The Intelligence Shift: Emerging AI Trends Shaping the Future of VSaaS 

We are currently living through the largest technological shift of human productivity in history: artificial intelligence (AI). AI isn’t just a new tool; it’s a fundamental change in how knowledge is distributed and, therefore, how work is accomplished.

This shift builds upon a history of innovation. It began with the printing press, which enabled the widespread physical distribution of static information (books, newspapers). Next came the internet, where information became dynamic, capable of changing instantly, and was delivered digitally. Now, we have Generative AI, which transforms the landscape again by allowing information to be generated and delivered simultaneously while also being hyper personalized, if needed.

AI is reshaping how organizations operate, not by increasing access to information, but by changing how insight is generated and applied. This shift is reaching every industry, including video surveillance, where expectations for awareness and responsiveness are rising. In this article, we examine how AI is impacting industries broadly, how those changes are influencing the video surveillance market, and how OpenEye is innovating with AI in a way that is ethical and future ready.

Why Today’s AI Shift is Unique

A popular phrase right now is that AI is currently the smartest it has ever been, yet the dumbest it will ever be. The technology is rapidly innovating, as well as becoming less resource intensive. Compared to just two years ago, the cost of deploying AI capabilities has dropped by roughly 90%, dramatically lowering the barrier to moving AI from experimentation into everyday operations.

What distinguishes this moment is not just improvement, but compression. Capabilities that once unfolded over decades are now advancing in years or months, leaving less time for gradual adoption. The shift we see happening today is occurring far too rapidly to merely be a “future” conversation. AI is reshaping how products are built and how careers evolve. Over the next five years, the surveillance industry is likely to continue shifting to meet these advancing trends, changing the organizational processes we’re used to, and the roles responsible for these workflows.

Moving From Video That Records to Intelligent Surveillance That Acts

The impact AI is having on the surveillance industry has undergone similar rapid development. AI has gone from simple Perceptive AI (the system seeing something) to Generative AI (systems that create and compare content) to Agentic AI (the system doing something requiring autonomy and reasoning) in just the past few years alone.

As security systems gain agentic capabilities to take digital and, perhaps in the future, even physical action, the defining question becomes less about what the system can see and more about what it is authorized to do. This elevates surveillance from a technical deployment to an operational design challenge, one that requires clear escalation paths, accountability, and trust in how decisions are made.

What this means practically is that video security systems are moving from “video that records” to “intelligence that acts,” turning surveillance into a source of measurable business value and giving organizations better operational insights from their video security system. This achieves a greater return on investment, as surveillance is no longer limited to a reactive security tool, but instead a proactive solution capable of delivering actionable intelligence.

When equipped with an AI‑powered video surveillance platform, surveillance systems move beyond simple alerting to structured decision‑making.

Activity can be initially assessed at the perimeter using intelligent motion detection to identify only the events that warrant attention. For lower‑risk activity, the system can respond immediately through automated active deterrence, such as activating white light or delivering a pre‑recorded audio message, often resolving the situation before human involvement is required.

Only when activity persists or meets defined escalation criteria is the event routed to a command center or security team for review and response. By filtering and addressing routine incidents automatically, organizations reduce unnecessary escalations, shorten response times for true priority events, and lower the operational cost of security without compromising protection.

The Look Back: From Recording to Intelligence

2025 was a pivotal year in video security. When an event occurs, the question shifted from “Did you record it?” to, “What action did our solution take?” As AI delivers timely insight in other parts of the organization, delays in awareness become more visible, and less acceptable. Video systems are increasingly judged not by what they capture, but by how effectively they reduce uncertainty in the moment it matters.

This transition exposed a clear divide between legacy systems and AI-native, hybrid architectures that balance the heavy lifting of edge processing with the global scale of the cloud.

At OpenEye, we met this shift by moving beyond basic detection toward individual and situational awareness, streamlining our platform to prioritize “time-to-insight” and ensuring our software is as adaptable to future AI agents as it is to our users today.

Below, we examine how AI has evolved over the past year, where the surveillance industry currently stands, and how OpenEye has evolved alongside AI.

The Technological Leaps of the Past Year

2025 marked a clear inflection point for artificial intelligence. AI moved from impressive demonstrations to an indispensable strategic enabler. Models became more accurate, more efficient, and more reliable in real‑world conditions. As a result, AI shifted from an experimental capability to operational infrastructure: no longer just a tool that responds, but a system capable of observing, analyzing, and acting within clearly defined, human‑led guardrails.

At the same time, the underlying architecture supporting AI matured. Cloud adoption accelerated, making advanced AI capabilities more accessible and scalable across organizations. For the surveillance industry, growing cloud capabilities unlock new flexibility, enabling faster response times, reduced bandwidth demands, and solutions tailored to the unique needs of each deployment.

This technological advancement also changed how organizations interact with AI. As AI systems became more capable, the limiting factor was no longer the technology itself, but the ability to guide and operationalize it effectively.

In 2025, demand surged for AI‑literate professionals and domain experts who understand how to direct AI, interpret its outputs, and integrate it into existing workflows. Rather than replacing expertise, AI began amplifying it, especially in industries like video security, where context, judgment, and accountability remain essential.

Together, these shifts laid the groundwork for what we now see across surveillance: systems that don’t just capture footage but actively contribute to operational awareness and decision‑making.

As AI capabilities stabilize, the limiting factor shifts away from model performance and toward orchestration, how insights are routed, contextualized, and acted upon. In this environment, competitive advantage is less about having access to AI and more about integrating it cleanly into real‑world workflows.

Where the Surveillance Industry Stands Today

AI has created a paradigm shift in the surveillance industry, moving surveillance solutions from “security only” video to systems that offer operational value. This is reshaping how many businesses are looking at their security teams; as other industries are leveraging AI insight combined with domain experts, security professionals are seeking to leverage foundational surveillance architecture enhanced through AI to optimize their business.

Remote Video Monitoring (RVM)

AI wasn’t the only major innovation happening in surveillance technology. Remote Video Monitoring (RVM) is another key trend on the rise, helping ensure the events that matter most reach security operators while reducing false alarms. This evolution reflects a broader reallocation of human effort. As AI handles volume and verification, human operators increasingly focus on judgment, coordination, and exception handling. The value of surveillance teams is no longer measured by how much they watch, but by how effectively they respond. With RVM, skilled remote operators are now interpreting what’s happening, informing the business, then making key security decisions to improve response times.

What’s changed is not the availability of video, but the cost of human attention. As AI reduces false positives and pre‑filters events, the bottleneck naturally shifts from monitoring capacity to decision quality. This shift is prompting organizations to rethink workflows so that increasing volumes of insight translate into faster, more effective responses, not just more data to review.

Video Surveillance as a Service (VSaaS)

Additionally, video surveillance as a service (VSaaS) and subscription-based models represent a shift in how organizations approach long-term security planning. Traditional surveillance systems are often deployed as fixed assets, with limited ability to adapt as operational needs, threats, and technologies change. VSaaS offers an alternative approach, designed to evolve over time through software-driven improvements, flexible scaling, and ongoing service delivery, positioning video surveillance as an ongoing investment rather than a static, one-time purchase.

Interoperable Solutions

Finally, interoperable solutions continue to help customers connect disparate data within a single cloud-based platform. Integrating access control, point-of-sale, environmental sensors, and other security and business systems with video surveillance uncovers fresh insights thanks to additional visibility into these events. Powered by AI, these events become a tangible measure of actionable data that can be leveraged to improve operations.

A Retrospective on OpenEye’s Ongoing AI Strategy

As both AI and the surveillance industry as a whole saw increased innovation in recent years, OpenEye continued to advance the OpenEye Web Services (OWS) cloud-managed video security platform. Solutions were designed with active intelligence in mind, building AI-powered surveillance technologies that go beyond passive recording. These innovations are built from within the core of the platform. AI video analytics, alongside other enhancements to OWS, are native capabilities, designed as part of the system rather than added later.

As many businesses are seeking to deploy AI effectively throughout their organization, OpenEye ensures users are provided with easy-to-use, scalable solutions that make deployment of AI smoother. In that spirit, the OpenEye architecture is designed as an easy on ramp to both cloud capabilities and the innovations of AI.

The Look Forward: The Era of the AI Teammate

We are entering the era of “Agentic AI,” where technology moves from a tool you operate to a teammate that cooperates. AI agents are autonomous software systems that use AI models to perceive, reason, plan, and take actions to achieve specific goals with minimal human oversight. Unlike standard generative AI that responds to immediate prompts, agents operate in loops to execute complex, multi-step tasks, use external tools, and learn from outcomes.

The coming years will be defined by agency and comprehension as AI takes on proactive roles, such as performing visual compliance checks, monitoring site conditions, and escalating intelligently, with necessary human-in-the-loop design to ensure quality output. Through generative search, video-based alarming, and natural language interfaces, AI is transforming security infrastructure into a core operational asset, providing solutions built on trust that augment teamwork.

Agentic AI Becomes Operational

We expect to see Agentic AI become more widely operational, proactive, and available as a teammate. Humans will move into higher-leverage roles, partnering with AI so they can focus on oversight, strategy, exception handling, and managing multiple AI agents.

One example of how this technology can be leveraged is by using an AI agent to monitor a secure entry. The combination of a badge event and person detection triggers an agentic check, powered by a Vision Language Model (VLM) and Large Language Model (LLM) reasoning capabilities. When the employee badges in but holds the door for an unbadged person in a delivery uniform, the system utilizes visual reasoning to identify a “social engineering” risk rather than simple tailgating. The agent then immediately executes a containment workflow, such as querying the Visitor Management System to verify if a delivery is scheduled or dispatch a guard while automatically logging the policy breach in the employee’s compliance file.

Another example could be an AI agent performing a facilities audit at 8:00 a.m. daily instead of a regional manager physically visiting a store to check compliance. Using VLM and referencing the company’s SOP for store opening, the agent would visually inspect the store to confirm that promotional signage is correct, key safety equipment like mats are out, shelves are stocked, and staff are wearing the current season’s uniforms.

If the agent identifies a discrepancy (for example, a missing promotional display), it doesn’t just flag a video clip. It acts by automatically emailing the manager and merchandising team with a snapshot of the empty floor space. The workflow closes only when the AI visually verifies the sign has been placed.

With the anticipated widespread adoption of AI agents, end user businesses will not be the only ones affected. To stay competitive, the companies developing AI-powered products will need to increasingly demonstrate how intelligent they are, how quickly they deliver insight, and how easy they are to use. 

AI, AI, AI: The Future of the Surveillance Industry

As it has done over the past several years, AI will continue to revolutionize video security. Due to increased interest in AI capabilities and funding towards these initiatives, new features will become available on an even wider scale than before from all products leveraging AI, making solutions more powerful while increasing intuitiveness and simplifying usage.

Cloud Processing and Video-Surveillance-as-an-Alarm

Alongside developments to video analytics, cloud processing and storage applications and options should increase, as well as video-surveillance-as-an-alarm becoming more mainstream. Each of these innovations signal great flexibility for organizations in how they’re leveraging their surveillance, creating greater drive to adopt them.

Cloud storage applications highlight the increasing shift from on-premises recording hardware to recording done entirely in the cloud. This offers many businesses greater convenience in how they deploy and scale their solution across multiple locations and new builds. Video-surveillance-as-an-alarm enhances existing alarm panels by leveraging the video surveillance solution as an additional alarm solution, providing visibility into events triggered by AI-powered video analytics. Conveniently, this allows businesses to utilize an “alarm” system where a panel isn’t present. A virtual line, triggered by AI recognition, can send an alert to security staff, offering increased flexibility in how the entire security system is leveraged.

Large Language Models (LLM) and Vision Language Models (VLM)

Finally, LLM and VLM are bound to become integrated tools in many venerable products/brands. The implementation of these foundational technologies into everyday tools, such as search engines and messaging applications, has driven a demand from users that they also be incorporated into their video surveillance solutions. Video security platforms can use natural language search to unlock new engagement and then combine machine learning and VLMs for visual analysis, LLMs for reasoning, and AI agents for automated actions, streamlining current tasks and enabling new applications.

As expectations for awareness and responsiveness rise, platforms must evolve from collections of features into systems of intelligence. This means designing AI capabilities that are embedded, contextual, and aligned with how people actually work, not bolted on as optional enhancements.

How OpenEye Continues to Innovate

To best empower customers in the next few years, OpenEye is continuing to innovate solutions that are powered by AI.

Natural Language Video Search

Natural Language Video Search is able to leverage complex queries to surface relevant video and shifts video review from a forensic task to an exploratory tool. Instead of manually scrubbing through hours of footage or spending time configuring search filters, this AI-powered capability enables simple descriptions to be used as search parameters to find relevant video, such as “a person carrying a box in the lobby yesterday afternoon” and quickly return the most relevant results. Natural Language Video Search eliminates manual review time and delivers clear, actionable insights, enabling faster, more confident decisions to improve operational efficiency.

Automated Visual Verification

Automated Visual Verification will offer proactive automated auditing, answering security and compliance questions quickly, such as “Is the floor mat present?” This helps automatically confirm whether important conditions are met, so business teams do not have to constantly watch video or perform routine inspections. Automated Visual Verification works by using AI to evaluate camera images and trigger alerts only when something needs attention. Each alert includes clear context, short AI-generated summaries, and reference images that make it easy to understand what happened for faster action taken.

Intelligent Similarity Matching

Intelligent Similarity Matching will further close the loop from detection to action by tying user-entered reference images to surveillance video, helping identify if persons-of-interest enter a camera’s view. Alerts are triggered via AI and sent with side-by-side images of both the reference photo and the captured video for verification by the user. This reduces operational workload by automating the monitoring process while simultaneously fortifying security.

AI-Assisted Support

Finally, AI-Assisted Support will function as an application of GenAI to support documentation. Users can receive instant answers to any issues they encounter through GenAI trained on OpenEye documentation and resources. As many cases can be resolved without a live support agent needed to assist, this will greatly benefit the user experience in OWS and ensure customers have reliable support 24/7.

Preparing Your Organization for the AI Era

AI does not replace expertise; it amplifies it. Pairing human judgment with intelligent systems is becoming a practical way for organizations to surface insight, reduce friction, and make faster, more informed decisions.

As AI becomes embedded in daily operations, trust matters. Security, transparency, and responsible deployment are no longer optional; they are foundational. At OpenEye, this means building AI directly into our platform in ways that are secure by design, ethically grounded, and focused on delivering practical value.

Looking ahead, the impact of AI on video surveillance is clear:

• Technology is evolving from passive recording to active intelligence, with agentic systems driving faster awareness and operational optimization.
  
• The industry is redefining the role of video, moving beyond “security only” toward platforms that support safety, efficiency, and business insight.
  
• OpenEye is advancing alongside this shift, investing in AI‑native capabilities that help customers deploy our open, intelligent, and trusted cloud video platform confidently and at scale.

The future of VSaaS does not belong to AI alone. It belongs to the security professionals, operators, and integrators who use these tools to extend their expertise and increase their impact. With the right platform, AI becomes a teammate, one that helps organizations see more, know more, and act sooner.

If you’re ready to explore how AI‑powered video analytics can elevate your operations, schedule an OpenEye demo today.

About the Author

Brent Boekestein leads OpenEye’s Enterprise team. Prior to that, he co-founded Vintra, an AI-powered video analytics company that was used by multiple Fortune 100 companies and the US Government prior to its acquisition by OpenEye and Alarm.com in April of 2023. 

Brent has delivered over two dozen talks globally on the Internet of Things and artificial intelligence. He holds an MSc from the University of Manchester and is a co-author of two patents in the field of computer vision.