Why VCs Are Focusing On Industry-Specific AI Startups

Elena Volotovskaya is the Head of Softline Venture Partners.

The artificial intelligence (AI) sector continues to dominate venture capital (VC) funding, with PitchBook reporting that a third of all VC dollars invested globally in 2024 went to AI startups.

Horizontal AI companies received much of VCs’ attention, with nine-figure rounds fueling compute-intensive foundation models. However, a promising shift is happening in the form of vertical AI.

The AI approach of “verticals” involves feeding domain-specific knowledge into an AI framework. This creates a deeper understanding of complexities and can improve decision making in context-specific situations. And investors are off to find their next unicorn in these less-hyped markets.

Unlike foundation models requiring massive capital for training, vertical AI startups often secure $2 million to $8 million rounds that quickly translate into revenue and growth.

Early-stage investors, like myself, should keep an eye out for the following five spheres.

1. Legal AI

Business Insider noted that $999 million had been put into funding legal and legal-tech companies this year through mid-May. With 89% of experts in the field acknowledging the use cases of GenAI, there are a couple of verticals to consider. E-discovery includes data review, knowledge gathering and billing software. These are all time-intensive tasks that can be done more accurately and better through AI, freeing up time for high-value tasks. Another vertical worth considering is contract life cycle management, where AI is used for analysis, creation or execution of tedious workflows for contracts.

However, I notice that the more niche the solution is, the better. Players here have the tendency to use a mix of horizontal models, which will prove difficult to scale and fully tailor to sector-specific needs.

2. Healthcare AI

With the global AI in healthcare market forecast to reach almost $188 billion by 2030, and $1.68 billion invested in just the first month and a half of the year, the vertical healthcare AI sector is overflowing with opportunities.

Here verticals include drug discovery and diagnosis and treatment support. AI can help accelerate drug discovery by analyzing massive datasets and crafting new compounds that save years in research. According to Deloitte, evidence shows that AI-discovered drugs are more successful in Phase I trials compared to historical averages.

In diagnosis and treatment support, AI can diagnose and tailor treatment options for patients and doctors by combining clinical reasoning of vast patient data (history, genetics, lab results).

A well-timed solution in this resource-intensive sphere has the potential for massive impact and even bigger returns if fundamentals prevail.

3. Fintech AI

IBM reported that companies using AI and automation cut the duration of breaches by 108 days.

In the fintech sector, verticals worth attention address three key problems:

• Fraud Detection And Prevention: Such solutions enhance security with help from machine learning to monitor transactions in real time and spot suspicious patterns.

• Credit Scoring And Lending: Credit assessments are now done with nontraditional data (transaction history or social media) alongside conventional metrics, improving creditworthiness accuracy.

• Customer Support: Area-specific chatbots or AI agents are now automated.

4. Industrial And Manufacturing AI

In VC Lab’s Q2 2025 Venture Trends survey, 6.7% of respondents picked the Deep Tech and Robotics sector as the top VC trend, reinforcing its growth and importance in solving crucial issues such as “manufacturing automation needs” and “supply chain resilience.”

Directions where vertical solutions might see good results include robotics and automation and logistic and route optimization. AI-driven robots now have the capacity to streamline welding, assembling and handling components and reducing human involvement in high-risk tasks. And by interpreting more data from IoT devices, AI can improve routes and schedules.

5. Education AI

According to Reach Capital, U.S. edtech funding stabilized in 2024, ending its two-year consecutive decline, and citing AI as a driving force for startups to build and scale, but also to raise early seed or Series A rounds. In some cases, edtech startups have surpassed average seed or Series A deal sizes.

Two main directions for vertical solutions are personalized learning and proctoring. Edtech providers can use AI to tailor content to students based on a variety of factors, in an effort to increase retention.

AI can also be used to verify identity and monitor behavior to circumvent cheating. AI-powered proctoring tools create fair conditions for students without requiring them to be physically present at a centralized location, reducing cost and increasing flexibility.

To sum up, highly specialized and narrowly focused solutions are gaining momentum as investors are less focused on hype and more wary of overblown valuations. Vertical AI serves as a litmus test for long-term gains.

The information provided here is not investment, tax or financial advice. You should consult with a licensed professional for advice concerning your specific situation.

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