AI In Video Surveillance Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

Global AI In Video Surveillance Market Trends and Insights

Growing demand for integrated AI-powered security analytics

• Municipal programmes increasingly embed analytics that link surveillance feeds to traffic control, emergency dispatch, and infrastructure diagnostics. Pilot deployments in Virginia demonstrate real-time detection of anomalous public-space behaviour, improving incident response and resource allocation^{[1]Tech-Xplore Staff, “SMAST system raises bar for real-time behaviour detection,” techxplore.com}. European towns such as Las Rozas use smart cameras to quantify pedestrian density for urban-planning decisions. These multipurpose systems justify higher capital budgets because one installation serves safety, mobility, and planning mandates simultaneously. New procurement records show municipal purchases for robotic patrol devices and AI-enabled licence-plate readers exceeding USD 465,000 across New York and Missouri in 2024. Budget efficiencies and data-driven governance objectives therefore reinforce analytics adoption within the AI in video surveillance market.

Rapid deployment of smart-city surveillance infrastructures

Government stimulus in emerging economies is standardizing AI-ready CCTV networks as foundational digital infrastructure. Saudi Arabia’s localization of surveillance equipment manufacturing through partnerships with Chinese suppliers reflects a policy focus on domestic value creation. Across the Gulf, mandatory camera installation regulations underpin a 6.2% regional surveillance CAGR to 2025. China’s “Skynet 2.0” even extends camera-based situational monitoring to lunar exploration programs, highlighting the scale of state-backed investment. South Korea plans a nationwide migration to AI-enabled CCTV by 2026, locking in supplier certification requirements that guarantee a pipeline of public contracts. These programs both expand immediate hardware volumes and set technical standards that shape the global AI in video surveillance market.

Declining cost and power of edge-AI chipsets

New video-centric system-on-chips deliver multi-model inference inside the camera body, cutting network load and latency. Ambarella’s CV72S doubles concurrent AI model throughput versus its predecessor while lowering power draw. Qualcomm’s industrial IoT reference designs bundle on-device analytics with secure connectivity for enterprise roll-outs. Such silicon advances put high-accuracy object detection within reach of small businesses, broadening the total addressable market. They also enable large campuses to offload computation from data centres, shrinking recurring cloud spend. As forecast by semiconductor vendors, energy-efficient accelerators will catalyse new use cases across 2025, especially video-heavy security workloads.

Expansion of VSaaS lowering adoption barriers

Fifteen years of VSaaS evolution show how improvements in broadband, browser protocols, and 5G have eliminated the frame-rate and latency issues that once limited cloud surveillance[3]. The 2025 merger of Milestone Systems and Arcules illustrates the convergence of mature video-management software with native cloud architecture, giving mid-market users enterprise-grade analytics without infrastructure overhead. Subscription pricing, automatic feature updates, and elastic storage appeal to residential and small commercial buyers. The model also lets vendors introduce AI upgrades without touching customer-site hardware, accelerating the feature refresh cycle across the AI in video surveillance market.

Escalating privacy and ethical regulation on biometric analytics

The EU AI Act imposes strict approval thresholds for remote facial recognition in public areas, limiting deployments to narrowly defined law-enforcement exceptions with judicial oversight. Additional clauses restrict emotion detection in workplaces and schools, prompting vendors to rethink product road maps. Because the regulation has extraterritorial scope, suppliers worldwide must validate compliance before selling into Europe, inflating certification costs and elongating the sales cycle. While top-ranked algorithm vendors such as IDEMIA meet accuracy and bias thresholds, many municipal buyers still prefer behaviour-based analytics that avoid biometric data capture. Regulatory uncertainty, therefore, suppresses near-term demand for facial-recognition modules inside the AI in the video surveillance market.

Cyber-security vulnerabilities in IP surveillance networks

Recurring disclosures of exploitable firmware gaps in network cameras undermine buyer confidence. A 2024 CISA advisory flagged actively weaponized Dahua flaws that persisted since 2021, underscoring patch-management challenges. Researchers similarly showed how unpatched Edimax devices could join Mirai botnets and launch volumetric attacks. These incidents drive stricter procurement criteria that demand end-to-end encryption, auto-update pipelines, and zero-trust architecture. Organizations often defer or resize projects until vendors demonstrate hardened cyber postures, trimming short-term equipment orders inside the AI in video surveillance market.

Segment Analysis

By Component: Software Intelligence Drives Value Migration

Hardware preserved 56.8% of 2024 revenue because cameras, recorders, and network gear remain physical prerequisites, yet the software segment is on track for an 18.20% CAGR to 2030, reflecting a decisive shift toward algorithm-centric value. All major video-management platforms have embedded real-time analytics, automated event triage, and cloud connectors, features that command service-subscription premiums. Industry demonstrations by IronYun, NVIDIA, and Verkada illustrate how generative models can classify complex behaviours in milliseconds, elevating software differentiation.

Hardware road-maps increasingly integrate deep-learning accelerators on the PCB, creating edge devices that execute detection and classification locally. Vendors such as Hikvision combine visible-light, thermal, and radar modules inside a single enclosure, freeing central servers for forensic analytics rather than basic object recognition. Services revenue, though smallest today, scales with the number of AI deployments that require model tuning, cyber-security audits, and regulatory documentation. Thus, software, services, and intelligent hardware form a mutually reinforcing stack that should lift the AI in video surveillance market over the forecast horizon.

Note: Segment shares of all individual segments available upon report purchase

By Deployment Model: Cloud Acceleration Reshapes Architecture

On-premises video storage and processing still hold 65.1% of the AI in video surveillance market share, yet cloud and hybrid configurations register the fastest expansion at 22.50% CAGR. Corporate adopters increasingly separate latency-critical inference at the edge from compute-intensive analytics in the cloud, an architecture that balances bandwidth, sovereignty, and cost. Smaller organisations migrate fully to VSaaS to avoid capital outlays, while campus-scale users adopt gateway appliances that forward selected metadata to central clouds for pattern mining.

Early concerns about real-time streaming quality have largely dissipated as 5G roll-outs and HTML5 improvements provide consistent throughput. Cloud providers release quarterly AI feature packs, offering anomaly detection, licence-plate recognition, and occupancy analytics without hardware swaps. This cadence materially shortens innovation cycles, making VSaaS the preferred growth engine for the AI in video surveillance market.

By End-user: Residential Surge Transforms Market Dynamics

Commercial sites—office parks, retail malls, and hospitality venues—delivered 43.5% of 2024 revenue. However, residential uptake, propelled by smart-home platforms and lower device prices, is projected to rise at 15.40% CAGR. Video doorbells and affordable Wi-Fi cameras now rank among the top two connected-home devices in ownership surveys, reflecting consumer confidence in DIY security systems.

Military and defence operators continue to buy ruggedized, specialized optics, while government agencies finance expansive citywide networks that integrate traffic, public-safety, and environmental sensors. Industrial facilities emphasize fail-safe design and cyber hardening. These diverse requirements sustain a broad solution mix, yet residential momentum is shifting volume leadership within the AI in video surveillance market.

By Application: Biometric Analytics Accelerates Despite Regulatory Headwinds

Perimeter-intrusion detection commanded 28.3% of 2024 sales because fence-line monitoring remains the first layer of defence for facilities. Facial-recognition and biometric modules, already delivering 98.39% accuracy in controlled conditions, are set for a 24.30% CAGR through 2030. Traffic and crowd analytics aid urban planning and emergency evacuation, while retail chains deploy heat-maps and path tracking to sharpen merchandising.

Machine-learning-based anomaly detection is the fastest-maturing use case. Research prototypes such as AnomalyRuler demonstrate how large language models can explain detection logic, boosting operator trust in alerts. Integrated AI suites that bundle multiple applications in one licence give buyers a single pane of glass and accelerate cross-function budget approval, adding resilience to the AI in video surveillance market.

Note: Segment shares of all individual segments available upon report purchase

By Camera Type: Multi-Sensor Integration Defines Next Generation

Recent product launches showcase cameras that blend optical, thermal, radar, and acoustic inputs, processed by on-board AI accelerators. Hikvision’s AIoT concept pairs 5G connectivity with multi-spectral sensors to create scenario-based digital twins of monitored assets. Similar designs from MileSight stream real-time traffic data to cloud dashboards with sub-second latency.

Academic work on sensor fusion for autonomous vehicles informs algorithm design for surveillance, underscoring how cross-disciplinary innovation benefits the AI in video surveillance market. Compression schemes that leverage coordinate-based neural nets also reduce storage requirements for UHD feeds, allowing longer retention without disproportionate cost increases.

Geography Analysis

Asia-Pacific held 36.9% of global revenue in 2024, fueled by China’s massive urban-camera grid and regional smart-city programs. Skynet expansion to lunar research illustrates the ambition and public funding mobilized for surveillance infrastructure. South Korean mandates to retrofit all public CCTV with AI by 2026 imply at least 20% annual spending lifts in that country. Japan and India add further weight through railway, airport, and urban-renewal projects, while ASEAN municipalities apply surveillance data to flood management and public-health monitoring.

North America remains the technology innovation hub, with federal research on autonomous multi-camera tracking and city budgets that finance robotic patrol units. Canadian border agencies expand AI video analytics to improve throughput at land crossings, and Mexican megacities install integrated command centers that coordinate traffic lights with predictive crime mapping. Venture funding flows to AI-native startups, reflecting market confidence in software-led growth inside the AI in video surveillance market.

The Middle East is on course for a 13.80% CAGR to 2030, anchored by Gulf smart-city visions that bundle surveillance with IoT-based public-service delivery. Mandatory camera regulations, easy access to capital, and public-sector backing accelerate adoption. Saudi Arabia’s plan to co-manufacture cameras domestically through Dahua tie-ups signals an appetite for local value capture. Despite privacy debates, large-scale deployments continue as governments prioritize security and urban optimization objectives.