AI In Video Surveillance Market Size & Share 2024 - 2032
Market Size by Component (Hardware, Software, Services), Deployment (Cloud-based, On Premise), End Users (Commercial, Residential, Infrastructure, Defense and Military, Public Facility, Industrial), Use Cases & Forecast.
Report ID: GMI8110
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Published Date: February 2024
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Report Format: PDF
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Authors:
Suraj Gujar, Sandeep Ugale
AI in Video Surveillance Market Size
AI in Video Surveillance Market size was valued at USD 5.5 billion in 2023 and is estimated to register a CAGR of over 15.5% between 2024 and 2032. With increasing security threats globally, there is a growing demand for advanced surveillance systems that can effectively monitor and protect public and private spaces. AI-powered video surveillance offers enhanced capabilities such as real-time threat detection, facial recognition, and behavior analysis, making it a preferred choice for security applications.
AI In Video Surveillance Market Key Takeaways
Market Size & Growth
Key Market Drivers
Challenges
The rapid advancements in artificial intelligence and deep learning technologies have enabled the development of sophisticated video analytics algorithms. These algorithms can automatically detect and classify objects, people, and activities in video feeds with high accuracy, improving the overall effectiveness of surveillance systems. AI-driven video surveillance systems can automate many tasks that would otherwise require human intervention, leading to cost savings for organizations.
Additionally, these systems can analyze vast amounts of video data in real-time, enabling proactive responses to security threats and reducing the need for manual monitoring. Additionally, In May 2023, Motorola Solutions, the parent company of Avigilion, released the V700 body camera a mobile broadband-enabled camera, to ensure a clear, accurate account of events, the V700's precision high-definition sensor adjusts to low lighting like a human eye.
AI algorithms used in video surveillance systems are susceptible to biases, both in their development and deployment. Biases can result from various factors, including biased training data, flawed algorithms, or improper calibration. These biases can lead to inaccurate or discriminatory outcomes, such as misidentifying individuals or misclassifying activities. Addressing algorithmic bias and ensuring the accuracy and fairness of AI-powered video surveillance systems is crucial to maintain trust, credibility, and effectiveness in security applications.
AI in Video Surveillance Market Trends
A notable trend in the AI in video surveillance industry is the increasing integration of edge computing capabilities. Edge computing involves processing data closer to its source rather than relying on centralized servers. In the context of video surveillance, this means deploying AI algorithms directly on cameras or edge devices, enabling real-time analysis of video feeds. This trend is driven by the need for faster response times, reduced bandwidth usage, and improved privacy by processing sensitive data locally.
Additionally, edge computing facilitates distributed intelligence, allowing surveillance systems to operate effectively even in environments with limited connectivity or latency constraints. As edge computing technologies continue to mature, we can expect further advancements in AI-powered video surveillance solutions, enhancing their scalability, efficiency, and effectiveness.
Another significant trend is the adoption of hybrid cloud architectures in AI in video surveillance market. Hybrid cloud solutions combine on-premises infrastructure with cloud-based services, offering a balance between data locality, scalability, and cost-effectiveness. In the context of video surveillance, hybrid cloud architectures allow organizations to store and analyze video data both locally and, in the cloud, depending on factors such as storage requirements, processing capabilities, and regulatory compliance. This trend enables seamless integration with existing surveillance infrastructure while leveraging the scalability and computational power of the cloud for tasks such as long-term storage, analytics, and machine learning.
By embracing hybrid cloud solutions, organizations can optimize their video surveillance operations, enhance situational awareness, and adapt to evolving security needs effectively. For Insttance, In Sep-2022: Hikvision made enhancements to its Pro series PTZ cameras with the addition of ColorVu technology. The integration of ColorVu in Hikvision's new Pro series cameras would deliver consistent image brightness and complete color imaging as the camera zooms in and out. Furthermore, the enhancement makes sure crystal-clear details and vivid color for distant objects at all times and in all situations.
AI in Video Surveillance Market Analysis
Based on the use cases, the gun detection segment is poised to witness over 15% CAGR from 2024 to 2032. Gun detection technology has emerged as a critical component in the market, leveraging semantic networks to enhance its capabilities. Semantic networks, a form of artificial intelligence, enable systems to understand the relationships between different entities within a given context, facilitating more accurate and contextualized analysis of video data.
Furthermore, semantic networks enable interoperability and integration with other AI-based modules within the surveillance ecosystem. For example, gun detection algorithms can communicate with facial recognition systems to identify individuals carrying firearms or with object tracking modules to monitor the movement of weapons within a monitored area. This holistic approach enhances the overall effectiveness of video surveillance systems in detecting and responding to potential security threats, making semantic networks a valuable tool in the evolving landscape of AI-powered video surveillance.
Based on the end user, the commercial segment held over 30% of the AI in video surveillance market share in 2023. In the commercial segment, AI-powered video surveillance systems offer various benefits tailored to the specific needs of businesses. These systems can detect and deter theft, vandalism, and unauthorized access in retail environments, thereby reducing losses and enhancing safety for employees and customers.
Additionally, AI algorithms can analyze customer behavior and preferences, providing valuable insights for marketing, merchandising, and operational decision-making. Furthermore, commercial establishments leverage AI-driven video analytics to improve operational efficiency and customer service. For instance, real-time monitoring of foot traffic can help optimize staffing levels and queue management, while video analytics can identify maintenance issues or safety hazards before they escalate.
North America AI in video surveillance market accounted for 25% of the revenue share in 2023. With rising security threats and incidents, there is a growing demand for advanced surveillance solutions in North America. AI-powered video surveillance offers enhanced capabilities such as real-time threat detection, facial recognition, and behavior analysis, making it a preferred choice for security applications in the region.
North America is home to many leading technology companies and research institutions driving innovations in artificial intelligence and video analytics. These advancements enable the development of sophisticated AI algorithms that can automatically detect and classify objects, people, and activities in video feeds with high accuracy, further fueling the adoption of AI in video surveillance.
AI in Video Surveillance Market Share
Honeywell International holds a significant market share in the AI in video surveillance industry. Offering a range of innovative solutions tailored to meet the security needs of diverse industries. Honeywell's video surveillance offerings combine advanced AI technologies with robust hardware and software solutions to provide comprehensive security and surveillance.
Major players, such as Avigilon Hikvision Dahua Technology Axis Communications Hanwha Techwin Bosch Security Systems Honeywell., are constantly implementing strategic measures including geographical expansion, acquisitions, mergers, collaborations, partnerships, and product or service launches.
AI in Video Surveillance Market Companies
Major companies operating in the AI in video surveillance industry are:
AI in Video Surveillance Industry News
The AI in video surveillance market research report includes in-depth coverage of the industry with estimates & forecast in terms of revenue (USD Billion) from 2018 to 2032, for the following segments:
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Market, By Component
Market, By Deployment
Market, By Use Cases
Market, By End User
The above information has been provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
1. Research design & analyst oversight
At GMI, our research methodology is built on a foundation of human expertise, rigorous validation, and complete transparency. Every insight, trend analysis, and forecast in our reports is developed by experienced analysts who understand the nuances of your market.
Our approach integrates extensive primary research through direct engagement with industry participants and experts, complemented by comprehensive secondary research from verified global sources. We apply quantified impact analysis to deliver dependable forecasts, while maintaining complete traceability from original data sources to final insights.
2. Primary research
Primary research forms the backbone of our methodology, contributing nearly 80% to overall insights. It involves direct engagement with industry participants to ensure accuracy and depth in analysis. Our structured interview program covers regional and global markets, with inputs from C-suite executives, directors, and subject matter experts. These interactions provide strategic, operational, and technical perspectives, enabling well-rounded insights and reliable market forecasts.
3. Data mining & market analysis
Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.
4. Market sizing
Our market sizing is built on a bottom-up approach, starting with company revenue data gathered directly through primary interviews, alongside production volume figures from manufacturers and installation or deployment statistics. These inputs are then pieced together across regional markets to arrive at a global estimate that stays grounded in actual industry activity.
5. Forecast model & key assumptions
Every forecast includes explicit documentation of:
✓ Key growth drivers and their assumed impact
✓ Restraining factors and mitigation scenarios
✓ Regulatory assumptions and policy change risk
✓ Technology adoption curve parameter
✓ Macroeconomic assumptions (GDP growth, inflation, currency)
✓ Competitive dynamics and market entry/exit expectations
6. Validation & quality assurance
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Our triple-layer validation process ensures maximum data reliability:
✓ Statistical Validation
✓ Expert Validation
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Trust & credibility
Verified data sources
Trade publications
Security & defense sector journals and trade press
Industry databases
Proprietary and third-party market databases
Regulatory filings
Government procurement records and policy documents
Academic research
University studies and specialist institution reports
Company reports
Annual reports, investor presentations, and filings
Expert interviews
C-suite, procurement leads, and technical specialists
GMI archive
13,000+ published studies across 30+ industry verticals
Trade data
Import/export volumes, HS codes, and customs records
Parameters studied & evaluated
Every data point in this report is validated through primary interviews, true bottom-up modelling, and rigorous cross-checks. Read about our research process →