Beyond Surveillance: How AI-Driven Video Technology is Transforming Security and Business Intelligence

With the early days of 2025 just beginning, video surveillance technology and all it encompasses celebrates approximately 83 years of innovation and evolution.  This marks a crucial point in its history where video systems will evolve into business intelligence systems.  In the early days, video systems were rudimentary and fundamental in technology, generally black and white cameras connected to monitors via coaxial cables.  Today, cameras are being used for safety and security in cities, buildings, and schools and are being leveraged for business intelligence capabilities in Retail and Entertainment.

Traditionally, video relied on human monitoring for threat detection. AI-driven analytics now provides real-time, automated insights. Algorithms can analyze large volumes of video data to identify anomalies and potential threats humans might miss. By harnessing AI, security teams can respond proactively, reducing response times and enhancing overall safety. It’s time to leverage AI to extend security and business capabilities and unlock new opportunities. 

AI-Driven Video Technology

We have discussed video analytics advancements for years. Have you evaluated how to use analytics to extend your organization's value with proactive monitoring and predictive capabilities? Basic analytics often come with cameras, but many integrators haven't used advanced features yet. Now is the time for integrators to review offerings, assess partners and vendors, and build an advanced customer roadmap. Practitioners should assess their ecosystem, use cases, and business impact and establish roadmaps and incubation programs to maximize organizational impact.

AI video analytics are expected to grow beyond $52B by 2032, with a CAGR of 22.7% from 2024 to 2032. Video is now the main workload at the edge, enabling scene analysis, object detection, tracking, classification, identification, 3D depth, and navigation. This capability presents new security opportunities. 

According to the 2025 Security Industry Association Megatrends Report, “Of the estimated 90 million cameras installed globally, very few use AI, but that is changing. If you further divide those 90 million cameras, a low percentage will use standard analytics (be that in the camera or the video management system (VMS)), and even fewer will use what you might call “real AI.” Most existing security cameras still function as simple scene-recording devices and do not yet provide the “visual intelligence” that this trend conveys. But all of that is about to change. Practitioners today are looking at their video surveillance investments as tools to provide visual oversights of their operations, and that makes this trend inherently connected to 2025 Megatrend No. 3, the undervaluation of security. 

After all, if your security cameras are no longer “video surveillance” but provide “visual intelligence,” those systems are worth more to the business. Of course, providing these additional values requires AI or at least “analytics,” creating a vast opportunity for video product makers, VMS vendors and systems integrators.   As practitioners build their technology roadmap and add-on capabilities, understanding key analytics functions they can leverage today will benefit their organization.

Visual Language Models will soon surpass traditional video analytics. Integrating computer vision and natural language processing will transform how we understand and interpret visual content. 

What AI Offers

AI enhances new security capabilities and introduces unprecedented operational functions. Understanding how AI can improve prevention, prediction, and response is essential. Agentic AI automates decision-making, while Explainable AI offers transparency in AI decisions. These technologies transform physical security by enabling proactive measures, enhancing situational awareness, and streamlining operations. Agentic AI autonomously detects and responds to threats, reducing response times and mitigating risks. Explainable AI ensures clarity and understanding of AI decisions, fostering trust and aiding human interpretation. Together, they enhance security and optimize operational efficiency.

AI can now use Explainable AI with Retrieval-Augmented Generation (RAG) to quickly provide security teams with security manuals, training, and operations data. 

Manufacturers can use Explainable AI with RAG to quickly provide product information for integrators and customers, improving training, product specs, and RFP responses. This method is more accurate and reduces the risk of errors compared to mainstream GenAI.

Technology Challenges

As we advance technologically, we must acknowledge the accompanying challenges. Many organizations still depend on outdated systems that can't integrate with modern software, resulting in disconnected systems. Moreover, completely replacing old devices isn't always practical for creating the infrastructure needed for edge AI.

Using cloud-based AI platforms allows access to powerful AI algorithms with a pay-as-you-go model, eliminating the need for on-prem hardware or software. This reduces upfront costs and offers scalability, enabling organizations to adjust their AI capabilities as needed. Financially, using the cloud diversifies budget and spending compared to traditional capex approaches.

Cloud-based video surveillance platforms offer advantages over traditional on-prem systems, such as scalability, flexibility, and cost-effectiveness. They can adjust to changing security needs, making them ideal for dynamic organizations. Additionally, they allow access to video footage and analytics from anywhere. Combining on-prem and cloud capabilities provides a flexible and diverse return on security investment. Prioritizing security and data privacy is essential, so choose a cloud provider with strong encryption, access control, and compliance certifications.

Assessing risks and threats is crucial as we enter a new era of physical security and access control. The line between physical and cybersecurity is blurring with the rise of IoT devices. This convergence challenges security leaders and addresses shared concerns like surveillance, defense, risk management, and access control. With AI integrating into every sector, protecting devices and information is vital. As threats evolve, bad actors exploit AI for cyber espionage, phishing, social engineering, and deepfakes. 

According to Antoinette King, Founder of Credo Cyber Consulting LLC, “Security professionals have a great responsibility to protect the large stores of live and recorded video surveillance footage, as well as access control data, that customers process from bad actors. Utilizing generative AI technology, bad actors can create deepfakes and target individuals and organizations; they can create digital twins of facilities to pursue kinetic attacks, and with access to access control systems, they can manipulate electronic locks and card access privileges. For years, security professionals could not conceive of how the data stored by the deployed systems could be useful to bad actors. Now, with the advancements in artificial intelligence, the price of admission to commit cyber-attacks and data breaches is much lower.”

Recent studies indicate that deepfakes have been doubling every six months since 2018, highlighting the rapid advancement and accessibility of this technology. This rise poses significant challenges for physical security teams as AI-generated deepfakes become more convincing and more challenging to detect. Organizations must prioritize advanced detection and mitigation strategies, including data encryption, zero trust access, enhanced network security, AI-powered real-time detection, securing all components, and adjusting data retention policies. Crucially, employee training on new threats is essential.

Developing Strategic Plans

Developing comprehensive security strategies allows for integrating processes, teams, and technology. Investments should be increased to improve network security and secure device management, and extensive threat intelligence capabilities should be added to safeguard physical systems from cyber-attacks.

The future of a converged security organization lies in maximizing security investment returns and reducing risk. This involves using AI-powered systems for threat detection and response across physical and cyber domains, automating incident responses, and establishing unified security information and event management systems. A resilient, holistic security program that integrates both physical and cybersecurity principles is essential.

The future of security is promising. Significant opportunities exist to modernize security approaches, develop roadmaps for advanced technology usage responsibly, and create positive business impacts. Stakeholders in the security ecosystem play a crucial role in this transformation:  

·         Technology Providers: Develop actual innovative security products with outcomes in mind that leverage AI and other emerging technologies to address evolving threats.

·         Integrators: Enhance capabilities to implement and manage increasingly sophisticated AI-driven security solutions, bridging the gap between advanced technology and practical application.

Gary Hoffner, Vice President of National Integrator PSLA, states, "AI has revolutionized how we engage with our customers and prospects.  The discussion no longer resides within the guardrails of manufacturers' imposed technical limitations.  Our offerings have always been about providing solutions, but the boundaries have expanded immensely with AI, and the dialogue with customers has evolved to provide innovative solutions specific to customer problems that “out-of-the-box analytics” cannot solve.”

·         Practitioners: Embrace holistic approaches to security that align with broader business goals, recognizing security as a value driver rather than a cost center. Upskill security teams to meet the demands of an AI-enabled security organization, becoming proficient at interpreting AI-generated insights and making informed decisions.

Tim Wenzel, Associated Managing Director at Kroll, states that modern security leaders must be involved in corporate governance and security policies to ensure transparency and gain support. Well-governed security organizations align with business value, and AI can enhance this alignment, benefiting both security and non-security stakeholders.

·         Industry Leaders: Guide the development of best practices and standards to ensure AI's responsible and ethical use in security applications.

By adopting forward-thinking strategies, the security industry can elevate its value proposition, moving beyond traditional notions of protection to become key enablers of business success and innovation. The growth of synergies between security expertise, business acumen, and advanced technology capabilities will define the modern security organization of 2025 and beyond.