Global AI in Video Analytics Market Outlook 2024–2030

Market Size, Scope, Growth Drivers, Technology Trends, Segmentation, Regional Insights, and Competitive Landscape

Market Overview

The Global AI in Video Analytics Market is experiencing rapid transformation, driven by the convergence of artificial intelligence, computer vision, and advanced video surveillance technologies. The market is projected to reach USD 66.54 billion by 2030, expanding at a strong CAGR of 31.94% during the forecast period (2024–2030).

AI in video analytics refers to the use of intelligent software algorithms to automatically analyze video data captured by surveillance cameras. These systems interpret images, audio, and video streams to detect, classify, and track people, vehicles, objects, and behaviors in real time. By replacing manual monitoring with automated insights, AI-powered video analytics significantly improves accuracy, speed, and operational efficiency across multiple sectors.

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Market Scope and Research Coverage

This report delivers an in-depth assessment of the global AI in video analytics market, covering market size trends, drivers, restraints, opportunities, segmentation, regional performance, and competitive strategies. Historical data from 2018–2023 and forecast analysis through 2030 are supported by structured analytical frameworks, including PORTER, SWOT, and PESTEL analysis.

The study is designed to support technology vendors, system integrators, government agencies, investors, and enterprise decision-makers seeking a clear understanding of the evolving video analytics ecosystem.

AI in Video Analytics Market Dynamics

Key Market Drivers

Rising Volume of Video Data and Surveillance Expansion

The widespread deployment of surveillance cameras across public and private spaces has led to an exponential increase in video data generation. Security operators and investigators are often required to monitor thousands of hours of footage, making manual analysis inefficient and prone to human error.

AI-based video analytics systems address this challenge by processing vast datasets in real time, enabling faster detection of incidents, improved situational awareness, and reduced reliance on human monitoring. The growing affordability of IP cameras and the expansion of high-speed internet connectivity further accelerate market adoption.

Government Adoption for Public Safety and Smart Infrastructure

Governments worldwide are increasingly deploying AI-driven video analytics for traffic monitoring, public safety, and critical infrastructure protection. Smart city initiatives leverage intelligent video surveillance to manage congestion, enhance law enforcement capabilities, and improve emergency response.

Applications such as facial recognition, anomaly detection, auto-tracking, and crowd behavior analysis are becoming integral to urban security frameworks, driving sustained demand for AI-powered video analytics solutions.

Market Opportunities

Strategic Partnerships and Technology Integration

The market is witnessing active collaboration among hardware manufacturers, AI software providers, and cloud infrastructure companies. Business strategies including partnerships, mergers, acquisitions, and global expansions are creating new revenue opportunities and accelerating technology adoption.

AI-based solutions now offer advanced capabilities such as emotion recognition, wide-area surveillance, and predictive threat detection, opening new use cases across commercial, industrial, and residential environments.

Market Restraints

High Deployment Costs and Data Privacy Concerns

Despite strong growth potential, the market faces challenges related to the high cost of system installation, including surveillance hardware, servers, storage infrastructure, and data management platforms. Additionally, rising concerns around data privacy, cybersecurity, and ethical use of facial recognition technologies may limit adoption in highly regulated regions unless compliance frameworks are strengthened.

AI in Video Analytics Market Segment Analysis

By Component

• Hardware
• Software
• Services

Software solutions dominate the market due to their ability to integrate AI algorithms, deep learning models, and analytics platforms that extract actionable insights from raw video feeds.

By Integration

• Edge-Based Solutions (Dominant in 2023)
• Server-Based Solutions
• Hybrid Solutions

Edge-based solutions led the market in 2023 due to their ability to process data locally, significantly reducing latency and bandwidth requirements. A substantial share of video analytics workloads is now executed at the edge, enabling real-time decision-making in critical applications such as traffic control and perimeter security.

Edge devices can analyze most video data on-site, enhancing response times and improving privacy by limiting data transmission to centralized servers. Leading companies are embedding advanced AI capabilities directly into cameras and edge devices, offering high performance with low power consumption.

By Organization Size

• Small and Medium Enterprises (SMEs)
• Large Enterprises

By Industry Vertical

• Banking, Financial Services, and Insurance (BFSI)
• Retail
• Government and Public Sector
• Healthcare
• Transportation and Logistics
• Manufacturing
• Others

The government and public sector segment remains a major contributor due to large-scale surveillance deployments, while retail and transportation sectors are rapidly adopting AI video analytics to improve loss prevention, customer insights, and operational efficiency.

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Regional Analysis

North America

North America dominated the global AI in video analytics market in 2023, supported by advanced digital infrastructure, strong AI research ecosystems, and high enterprise adoption rates. The region has made significant investments in deep learning–based video analytics for public safety, smart cities, and commercial security applications.

The deployment of AI-enhanced surveillance systems across major metropolitan areas reflects a strong emphasis on real-time analytics, ethical AI development, and regulatory compliance, positioning North America as a global technology leader.

Asia Pacific

Asia Pacific is expected to witness the fastest growth over the forecast period, driven by rapid urbanization, expanding smart city projects, increasing public safety investments, and growing adoption across manufacturing and transportation sectors.

Europe, Middle East & Africa, and South America

These regions are steadily adopting AI-powered video analytics to modernize infrastructure, enhance border security, and improve operational efficiency across public and private sectors.

Competitive Landscape

The global AI in video analytics market is highly competitive, with players focusing on AI innovation, edge computing integration, geographic expansion, and strategic alliances.

Key Market Players Include:

• IBM
• Intel Corporation
• Cisco Systems, Inc.
• Hikvision
• Dahua Technology
• Avigilon
• Axis Communications
• Hanwha Techwin
• BriefCam
• VIVOTEK
• IntelliVision Technologies
• Verint Systems
• Verkada
• i2v Systems
• Bosch Security Systems
• NICE Systems
• Honeywell International
• ObjectVideo Labs, LLC
• Viseum International Limited
• Pro-Vigil, Inc.

Key Questions Answered in the Report

• What is the current and projected size of the AI in video analytics market?
• Which integration models are driving real-time analytics adoption?
• How are governments and enterprises leveraging AI for surveillance and safety?
• What are the major regional growth opportunities?
• Who are the leading market players and what strategies are shaping competition?

Conclusion

The Global AI in Video Analytics Market is positioned for exceptional growth as organizations seek smarter, faster, and more secure ways to interpret video data. Advances in edge computing, deep learning, and real-time analytics are redefining surveillance and operational intelligence across industries. With expanding applications in public safety, transportation, retail, and smart infrastructure, AI-powered video analytics is set to become a foundational technology in the global digital ecosystem through 2030.