leading vertical AI companies demonstrate:
These aren't theoretical projections—they're results from companies already in market. Industry analysts predict at least five vertical AI companies will reach $100M ARR within the next 2-3 years, with the first vertical AI IPO likely in the same timeframe.
Every founder needs to decide: are they enabling existing providers or replacing them?
That seemingly basic choice determines everything from customer acquisition costs to exit multiples. The six resulting business models offer investors dramatically different risk-reward profiles.
The table below maps the six dominant business models that have emerged in this space:
Jason Shuman, a General Partner at Primary, emphasizes the strategic importance of understanding these distinctions: "Understanding whether to enable service providers or to be a service provider is essential for founders navigating the Vertical AI space. The chosen model significantly influences a company’s growth trajectory and its potential impact on the industry.”4
Across sectors, Vertical AI is addressing pain points that general AI models simply cannot solve:
Beyond its technical and operational advantages, Vertical AI presents unique investment opportunity with several key benefits:
Unlike general AI models that can be applied across industries, Vertical AI is built for specific sectors. This specialization makes it significantly harder for new entrants to compete.
A critical advantage comes from proprietary data–often difficult to access or replicate. Many startups secure exclusive partnerships or develop unique datasets that create defensible competitive moats. Without this data, competitors struggle to deliver comparable accuracy and performance.
“In AI, access to proprietary data isn't just an advantage—it's a barrier to competition. Vertical AI companies that secure exclusive datasets and integrate deeply into industry workflows build moats that are nearly impossible to cross.”5
- Bessemer Venture Partners
Once embedded in operations, these solutions become difficult to replace. Businesses are hesitant to switch providers due to the challenges of retraining models, helping early entrants retain customers and strengthen their market position.
Vertical AI is designed to tackle real-world problems from day one. This focused approach accelerates adoption as businesses quickly experience gains in efficiency, accuracy, and cost savings. Its seamless integration into existing workflows minimizes disruption while maximizing impact. Whether automating manual tasks, improving decision-making, or optimizing resource allocation, these industry-specific AI solutions deliver measurable returns in a shorter timeframe.6
The TAM within these sectors is immense:7
These industries, along with others rapidly adopting specialized AI solutions, represent multi-trillion-dollar markets where Vertical AI can enhance efficiency at unprecedented scale.
Vertical AI thrives when integrated with other cutting-edge technologies like IoT, blockchain, edge computing, and automation. These combinations enhance efficiency, fortify security, and create deeper competitive moats, unlocking entirely new revenue streams. Companies that embed AI within broader technological ecosystems make their solutions harder to replicate, strengthening their market position and long-term value.8
By addressing mission-critical industry challenges, these AI-driven solutions justify premium pricing models and secure long-term contracts. Their deep integration into business operations results in high switching costs, making them indispensable to customers and ensuring recurring revenue.9
Look ahead three years and the vertical AI landscape will be dramatically different. Industry analysts expect at least five companies to cross the $100M ARR threshold by then – a milestone that separates the serious players from the merely interesting startups. The first vertical AI IPO will likely hit public markets in that same window, bringing broader investor attention to the category.
The timing couldn't be better. Healthcare, legal services, and financial firms face crippling labor shortages with no quick fix in sight. Vertical AI isn't just offering incremental efficiency – it's becoming essential infrastructure for industries that can't hire enough skilled professionals to meet demand.
What's curious is how relatively underfunded this category remains despite the clear potential. While founders chasing the next ChatGPT attract billion-dollar valuations on little more than technical demos, companies solving actual business problems with domain-specific AI are raising at valuations that still make fundamental sense.
The contrast in funding efficiency is stark. Training another large language model might require $100M+ just to cover compute costs, with commercialization still a distant hope. Meanwhile, vertical AI startups typically raise $2-8M at early stages and convert that capital directly into customer acquisition and revenue.
For investors, this presents a compelling proposition: back businesses that can achieve profitability without the infrastructure costs of general AI. The capital efficiency translates to lower dilution for founders and investors alike, while the faster path to revenue reduces overall investment risk.
The potential returns look particularly attractive as these solutions gain traction across major industries. Companies that establish leadership positions now will be difficult to dislodge later, creating powerful first-mover advantages for early investors.
The next wave of enterprise value creation won't come from marginally better chatbots or text generators. It will emerge from AI that's purpose-built to solve specific industry challenges – improving patient outcomes, accelerating financial decisions, optimizing supply chains, and transforming dozens of other critical business functions.
For investors, vertical AI isn't just another trend to watch – it represents a fundamental shift in how enterprise software creates and captures value. The winning companies will build defensible positions through proprietary data and deeply integrated workflows, deliver measurable ROI from day one, and command premium pricing by solving mission-critical problems.
As adoption accelerates across trillion-dollar markets, early movers are establishing positions that will be nearly impossible to challenge once embedded. The opportunity window won't stay open indefinitely.
At Venture Forward Capital, we're backing founders who understand that the most valuable AI isn't necessarily the most generalized – it's the most relevant. Whether you're a seasoned tech investor or just beginning to explore AI opportunities, vertical applications offer the rare combination of growth potential and business fundamentals that create category-defining companies.
The hype cycle will eventually move on. The value creation won't.
1. Global Market Insights. "Vertical AI Market Size, Share & Growth Report, 2024-2034."Global Market Insights, 2024, https://www.gminsights.com/industry-analysis/vertical-ai-market
2. Bessemer Venture Partners. The Future of AI Is Vertical." Bessemer Venture Partners, 2024, https://www.bvp.com/atlas/part-i-the-future-of-ai-is-vertical.
3. "Tomorrow's Titans: Vertical AI." New Enterprise Associates (NEA), https://www.nea.com/blog/tomorrows-titans-vertical-ai
4. Shuman, Jason. "Vertical AI vs. Software: How Founders Are Navigating the Rapidly Evolving Landscape." LinkedIn, 11 Mar. 2025, www.linkedin.com/pulse/vertical-ai-software-how-founders-navigating-rapidly-evolving-shuman-vuaze/
5. Bessemer Venture Partners. "The Future of AI Is Vertical." Bessemer Venture Partners, https://www.bvp.com/atlas/part-i-the-future-of-ai-is-vertical
6. "Vertical AI Market Trends." Global Market Insights, https://www.gminsights.com/industry-analysis/vertical-ai-market/market-trends.
7. "Artificial Intelligence Market Size | Industry Report, 2030." Grand View Research, https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market.
8. Pandey, Vijay. "Financial Technology Trends and Vertical AI Technology." Forbes, 19 Feb. 2025, https://www.forbes.com/councils/forbesfinancecouncil/2025/02/19/financial-technology-trends-and-vertical-ai-technology/
9. "Artificial Intelligence (AI) Market." MarketsandMarkets, https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html