I was recruited by just one company coming out of graduate school. I remember the day of my first interview vividly—I had nearly talked myself out of it. Selling cameras didn’t seem like the high-tech future I had envisioned after completing my master’s degree at the University of Utah. I wanted to be in a deeply technical field, solving complex problems as a technical salesperson. Cameras, at the time, felt too basic.
A little research before that interview changed everything. What I discovered was an industry on the verge of transformation—ripe with potential and driven by emerging technology. Until that point, surveillance was largely dependent on closed-circuit television architecture. Analog cameras and coaxial cabling were the standard. Even today, remnants of that era are still found in many environments.
But as I entered the field in 2013, the IP (Internet Protocol) inflection point was nearing its end. My very first sale was for IP encoders—devices that could ingest analog video over coax and output it as IP, effectively allowing customers to modernize their infrastructure without ripping and replacing everything. These sold like hotcakes, and for good reason: IP unlocked access to standard network infrastructure, allowed for rapid software innovation, and enabled remote access to video feeds from anywhere. No more squinting at grainy footage in a dark server room; now, a customer could identify what vehicle hit the fence post from a browser halfway across the world.
IP was more than a technical upgrade—it was a gateway. It paved the way for the cloud to enter the surveillance conversation. With IP, the head end of a surveillance system could be virtualized. Cloud-based platforms offered infinite scalability, centralized management, and the ability to deploy features and updates at the speed of software. Imagination became the limit.
The Cloud Era: Virtualized, Scalable, and Always-On
Cloud changed the game by making surveillance systems location agnostic. No more being tethered to on-premises NVRs and DVRs. With cloud-native or hybrid systems, users could securely manage, access, and share video from anywhere with an internet connection. Suddenly, visibility became 24/7—not just in terms of time, but across geography and organizational silos.
For multi-site enterprises, this was transformational. A retailer with 500 locations no longer needed 500 discrete video systems. Central IT could manage firmware, access controls, device health, and incident response from a single pane of glass. This consolidation didn’t just reduce complexity—it enabled entirely new operating models.
The possibilities only expanded with the evolution of application programming interface (APIs) and integrations. Cloud-based video management system (VMS) platforms began connecting with access control systems, alarm panels, point-of-sale terminals, and even environmental sensors. Video moved from being a reactive evidence tool to a real-time input in an intelligent, interconnected ecosystem.
Cloud also brought a new level of agility. In the traditional model, deploying a new feature meant updating every appliance across the enterprise. Now, updates could be pushed centrally, continuously, and without downtime. The “VMS” evolved from static software to dynamic service—always improving, always iterating.
Of course, this transformation also introduced new responsibilities. When surveillance lives in the cloud, security of security becomes paramount. Questions around data sovereignty, encryption standards, user authentication, and incident response protocols took center stage. But the shift was inevitable—and beneficial. Cloud-first security forced the industry to harden itself, adopting best practices from the broader IT world.
The Rise of Analytics
In 2014, the company I worked for acquired a video analytics startup. The goal was to integrate that technology into our existing VMS platform. At first, I didn’t quite grasp the significance. “So what if the camera draws a red box around a person?” I thought. “How does that really help?”
But those basic questions were the same ones customers would ask—and that meant I needed to understand the value at a foundational level.
The key word is recognition. Once a camera can identify a human or a vehicle in real time, the logic you can apply becomes limitless. You can record only when a person enters the scene. You can trigger alerts, tie into other hardware systems, or run complex automation—all based on actionable data. That simple red box represented a shift from passive recording to intelligent surveillance.
Of course, for any of this to work in real-world, mission-critical environments, the analytics had to be accurate. I quickly learned a painful but valuable lesson: overselling technology that isn’t ready can break trust and damage relationships. In those early days, analytics were more promise than performance—a dynamic sometimes referred to as “security theater.”
Still, my optimism drove me to dig deeper. I insisted on programming analytics myself. If something we sold didn’t work as expected, I’d go onsite to troubleshoot it firsthand. Those moments—often stressful and humbling—were my true education in intelligent video analytics. They taught me not just how the technology worked, but when and how to position it credibly.
Intelligence at the Edge Meets Infinite Compute
About 2017 to now, we hit what I consider a compound inflection point. Manufacturers began deploying deep learning-based analytics directly on edge devices, and the cloud started to gain real traction. The combination of edge intelligence and cloud computing fundamentally reshaped the surveillance industry.
Today, analytic performance is a key differentiator. Artificial intelligence at the edge allows for lightning-fast event detection and classification without the latency of backhauling video. Cameras can now distinguish between a person and a shadow, a vehicle and a tree branch, even a loiterer versus a passerby.
Simultaneously, cloud-based platforms began ingesting this edge data and enriching it—using powerful algorithms to detect anomalies, run cross-site pattern analysis, or trigger advanced workflows. The edge gives us speed. The cloud gives us scale.
We’re also seeing the rise of metadata-driven surveillance. Cameras no longer just capture footage—they generate structured data about what’s happening in the scene. This metadata fuels search, audit, and automation at a level we once thought impossible. You can now type “white truck with ladder rack” and instantly retrieve relevant clips across hundreds of sites. Or configure a system to alert you only when someone approaches a restricted area, lingers more than 15 seconds, and is wearing a backpack. That’s not science fiction—that’s now.
From Reactive to Proactive: The New Role of Surveillance
The surveillance industry has traditionally been reactive. A theft occurs, an incident happens, and then we go back and pull the footage. But with intelligent analytics and cloud infrastructure, we’re moving toward a proactive insights model.
Instead of just seeing the past, we can now influence the present. A system might automatically trigger lights, speakers, or lockdowns based on behavior analytics. Or notify security staff of a crowd forming at a venue before it becomes a safety hazard. Surveillance is no longer just a camera on a wall—it’s a real-time sensor in a broader system of awareness.
This shift has also opened new use cases. Retail uses cameras for dwell time and conversion analytics. Cities use them for traffic optimization. Warehouses use them to ensure safety compliance. Video has become more than security—it’s now business intelligence.
Looking Ahead
Of course, challenges remain. Accuracy, privacy, and interoperability are ongoing concerns. But if the last decade has taught me anything, it’s that innovation moves faster than most expect—and those who embrace the inflection points are the ones who grow with them.
Today, we are equipping cameras with brains, connecting systems across clouds, and layering intelligence atop environments that once relied solely on grainy footage and manual review. The industry is evolving rapidly—and the next decade will likely bring even greater transformation.
From coax cables to cloud orchestration, I’ve watched this industry reinvent itself again and again. I’m grateful I didn’t walk away from that first interview. What I thought would be a simple career in cameras turned out to be a front-row seat to one of the most dynamic technology shifts of our time.
