Vertical AI Market

Vertical AI Market Size

The global vertical AI market was valued at USD 10.2 Billion in 2024 and is estimated to register a CAGR of 21.6% between 2025 and 2034. Vertical AI seeks to cater to the distinct needs of industries such as healthcare, automotive, manufacturing, and finance. This enables Vertical AI to customize tools specifically designed to optimize processes within the industry as well as solve challenges beyond the reach of traditional AI solutions. Bespoke issues in specific industries are referred to as the ‘vertical’ characteristic of AI in AI optimization.

The AIM-MASH leverages AI technology to assist in grading and staging fibrosis of MASH Clinical Research Network’s Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD). This release seeks to enhance pathologists’ management of MASH cases with the aim of achieving better consistency and scalability in assessments. The creation of the product allows further improvement in MASH evaluation by pathologists, who are able now to do this more precisely and more accurately which enhances the whole drug development process.

As the automation of processes becomes commonplace, the need for the implementation of new technologies is rapidly growing. Vertical AI helps automate many sectors which involve tedious but absolutely necessary work processes. AI has made production facilities more efficient by automating quality assurance and predictive maintenance, which decreases downtimes for manufacturing. Most of the common queries by clients are handled by AI-lead chat support which enables human operators to focus on more complex problems that need resolution.

The progressive boom in AI vertical creates demand for automation which includes process optimization and increase in operational output while minimizing labor costs; this is a key factor for automation processes to development.

Vertical AI Market Trends

The integration of vertical AI with other emerging technologies, such as IoT, 5G, and edge computing increases its usefulness. In the automotive field, AI augmented IoT is used for real time performance metrics on the vehicle, and AI integrated with 5G is used in multiple sectors like healthcare to enable high speed data communication. The introduction of vertical AI and other technologies leads to intelligent and adaptive responses capable of enhancing performance while providing enriched insights. The pressure to utilize AI in conjunction with other emerging technologies is driving the development of vertical AI and concomitantly, the market demand.

The goals of vertical AI providers concentrate on developing AI products for the various industries. For example, in August 2024, Caregility Corporation, a telehealth services provider enterprise, has publicly stated that it has added a new IObserver Solution feature which detects the risk of falls. Hospital care teams employ iObserver for the continuous surveillance of patients at risk for self-inflicted harm or fall. New AI capabilities are used by Caregility that were developed in-house and use computer vision analytics to assess images for indicators of potential falls and provide warnings to caregivers.

With the surge of large volumes of data across industries, vast amounts of information are required by AI systems to formulate decisions. Statista states that, in 2024, the size of data created, captured, copied, and consumed globally reached 149 zettabytes. Vertical AI enhances business processes, optimizes customer interactions, and fosters insights based on this data.

In the medical field, for example, AI diagnostic machines scrutinize patients’ histories and records to find commonalities to predict conditions and interventions. Transactional data is used by AI systems in finance to identify instances of fraudulent activities. The exponential growth of big data, coupled with the capabilities of cloud computing and edge devices, fuels the expansion of AI in vertical industries.

The first investment into vertical AI solutions can be quite prohibitive for many organizations. In the case of vertical AI, building specific models for a particular industry, putting in place the requisite infrastructure, and training AI-skilled personnel involves a heavy expenditure. Moreover, in case an industry does not have the requisite data or infrastructure to support AI, the costs of establishing the support framework can be considerably higher. This implies the developed setup can exclude SMEs from utilizing vertical AI and keep its use to large firms with deeper pockets and resources.

Vertical AI Market Analysis

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Based on deployment model, the vertical AI market is divided into on-premises, cloud and hybrid. In 2024, the cloud segment held a market share of over 60% and is expected to cross USD 40 billion by 2034.  

• Cloud-based Vvertical AI solutions enable companies to expand their business profitably and quickly. These solutions allow businesses to grow their IT infrastructure without large upfront spending on hardware, thanks to the cloud.
  

This is essential for industries that are data-intensive and run sophisticated AI algorithms. Most cloud service providers operate with a pay-as-you-go model, which brings AI technologies within the reach of smaller enterprises. This results in quicker AI adoption across industries. The cloud ecosystem comprises many data stores, analytical tools, and APIs that simplify the incorporation of vertical AI with existing cloud-based solutions and bolster vertical AI deployment, particularly in healthcare and finance, where timely access to processed information is critical.

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Based on technology, the vertical AI market is categorized into machine learning, deep learning, natural language processing, computer vision, robotics and others. The machine learning segment held a market share of 36% in 2024.

• Machine learning, as a component of AI, is excellent for businesses as it can predict the future by analyzing past data, which enables multiple sectors, including retail, insurance, and finance, to benefit.
  

It automates formerly manual tasks such as classification of data, anomaly detection, and risk assessment. Most retailers employ it to predict the consumption patterns of their customers, while finance companies employ it to estimate risk exposure for credit. This is expected to drive the segment growth during the forecast period. Machine learning models continue to evolve, and their utility within industries is being expanded to improve decision-making processes.

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• North America dominated the global vertical AI market with a major share of around 40% in 2024 and the U.S. leads the market in the region. The strong technological base in any region fosters the adoption of vertical AI in North America. Major technological clusters like Silicon Valley and the emphasis on digital evolution mean that businesses in North America tend to consume more AI products. In addition, vertical artificial intelligence development and research get substantial backing in the US. VCs and government programs support artificial intelligence innovation, which funds the growth of industry-focused AI startups. This, in turn, drives the expansion of the vertical AI market.
  
• China, Japan, India, and other countries in Asia-Pacific are expected to adopt vertical AI due to rapid industrialization. For example, smart city initiatives in China employ AI for urban planning, resource management, and traffic optimization. With the ongoing transformation into cities, environmental conservation, traffic congestion, and healthcare availability issues are tackled using vertical AI technology. There are some of the biggest manufacturing hubs in this region.
  
• The vertical AI development in these countries is due to a strong demand for automation. AI robots, quality and process control, as well as predictive maintenance, are now integral to the production value chain for industries ranging from electronics to automotive. These factors propel the rate of adoption of vertical AI in this region due to smart manufacturing as well as Industry 4.0.
  
• The specialized AI industry focuses on machine learning that helps tackle specific issues. The AI systems are trained and engineered with Artificial Intelligence methods that help extract information. The sophisticated analytics and structured machines used with data allow businesses in finance and healthcare to not only trust the system but also lower any possible legal risks and enhance compliance.
  
• To add on, AI-powered compliance systems make it easier for banks that deal with anti-money laundering to tackle the set standards from Europe. Their focus is solely on these compliance issues rather, which in turn their focus is switched from helping the company with anything else. Alongside this, vertical AI in manufacturing, agriculture, and energy is being driven by strong common guiding principles with the region's vertical specialization promoting regulatory extensiveness anchor concerns.
  

Vertical AI Market Share

• Recursion Pharmaceuticals and Path AI hold a market share of over 5% in the vertical AI industry. Strength-wise, Recursion Pharmaceuticals has leveraged Exscientia and merged with them to boost their capabilities. The sophisticated chemistry tools of Exscientia combined into an AI-powered platform allow Recursion to advance into new avenues like large-scale biological research.
  
• Besides that, Recursion has merged with other big pharmaceutical corporations such as Roche, Bayer, and Genentech, targeting huge advances in neurosurgery, oncology, and challenging ovarian cancers.
  
• Like many other businesses, PathAI is leveraging machine learning for better accuracy when diagnosing patients for pathological issues. PathAI is taking traditional pathology workflows and converting them into artificial intelligence-powered systems by improving algorithms for disease detection and treatment response.
  
• The company has partnered with some of the most important global healthcare companies, including Labcorp, Bristol-Myers Squibb, and Roche. These alliances focus on the application of AI in decision-making processes of diagnosis and therapeutics, which reflects PathAI's approach of regional integration of its solutions in every segment of healthcare.
  

Vertical AI Market Companies

Major players operating in the vertical AI industry include:

• Atomwise
• BenevolentAI
• Blue River Technology
• Databricks
• Farmers Edge
• Harvey AI
• Insilico Medicine
• Nauto
• Path AI
• Recursion Pharmaceuticals
  

The vertical AI market is now shifting towards providing domain-centric solutions as the players are already solving problems for healthcare, finance, retail, manufacturing, so on and so forth. This is done through specialized algorithms applied on big data captured for decision making and other business processes.

Partnerships with key industry players and collaborations with research institutions are gaining prevalence among market players to boost their technological capabilities and gain greater coverage in the vertical AI market. Moreover, significant attention is paid towards the development of AI-compatible solutions for the enterprise systems which are already in place to ensure system adoption and growth. Market players are becoming more accommodating by introducing cloud and on-premise based flexible deployment alternatives to meet the diverse enterprise and regulatory requirements.

Vertical AI Industry News

• In June 2024, Simplify Healthcare, a provider of enterprise SaaS solutions for health insurance companies (Payers), acquired Virtical.ai, an innovative AI company. The acquisition highlights Simplify company’s commitment to providing its Payer clients with advanced AI technology and strengthens its leadership in the AI field. The acquisition will benefit customers of both companies. By combining Simplify Healthcare's cloud platform, Simplify Health Cloud, with Virtical.ai's AI solutions, the companies will offer a powerful set of tools that enhance innovation, efficiency, and growth for Payers.
  
• In October 2023, Infinity Learn launched Virtual Intelligent System for Tailored Academics (VISTA), an innovative AI solution for education. VISTA uses AI to tackle issues faced by teachers and students. This solution is available through mobile and web applications, providing users with advanced tools at their fingertips.
  

The vertical AI market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue ($Bn) from 2021 to 2034, for the following segments:

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Market, By Component

• Hardware
• Software
• Services
  • Professional services
  • Managed services

Market, By Deployment Model

• On-premises
• Cloud
• Hybrid

Market, By Enterprise Size

Large enterprises

SME

Market, By Technology

• Machine learning
• Deep learning
• Natural language processing
• Computer vision
• Robotics
• Others

Market, By End Use

• Healthcare
  • Clinical applications
  • Drug discovery & development
  • Medical imaging
  • Healthcare operations
• BFSI
  • Banking
  • Investment & trading
  • Insurance
• Manufacturing & Industrial
  • Production operations
  • Supply chain
  • Industrial IoT
• Agriculture & farming
  • Crop management
  • Livestock management
  • Precision agriculture
• Legal & Compliance
  • Legal research
  • Contract management
  • Regulatory compliance
• Retail & e-commerce
  • Customer experience
  • Operations
  • Marketing & sales
• Energy & Utilities
  • Power generation
  • Energy trading
  • Distribution
  • Renewable energy
• Transportation & logistics
  • Fleet management
  • Supply chain
  • Infrastructure
• Others

The above information is provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Nordics
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • Southeast Asia 
• Latin America
  • Brazil
  • Mexico
  • Argentina 
• MEA
  • UAE
  • South Africa
  • Saudi Arabia