AI Revolution in Physical Security: Navigating Innovation, Intelligence, and Governance

Security 50, 2025

The physical security industry is experiencing a fundamental transformation as artificial intelligence, cloud computing, and IoT technologies converge to create intelligent, interconnected networks.

By: Tommy Zhu, Principal Analyst, Physical Security, Omdia

According to Omdia’s 2025 Video Surveillance & Analytics Report, the global video surveillance market, valued at $25.9 billion in 2024, is projected to reach $37.1 billion by 2029 with a 7.5% CAGR, driven by AI integration and intelligent analytics adoption. This evolution represents more than technological advancement—it signals a paradigm shift from traditional reactive monitoring to proactive, intelligent security operations.

Four interconnected forces are reshaping the security landscape: intelligent AI systems, edge computing proliferation, evolving governance frameworks, and cybersecurity imperatives. Each element builds upon the others, creating a comprehensive transformation that demands strategic coordination.

Four factors are shaping the new security reality: advanced AI systems, edge proliferation, regulatory governance, and cybersecurity imperatives.

Generative and Agentic AI: The Intelligence Revolution

The integration of generative AI and agentic AI systems is fundamentally reshaping video surveillance operations, enabling a shift from reactive response to proactive decision-making. Modern AI-powered systems leverage vision-language models (VLMs) trained on image/video-text pairs, creating sophisticated understanding capabilities that surpass traditional computer vision approaches. The large models used in the video surveillance systems offer several key advantages.

AI systems now distinguish between suspicious loitering and casual waiting, providing nuanced scene interpretation that reduces false alarms while improving threat detection accuracy. Foundation models enable rapid fine-tuning for scenario-specific applications, allowing organizations to quickly adapt security systems to emerging threats and operational requirements. Modern systems can monitor passenger and vehicle flows in urban transport, detect rule violations automatically, and identify suspicious patterns through intelligent analytics, transforming security from passive recording to active threat prevention.

Edge AI Proliferation: Distributed Intelligence Architecture

As these intelligent systems become more sophisticated and capable, they require substantial computational resources that traditional centralized architectures cannot support efficiently. The computational demands of advanced AI systems have catalyzed a fundamental shift toward edge processing, with 61% of all camera shipments expected to be AI cameras by 2029, according to Omdia’s research.

This proliferation is enabled by advanced computer vision models and compression technologies, including knowledge distillation, which allows large AI models to operate efficiently on resource-constrained edge devices. With the integration of multiple sensors and data sources, modern AI-enabled video cameras can create comprehensive situational awareness. Edge AI deployment transforms security networks from centralized monitoring systems into intelligent, autonomous networks capable of independent decision-making and coordinated response.

Global AI Governance: Regulatory Framework Evolution

As AI-powered security systems become more pervasive and autonomous, their potential impact on society grows exponentially. This expanding influence has prompted governments worldwide to develop comprehensive regulatory frameworks to ensure responsible AI deployment while fostering continued innovation. The passage of the EU’s AI Act in August 2024 represents a watershed moment in AI governance, establishing comprehensive regulatory frameworks that influence global security industry practices. This legislation creates clear boundaries for acceptable AI applications while promoting responsible innovation, which directly addresses concerns raised by the proliferation of intelligent surveillance systems. The AI Act explicitly prohibits untargeted scraping of facial images from CCTV footage, emotion recognition in workplaces and schools, and predictive policing based solely on profiling—setting global precedents for ethical AI deployment. The regulatory frameworks provide structured guidance for ethical AI implementation while addressing cross-border data compliance challenges, creating both constraints and opportunities for innovation. 

Cybersecurity and Privacy: The Security Paradox

While regulatory frameworks establish the boundaries for responsible AI deployment, they also highlight a critical challenge: the expanded attack surfaces and cybersecurity risks created by intelligent, interconnected security systems. The same technologies that enable proactive threat detection can also create new vulnerabilities that must be systematically addressed. AI-enabled video surveillance system backends host massive amounts of private and confidential metadata, making them attractive targets for cybercriminals while subjecting organizations to significant regulatory penalties—GDPR violations can result in fines up to 4% of annual global turnover or €20 million.

With growing concerns over cyber-physical security, new legislations are expected to commence and come into force in the next few years, such as the EU’s Cyber Resilience Act (CRA), which requires “secure by design” and “secure by default” implementations. Navigating the evolving regulatory and compliance landscape is becoming critical to the security industry.

Orchestrating Transformation

The convergence of AI intelligence, edge proliferation, regulatory governance, and cybersecurity imperatives is creating an interconnected ecosystem that promises unprecedented security capabilities while introducing complex management challenges. Success in today’s transformed landscape requires organizations to adopt a holistic orchestration approach that seamlessly integrates multiple elements. This includes advanced AI capabilities that enable proactive threat detection while adhering to regulatory requirements, distributed edge intelligence that processes data locally without compromising cybersecurity, comprehensive compliance frameworks to support ethical AI deployment across jurisdictions, and robust cybersecurity measures that safeguard AI models, edge devices, and sensitive data simultaneously. Organizations that successfully orchestrate this complex transformation will define the future of intelligent physical security and capture the significant growth opportunities in this rapidly evolving market.