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As per Intent Market Research, the Artificial Intelligence (AI) in Video Surveillance Market was valued at USD 5.3 billion in 2023 and will surpass USD 22.7 billion by 2030; growing at a CAGR of 23.1% during 2024 - 2030.
The artificial intelligence (AI) in video surveillance market has emerged as a pivotal sector, driven by the growing need for enhanced security solutions across various industries. As security threats evolve and become more sophisticated, traditional surveillance methods are proving insufficient. The integration of AI technologies into video surveillance systems enables organizations to analyze vast amounts of data in real-time, improving incident detection, response times, and overall situational awareness. This transition is reshaping the security landscape, providing advanced features such as facial recognition, behavioral analysis, and anomaly detection, ultimately transforming the way organizations manage security.
This growth can be attributed to the increasing adoption of AI technologies across sectors such as retail, transportation, healthcare, and smart cities. As businesses recognize the value of integrating AI-driven surveillance systems to safeguard assets, improve operational efficiency, and enhance customer experiences.
The software segment of the AI in video surveillance market holds the largest share, primarily due to the demand for advanced analytical capabilities. AI-driven software applications enhance the functionality of video surveillance systems by providing real-time data analysis, alerting users to potential security threats, and automating responses to incidents. Features such as facial recognition, object detection, and crowd analytics are becoming increasingly essential for organizations looking to bolster their security measures.
Furthermore, the continuous advancements in machine learning algorithms and deep learning techniques are driving the development of sophisticated software solutions. These innovations enable more accurate surveillance and predictive analytics, leading to improved decision-making processes. As organizations invest in upgrading their surveillance systems to incorporate AI software, this segment is expected to maintain its dominant position in the AI in video surveillance market throughout the forecast period.
The services segment is recognized as the fastest-growing component of the AI in video surveillance market, propelled by the rising demand for customized solutions and ongoing support. As organizations increasingly adopt AI-powered video surveillance systems, there is a growing need for consulting, installation, maintenance, and training services. Providers of these services play a crucial role in helping clients integrate AI technologies into their existing systems, ensuring optimal functionality and performance.
Moreover, the complexity of AI technologies necessitates specialized expertise for effective implementation and management. Service providers are focusing on developing tailored solutions that align with the unique requirements of various industries, including retail, transportation, and public safety. This trend is fostering stronger partnerships between clients and service providers, further driving growth in the services segment. As organizations prioritize effective surveillance solutions, the demand for comprehensive services is expected to accelerate, making it a key area of growth in the AI in video surveillance market.
The hardware segment of the AI in video surveillance market is the largest, primarily due to the increased adoption of advanced surveillance devices equipped with AI capabilities. This includes high-definition cameras, sensors, and recording devices that are essential for capturing and processing video data. The transition from traditional analog systems to IP-based solutions has further propelled the demand for cutting-edge hardware, as organizations seek to enhance their surveillance capabilities.
Additionally, the integration of AI technologies into hardware components enables enhanced features such as real-time image processing, advanced encoding, and improved storage solutions. This integration not only boosts the effectiveness of surveillance systems but also reduces operational costs associated with manual monitoring. As organizations continue to invest in high-quality surveillance hardware to enhance security measures, this segment is expected to maintain its leadership position in the AI in video surveillance market.
The transportation segment is emerging as the fastest-growing area within the AI in video surveillance market, driven by the proliferation of smart city initiatives. Governments and municipalities are increasingly leveraging AI-powered video surveillance to enhance public safety, traffic management, and infrastructure monitoring. By integrating AI technologies into transportation networks, authorities can analyze real-time data to optimize traffic flow, monitor vehicular activities, and enhance incident response capabilities.
Moreover, the rise of connected vehicles and intelligent transportation systems is further accelerating the demand for AI-driven surveillance solutions in this segment. These technologies enable improved situational awareness and facilitate the collection of valuable data for urban planning and development. As cities worldwide prioritize safety and efficiency, the transportation segment is poised for substantial growth, positioning itself as a key player in the AI in video surveillance market.
The Asia-Pacific region is recognized as the fastest-growing market for AI in video surveillance, fueled by rapid urbanization, rising security concerns, and increasing investments in smart city initiatives. Countries such as China, India, and Japan are at the forefront of adopting AI technologies across various sectors, leading to significant demand for advanced surveillance solutions. The growing middle-class population in this region is also contributing to the rising need for enhanced security measures in residential, commercial, and public spaces.
Additionally, the presence of numerous technology companies and start-ups specializing in AI and surveillance solutions is fostering innovation and competition in the region. Governments are actively promoting the adoption of AI-driven video surveillance systems to enhance public safety and support law enforcement efforts. As the Asia-Pacific region continues to embrace digital transformation and prioritize security, it is expected to maintain its position as a leader in the global AI in video surveillance market.
The competitive landscape of the AI in video surveillance market is characterized by the presence of several prominent players and a rapidly evolving environment marked by technological advancements. Leading companies such as Hikvision Digital Technology Co., Ltd., Dahua Technology Co., Ltd., Axis Communications AB, and Bosch Security Systems dominate the market by offering a diverse range of AI-driven surveillance products and solutions. These companies invest heavily in research and development to enhance their offerings, ensuring they remain at the forefront of innovation.
Moreover, the market is witnessing the emergence of new entrants and niche players focusing on specialized AI solutions, such as advanced analytics, cloud-based storage, and integrated security systems. These players are leveraging their expertise to provide unique offerings tailored to specific industry needs, creating a dynamic competitive environment. As competition intensifies, companies are likely to pursue strategic partnerships, mergers, and acquisitions to strengthen their market presence and capitalize on emerging trends, ensuring a vibrant and rapidly evolving landscape in the AI in video surveillance market throughout the forecast period and beyond.
The report will help you answer some of the most critical questions in the Artificial Intelligence (AI) in Video Surveillance Market. A few of them are as follows:
Report Features |
Description |
Market Size (2023) |
USD 5.3 billion |
Forecasted Value (2030) |
USD 22.7 billion |
CAGR (2024 – 2030) |
23.1% |
Base Year for Estimation |
2023 |
Historic Year |
2022 |
Forecast Period |
2024 – 2030 |
Report Coverage |
Market Forecast, Market Dynamics, Competitive Landscape, Recent Developments |
Segments Covered |
AI in Video Surveillance Market By Offering (Software, Service, Hardware), By Deployment Mode (On-Premises, Cloud Based), By End Use (Commercial, Residential, Infrastructure, Military & Defense, Public Facility, Industrial) |
Regional Analysis |
North America (US, Canada, Mexico), Europe (Germany, France, UK, Spain, Italy & Rest of Europe), Asia Pacific (China, Japan, South Korea, India, and Rest of Asia Pacific), Latin America (Brazil, Argentina, & Rest of Latin America), Middle East & Africa (Saudi Arabia, South Africa, Turkey, United Arab Emirates, & Rest of MEA) |
Customization Scope |
Customization for segments, region/country-level will be provided. Moreover, additional customization can be done based on the requirements |
1.Introduction |
1.1.Market Definition |
1.2.Scope of the Study |
1.3.Research Assumptions |
1.4.Study Limitations |
2.Research Methodology |
2.1.Research Approach |
2.1.1.Top-Down Method |
2.1.2.Bottom-Up Method |
2.1.3.Factor Impact Analysis |
2.2.Insights & Data Collection Process |
2.2.1.Secondary Research |
2.2.2.Primary Research |
2.3.Data Mining Process |
2.3.1.Data Analysis |
2.3.2.Data Validation and Revalidation |
2.3.3.Data Triangulation |
3.Executive Summary |
3.1.Major Markets & Segments |
3.2.Highest Growing Regions and Respective Countries |
3.3.Impact of Growth Drivers & Inhibitors |
3.4.Regulatory Overview by Country |
4.Artificial Intelligence (AI) in Video Surveillance Market, by Offering (Market Size & Forecast: USD Million, 2022 – 2030) |
4.1.Software |
4.2.Service |
4.3.Hardware |
5.Artificial Intelligence (AI) in Video Surveillance Market, by Deployment Mode (Market Size & Forecast: USD Million, 2022 – 2030) |
5.1.On Premises |
5.2.Cloud Based |
6.Artificial Intelligence (AI) in Video Surveillance Market, by End Use (Market Size & Forecast: USD Million, 2022 – 2030) |
6.1.Military & Defense |
6.1.1.Prison & Correctional Facilities |
6.1.2.Border Surveillance |
6.1.3.Coastal Surveillance |
6.1.4.Law Enforcement |
6.2.Residential |
6.3.Infrastructure |
6.3.1.Transportation |
6.3.2.City Surveillance |
6.3.3.Utility |
6.4.Commercial |
6.4.1.Retail Stores & Malls |
6.4.2.Enterprises & Data Centers |
6.4.3.Banking & Financial Buildings |
6.4.4.Hospitality Centers |
6.4.5.Warehouses |
6.5.Public Facility |
6.5.1.Healthcare Buildings |
6.5.2.Educational Buildings |
6.5.3.Government Buildings |
6.5.4.Religious Buildings |
6.6.Industrial |
6.6.1.Manufacturing Facilities |
6.6.2.Construction Sites |
7.Regional Analysis (Market Size & Forecast: USD Million, 2022 – 2030) |
7.1.Regional Overview |
7.2.North America |
7.2.1.Regional Trends & Growth Drivers |
7.2.2.Barriers & Challenges |
7.2.3.Opportunities |
7.2.4.Factor Impact Analysis |
7.2.5.Technology Trends |
7.2.6.North America Artificial Intelligence (AI) in Video Surveillance Market, by Offering |
7.2.7.North America Artificial Intelligence (AI) in Video Surveillance Market, by Deployment Mode |
7.2.8.North America Artificial Intelligence (AI) in Video Surveillance Market, by End Use |
*Similar segmentation will be provided at each regional level |
7.3.By Country |
7.3.1.US |
7.3.1.1.US Artificial Intelligence (AI) in Video Surveillance Market, by Offering |
7.3.1.2.US Artificial Intelligence (AI) in Video Surveillance Market, by Deployment Mode |
7.3.1.3.US Artificial Intelligence (AI) in Video Surveillance Market, by End Use |
7.3.2.Canada |
7.3.3.Mexico |
*Similar segmentation will be provided at each country level |
7.4.Europe |
7.5.APAC |
7.6.Latin America |
7.7.Middle East & Africa |
8.Competitive Landscape |
8.1.Overview of the Key Players |
8.2.Competitive Ecosystem |
8.2.1.Level of Fragmentation |
8.2.2.Market Consolidation |
8.2.3.Product Innovation |
8.3.Company Share Analysis |
8.4.Company Benchmarking Matrix |
8.4.1.Strategic Overview |
8.4.2.Product Innovations |
8.5.Start-up Ecosystem |
8.6.Strategic Competitive Insights/ Customer Imperatives |
8.7.ESG Matrix/ Sustainability Matrix |
8.8.Manufacturing Network |
8.8.1.Locations |
8.8.2.Supply Chain and Logistics |
8.8.3.Product Flexibility/Customization |
8.8.4.Digital Transformation and Connectivity |
8.8.5.Environmental and Regulatory Compliance |
8.9.Technology Readiness Level Matrix |
8.10.Technology Maturity Curve |
8.11.Buying Criteria |
9.Company Profiles |
9.1.Hangzhou Hikvision Digital Technology |
9.1.1.Company Overview |
9.1.2.Company Financials |
9.1.3.Product/Service Portfolio |
9.1.4.Recent Developments |
9.1.5.IMR Analysis |
*Similar information will be provided for other companies |
9.2.Dahua Technology |
9.3.SenseTime |
9.4.Zhejiang Uniview Technologies |
9.5.Avigilon Corporation (Motorola Solutions) |
9.6.Milestone Systems |
9.7.YITU Tech |
9.8.NEC Corporation |
9.9.Genetec Inc. |
9.10.CloudWalk Technology |
10.Appendix |
A comprehensive market research approach was employed to gather and analyze data on the Artificial Intelligence (AI) in Video Surveillance Market. In the process, the analysis was also done to analyze the parent market and relevant adjacencies to measure the impact of them on the Artificial Intelligence (AI) in Video Surveillance Market. The research methodology encompassed both secondary and primary research techniques, ensuring the accuracy and credibility of the findings.
Secondary research involved a thorough review of pertinent industry reports, journals, articles, and publications. Additionally, annual reports, press releases, and investor presentations of industry players were scrutinized to gain insights into their market positioning and strategies.
Primary research involved conducting in-depth interviews with industry experts, stakeholders, and market participants across the Artificial Intelligence (AI) in Video Surveillance ecosystem. The primary research objectives included:
A combination of top-down and bottom-up approaches was utilized to analyze the overall size of the Artificial Intelligence (AI) in Video Surveillance Market. These methods were also employed to assess the size of various subsegments within the market. The market size assessment methodology encompassed the following steps:
To ensure the accuracy and reliability of the market size, data triangulation was implemented. This involved cross-referencing data from various sources, including demand and supply side factors, market trends, and expert opinions. Additionally, top-down and bottom-up approaches were employed to validate the market size assessment.