AI in Video Surveillance Market by Component, Technology, Functionality Module, Application, End-User, Deployment Mode

List of Tables

The AI in Video Surveillance Market was valued at USD 4.17 billion in 2024 and is projected to grow to USD 4.82 billion in 2025, with a CAGR of 15.86%, reaching USD 10.10 billion by 2030.

KEY MARKET STATISTICS
Base Year [2024]	USD 4.17 billion
Estimated Year [2025]	USD 4.82 billion
Forecast Year [2030]	USD 10.10 billion
CAGR (%)	15.86%

The emergence of artificial intelligence in video surveillance has redefined the way security solutions are designed and deployed. Rapid advancements in AI algorithms and computer vision have transformed conventional video monitoring into smart, predictive, and highly adaptive systems. These innovations are not only streamlining current security operations but are also enabling proactive threat detection, efficient incident response, and a higher level of situational awareness.

This report examines the evolution of AI-powered surveillance and captures how these technologies have introduced unprecedented levels of accuracy and efficiency. System robustness, scalability, and automation in detection and analysis have collectively driven the industry forward, laying the foundation for comprehensive risk management strategies. As organizations navigate an increasingly complex security landscape, understanding these trends is critical for making informed investment and strategic decisions.

In today's rapidly evolving environment, AI continues to set new benchmarks for performance and reliability. Stakeholders-from technology developers to end-users-are encouraged to recognize the role of innovation in overcoming traditional surveillance challenges with scalable and transformative solutions. Through enhanced automation and integrated analytics, the AI revolution in video surveillance ensures that both public and private sectors can maintain a step ahead in defining secure communities.

Transformative Shifts Redefining Video Surveillance Innovation

In recent years, the landscape of video surveillance has experienced transformative shifts driven by rapid technological advancements and evolving security needs. AI integration has become a linchpin that is redefining traditional practices, providing a quantum leap in system accuracy and real-time responsiveness. The core of these transformative shifts is not only technological but also a strategic rethinking of how surveillance can preempt and mitigate risks.

One of the prominent shifts in the landscape is the convergence of data analytics with real-time video processing. This integration enables systems to analyze multiple data streams simultaneously, recognize unusual behavioral patterns, and issue timely alerts. Traditional video systems, which relied primarily on manual monitoring, have given way to automated platforms that learn over time and improve through feedback loops. The result is a system that continuously evolves, becoming more adept at detecting anomalies such as unauthorized access, suspicious behaviors, or even subtle environmental changes.

Moreover, the adoption of edge computing has minimized latency, ensuring that the heavy lifting of data processing happens near the source. This not only enhances speed but also augments privacy and security by reducing the reliance on centralized data hubs. The shift towards decentralized processing showcases the industry's commitment to balancing operational efficiency with enhanced security protocols.

Enabling these changes are robust collaborations between hardware manufacturers, software developers, and cybersecurity experts. The holistic approach fosters an ecosystem where technological breakthroughs are rapidly disseminated, driving global trends that set new industry standards. By reorienting strategies around agility and resilience, the video surveillance industry has become better equipped to handle both current and emerging threats.

Key Segmentation Insights for a Nuanced Market Approach

A deep dive into the market reveals that segmentation is pivotal for understanding the nuanced demands and growth potential across various facets of AI in video surveillance. The market has been segmented on multiple dimensions to capture the breadth of opportunities available. One vital segmentation is based on the component with a clear division into hardware, service, and software. Within the hardware segment, there is further analysis across access control systems, cameras, monitors, and storage devices; meanwhile, the service component encompasses consulting services, installation, and maintenance; the software side is analyzed via three key aspects: AI in edge computing, video analytics, and video management software solutions.

Another important aspect is the segmentation based on technology. Here, a detailed examination is undertaken across various advanced methodologies including computer vision, deep learning, edge computing, machine learning, and natural language processing. These technologies serve as the backbone for delivering smart surveillance solutions and have been pivotal in elevating system performance and decision accuracy.

Functionality further refines the market segmentation. The functionality module is carefully studied across behavioral analysis, motion detection, and object detection. These specific capabilities allow systems to tailor their approach to different operational scenarios, ensuring that each application delivers optimal performance. The focus on functionality ensures that surveillance systems can adapt to varying environments, whether high-traffic urban areas or quiet industrial settings.

Application-based segmentation offers additional insights by examining the deployment in behavioral analysis, crowd management, industrial monitoring, and traffic monitoring. This level of segmentation is crucial to understanding operational effectiveness in diverse contexts. End-user segmentation indicates that the market caters to a broad range of sectors, including commercial establishments, government and homeland security agencies, industrial setups, and residential environments. In each case, customized surveillance solutions are offered to address the unique challenges and regulatory requirements relevant to the sector.

Moreover, the deployment mode is studied to extract insights across cloud, hybrid, and on-premise configurations. This segmentation reflects the preference for scalable and cost-effective deployments, which are essential for organizations's adapting to evolving security needs. Collectively, these layers of segmentation illustrate a complex yet highly organized market landscape, where each dimension brings critical insights into the development, commercialization, and operational success of AI-driven video surveillance.

Based on Component, market is studied across Hardware, Service, and Software. The Hardware is further studied across Access Control Systems, Cameras, Monitors, and Storage Devices. The Service is further studied across Consulting Services, Installation, and Maintenance. The Software is further studied across AI in Edge Computing, Video Analytics, and Video Management Software (VMS).

Based on Technology, market is studied across Computer Vision, Deep Learning, Edge Computing, Machine Learning, and Natural Language Processing.

Based on Functionality Module, market is studied across Behavioral Analysis, Motion Detection, and Object Detection.

Based on Application, market is studied across Behavioral Analysis, Crowd Management, Industrial Monitoring, and Traffic Monitoring.

Based on End-User, market is studied across Commercial, Government & Homeland Security, Industrial, and Residential.

Based on Deployment Mode, market is studied across Cloud, Hybrid, and On-Premise.

Key Regional Insights Underscoring Global Market Dynamics

The market for AI-powered video surveillance exhibits notable regional diversity, which is crucial to understanding its global dynamics. In the Americas, technological advancements are being rapidly adopted to enhance public and private security infrastructures, driven by a focus on safety and regulatory compliance. The region is characterized by strong investments in technology innovation and partnerships that drive both the emergence and maturation of AI in the security domain.

Across Europe, the Middle East, and Africa, the markets have experienced accelerated growth facilitated by progressive regulatory frameworks and heightened security concerns. These regions are witnessing a dynamic shift as governments and corporations strive for an advanced surveillance setup that integrates real-time analytics and autonomous operation in high-risk environments such as urban centers and critical infrastructure networks.

In Asia-Pacific, the growth trajectory has been particularly impressive, fueled by an already robust technology manufacturing base and a growing appetite for smart city initiatives. Increasing urbanization and heightened awareness of security have led to significant investments in modern surveillance systems. This region continues to evolve, with innovations increasingly aimed at harnessing the full potential of artificial intelligence to deliver context-aware, adaptive security solutions.

Each of these regions contributes uniquely to the overall market, with distinct regulatory requirements, economic dynamics, and cultural influences shaping the adoption and innovation of AI in video surveillance. The interplay between regional trends establishes a global marketplace where localized challenges meet universal technological breakthroughs.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Key Company Insights Highlighting Industry Leaders and Innovators

Significant players in the AI-powered video surveillance market are driving the transformation with innovative products and strategic collaborations. Notable companies include Agent Video Intelligence Ltd. and AllGoVision Technologies Pvt Ltd, which are making considerable strides in enhancing video analytics through AI-based solutions. Companies such as Avigilon Corporation by Motorola Solutions, Inc. and Axis Communications AB are recognized for their robust hardware innovations and comprehensive surveillance systems that consistently set industry benchmarks.

Other industry leaders-like Calipsa Ltd., Canon Inc., and Cognitec Systems GmbH-are deeply engaged in refining image processing and facial recognition technologies. Dahua Technology Co., Ltd. and Digital Barriers plc are known for their cutting-edge video processing equipment, while FLIR Systems, Inc. and Genetec Inc. continue to influence the market with state-of-the-art thermal imaging and integrated security platforms. Meanwhile, Gorilla Technology Group Inc. and Hangzhou Hikvision Digital Technology Co., Ltd. have made substantial investments into developing scalable and reliable systems that combine traditional surveillance with modern analytics capabilities.

Established names including Hanwha Group, Honeywell International Inc., Huawei Technologies Co., Ltd., and IC Realtime LLC have bolstered their market presence through strategic innovations and tailored solutions to emerging security challenges. Companies like Infinova Corporation and Intellivision Technologies Corp. have risen as notable competitors in segments like cloud integration and smart deployment. MOBOTIX AG and NEC Corporation have delivered high-performance surveillance solutions that focus on both ease of implementation and long-term reliability.

In addition, Panasonic Corporation and Robert Bosch GmbH continue to be at the forefront of integrating advanced AI functionalities within their products. SenseTime Group Limited, Sony Corporation, Turing AI, Verint Systems Inc., Vivint, Inc., and VIVOTEK Inc. further diversify the landscape with their varied specialties and comprehensive portfolio of products. These companies collectively drive the market by blending innovative research with practical implementations, ensuring that the industry remains adaptive, forward-looking, and resilient in the face of evolving security challenges.

The report delves into recent significant developments in the AI in Video Surveillance Market, highlighting leading vendors and their innovative profiles. These include Agent Video Intelligence Ltd., AllGoVision Technologies Pvt Ltd, Avigilon Corporation by Motorola Solutions, Inc., Axis Communications AB, Calipsa Ltd., Canon Inc., Cognitec Systems GmbH, Dahua Technology Co., Ltd., Digital Barriers plc, FLIR Systems, Inc., Genetec Inc., Gorilla Technology Group Inc., Hangzhou Hikvision Digital Technology Co., Ltd., Hanwha Group, Honeywell International Inc., Huawei Technologies Co., Ltd., IC Realtime LLC, Infinova Corporation, Intellivision Technologies Corp., MOBOTIX AG, NEC Corporation, Panasonic Corporation, Robert Bosch GmbH, SenseTime Group Limited, Sony Corporation, Turing AI, Verint Systems Inc., Vivint, Inc., and VIVOTEK Inc.. Actionable Recommendations for Industry Leaders Aiming for Tomorrow's Security Solutions

For decision-makers and innovators in the AI in video surveillance space, a few strategic recommendations can pave the way for sustained excellence and competitive advantage. First, invest robustly in research and development to enhance core algorithms behind AI-based analytics. Emphasis on areas like deep learning and computer vision will not only improve detection accuracy but also increase system adaptability. Coupled with edge computing to minimize latency in real-time analysis, this focus will create a full-spectrum solution capable of responding decisively to numerous security threats.

Adopting a modular approach towards system design is equally critical. A modular architecture allows for seamless integration of new technologies while safeguarding existing investments. Embracing cloud, hybrid, or on-premise deployment modes based on operational needs can enhance scalability and offer tailored solutions for diverse end-user requirements. Industry players should ensure that system updates and continuous training of AI models occur regularly, enabling systems to remain effective in the face of evolving threat patterns.

Moreover, collaboration is paramount. Form strategic alliances with technology partners and industry consortia to pool knowledge, share best practices, and foster innovation. A concerted focus on interoperability between systems and devices will ensure that security solutions can function synergistically across diverse platforms. This approach is essential when facing next-generation challenges that require a unified, cross-functional response.

In parallel, market players are encouraged to invest in customer education and structured support systems. Enhancing user understanding of AI capabilities, deploying intuitive interfaces, and delivering dedicated training programs can significantly improve user adoption and overall satisfaction, hence driving both retention and expansion of market share.

Embracing a data-centric approach is another critical recommendation. The integration of vast datasets with advanced analytics can uncover insights that drive predictive assessments and dynamic responses. Regular data audits and adherence to regulatory frameworks will further build trust among stakeholders and end-users, laying the groundwork for sustained success in an increasingly competitive market.

Finally, agile decision-making coupled with strategic long-term planning is essential. The ability to rapidly adapt in response to cybersecurity challenges and market shifts will define the leaders in this field. With a clear roadmap for innovation, industry leaders can secure a future where intelligent video surveillance not only meets but exceeds modern security expectations.

Conclusion: Shaping a Resilient and Intelligent Security Tomorrow

In conclusion, the evolution of AI in video surveillance is a testament to the power of technology in redefining security paradigms. The comprehensive analysis presented here underscores that the convergence of innovative software, robust hardware infrastructures, and intelligent service models is reshaping the global surveillance landscape. By integrating transformative technologies like deep learning, computer vision, and edge computing, the industry unlocks new dimensions of operational efficiency and proactive threat detection.

This in-depth exploration of segmentation-from component and technology to functionality, application, end-user, and deployment mode-reveals that the market is both complex and highly adaptive. The insights into regional trends highlight that while the Americas, Europe, the Middle East & Africa, and Asia-Pacific each have unique market dynamics, the global challenge remains consistent: to implement smarter, more reliable, and scalable surveillance solutions.

Additionally, the review of key companies affirms that a competitive and innovative marketplace is thriving. Companies across the spectrum are setting benchmarks and driving progress through strategic investments and collaborations. Their contributions are critical in the evolving landscape where smart surveillance solutions become increasingly nuanced and indispensable.

Looking forward, the recommendations provided offer a clear pathway for maintaining momentum in research, system optimization, and stakeholder collaboration. With an emphasis on interoperability, continuous innovation, and agile response strategies, industry players can navigate the transforming security landscape with confidence. Ultimately, the intelligent integration of AI in video surveillance is not merely about technology deployment-it is about forging resilient, adaptive, and future-ready security ecosystems.

Product Code: MRR-7F0A2CC1C4F4

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Rising urbanization leading to increased surveillance needs in smart city developments worldwide
  - 5.1.1.2. Growing demand for enhanced security and surveillance measures in both public and private sectors
  - 5.1.1.3. The demand for personalized and data-driven security strategies accelerates AI integration.
- 5.1.2. Restraints
  - 5.1.2.1. Complexity and high cost of implementation and technological integration limiting AI-based surveillance growth
- 5.1.3. Opportunities
  - 5.1.3.1. Increased government investments and regulatory support enhancing AI video surveillance systems
  - 5.1.3.2. AI advancements in drone surveillance applications for large agricultural land monitoring and protection
- 5.1.4. Challenges
  - 5.1.4.1. Concerns associated with cyber-attacks and unauthorized access attempts
5.2. Market Segmentation Analysis
- 5.2.1. Component: Preference for access control system for real-time analytics and to boost security
- 5.2.2. Application: Adoption of AI in video surveillance for crowd management to analyze crowd density, movement flows, and potential bottlenecks in real-time
5.3. Porter's Five Forces Analysis
- 5.3.1. Threat of New Entrants
- 5.3.2. Threat of Substitutes
- 5.3.3. Bargaining Power of Customers
- 5.3.4. Bargaining Power of Suppliers
- 5.3.5. Industry Rivalry
5.4. PESTLE Analysis
- 5.4.1. Political
- 5.4.2. Economic
- 5.4.3. Social
- 5.4.4. Technological
- 5.4.5. Legal
- 5.4.6. Environmental

6. AI in Video Surveillance Market, by Component

6.1. Introduction
6.2. Hardware
- 6.2.1. Access Control Systems
- 6.2.2. Cameras
- 6.2.3. Monitors
- 6.2.4. Storage Devices
6.3. Service
- 6.3.1. Consulting Services
- 6.3.2. Installation
- 6.3.3. Maintenance
6.4. Software
- 6.4.1. AI in Edge Computing
- 6.4.2. Video Analytics
- 6.4.3. Video Management Software (VMS)

7. AI in Video Surveillance Market, by Technology

7.1. Introduction
7.2. Computer Vision
7.3. Deep Learning
7.4. Edge Computing
7.5. Machine Learning
7.6. Natural Language Processing

8. AI in Video Surveillance Market, by Functionality Module

8.1. Introduction
8.2. Behavioral Analysis
8.3. Motion Detection
8.4. Object Detection

9. AI in Video Surveillance Market, by Application

9.1. Introduction
9.2. Behavioral Analysis
9.3. Crowd Management
9.4. Industrial Monitoring
9.5. Traffic Monitoring

10. AI in Video Surveillance Market, by End-User

10.1. Introduction
10.2. Commercial
10.3. Government & Homeland Security
10.4. Industrial
10.5. Residential

11. AI in Video Surveillance Market, by Deployment Mode

11.1. Introduction
11.2. Cloud
11.3. Hybrid
11.4. On-Premise

12. Americas AI in Video Surveillance Market

12.1. Introduction
12.2. Argentina
12.3. Brazil
12.4. Canada
12.5. Mexico
12.6. United States

13. Asia-Pacific AI in Video Surveillance Market

13.1. Introduction
13.2. Australia
13.3. China
13.4. India
13.5. Indonesia
13.6. Japan
13.7. Malaysia
13.8. Philippines
13.9. Singapore
13.10. South Korea
13.11. Taiwan
13.12. Thailand
13.13. Vietnam

14. Europe, Middle East & Africa AI in Video Surveillance Market

14.1. Introduction
14.2. Denmark
14.3. Egypt
14.4. Finland
14.5. France
14.6. Germany
14.7. Israel
14.8. Italy
14.9. Netherlands
14.10. Nigeria
14.11. Norway
14.12. Poland
14.13. Qatar
14.14. Russia
14.15. Saudi Arabia
14.16. South Africa
14.17. Spain
14.18. Sweden
14.19. Switzerland
14.20. Turkey
14.21. United Arab Emirates
14.22. United Kingdom

15. Competitive Landscape

15.1. Market Share Analysis, 2024
15.2. FPNV Positioning Matrix, 2024
15.3. Competitive Scenario Analysis
- 15.3.1. Yotta unveils Drishticam, an AI-enhanced surveillance platform for advanced security
- 15.3.2. Spot AI transforms video surveillance with USD 31 million funding and launch of proactive AI agents
- 15.3.3. Milestone Systems and Arcules merge to transform video surveillance with AI-powered cloud solutions
15.4. Strategy Analysis & Recommendation

Companies Mentioned

1. Agent Video Intelligence Ltd.
2. AllGoVision Technologies Pvt Ltd
3. Avigilon Corporation by Motorola Solutions, Inc.
4. Axis Communications AB
5. Calipsa Ltd.
6. Canon Inc.
7. Cognitec Systems GmbH
8. Dahua Technology Co., Ltd.
9. Digital Barriers plc
10. FLIR Systems, Inc.
11. Genetec Inc.
12. Gorilla Technology Group Inc.
13. Hangzhou Hikvision Digital Technology Co., Ltd.
14. Hanwha Group
15. Honeywell International Inc.
16. Huawei Technologies Co., Ltd.
17. IC Realtime LLC
18. Infinova Corporation
19. Intellivision Technologies Corp.
20. MOBOTIX AG
21. NEC Corporation
22. Panasonic Corporation
23. Robert Bosch GmbH
24. SenseTime Group Limited
25. Sony Corporation
26. Turing AI
27. Verint Systems Inc.
28. Vivint, Inc.
29. VIVOTEK Inc.