Dominic Jainy stands at the forefront of the modern shift in infrastructure, where the digital and physical worlds collide through artificial intelligence and decentralized data management. As a seasoned expert in machine learning and cybersecurity, Jainy has spent years dissecting how large-scale systems can be made more resilient and intuitive. With the recent advancements unveiled at the ASIAL 2026 event in Sydney, the conversation around physical security has shifted from simple surveillance to sophisticated data sovereignty and proactive intelligence. This discussion explores the integration of cloud-hosted access control with AI-driven video security, the regulatory pressures of the Security of Critical Infrastructure Act, and the strategic move from heavy capital investments to agile, operational expenditure models that prioritize real-time response over passive recording.
The following interview explores the critical importance of local data residency for government and enterprise sectors, the transformative power of “focus of attention” technology in reducing operator fatigue, and how physical security systems are being repurposed as vital business intelligence tools. We also examine the practical benefits of moving to mobile credentials to streamline operations and the ultimate industry goal of making the manual monitoring of video feeds entirely obsolete through autonomous analytical ecosystems.
The shift toward cloud-based security has historically met with some hesitation, especially regarding where data actually lives. How does the expansion of a local cloud instance for access control change the calculation for major Australian enterprises and government agencies?
It really comes down to a fundamental shift in trust and the legal necessity of data sovereignty. For a long time, the “cloud” felt like an abstract place, often leading to concerns that sensitive security footage or entry logs might be sitting in a data center thousands of miles away under a different legal jurisdiction. By bringing access control data onshore, there is a tangible sense of relief for security directors who are now operating under the Security of Critical Infrastructure Act (SOCI). This move allows them to tick every box for local residency requirements while benefiting from the speed of a fully integrated cloud environment. We are seeing large-scale organizations finally move away from their “on-premises only” mandates because the latency is lower and the legal compliance is airtight. It feels like a homecoming for data that was previously scattered, providing a unified architecture where video and access control live under one Australian roof.
Many organizations are transitioning from traditional capital-heavy investments to recurring operational expenditure models for their security infrastructure. What is driving this financial evolution, and how does it impact their ability to stay current with technology?
The old way of doing things required a massive, eye-watering upfront check to buy servers, cameras, and software licenses that would start depreciating the moment they were installed. By pivoting to an operating expenditure model, or OpEx, businesses are essentially future-proofing their security stack without the financial trauma of a multi-million dollar capital hit. This recurring fee model makes advanced AI-enabled systems accessible to a much broader range of companies that might have previously balked at the cost of entry. It also changes the psychology of the partnership; the provider is now responsible for keeping the system updated with the latest AI analytical capabilities in real-time. Instead of being stuck with five-year-old hardware, these organizations are always running the most current version of the platform, ensuring they never fall behind the curve of modern threats.
With the introduction of AI-powered analytics like “appearance search” and “unusual motion detection,” the role of the security operator is changing. Can you describe how these tools physically change a day in the life of someone working in a control room?
Imagine sitting in front of a “sea of monitors” for eight hours, where the flickering light and repetitive motion eventually lead to a sort of visual numbness. AI analytics like unusual motion detection act as a digital tap on the shoulder, alerting the operator only when something actually deviates from the norm, such as someone running in a hallway where everyone usually walks. Instead of manually scrubbing through hours of video to find where a specific shopping bag disappeared, an operator can use appearance search to find that exact moment in seconds. This reduces the cognitive load significantly, allowing a single person to manage a much larger network of cameras without feeling overwhelmed. It turns the job from a passive, soul-crushing task of watching nothing happen into a high-stakes role of managing real-time intelligence and response.
There is a bold ambition within the industry to essentially “make watching video obsolete.” What does that look like in practice, and how do we ensure that human oversight remains effective?
Making video watching obsolete doesn’t mean we stop using cameras; it means we stop using humans as the first line of detection for mundane events. The “focus of attention” feature is a perfect example of this, where the system uses AI to surface only the most relevant incidents, highlighting them so they are impossible to miss. We want the technology to do the heavy lifting of sorting through the 99% of footage where nothing is happening, so the human operator is only brought into the loop when a decision is actually required. This creates a much more surgical approach to security, where the “noise” is filtered out and only the “signal” remains. Human oversight actually becomes more effective in this scenario because the person is fresh, focused, and acting on high-quality data rather than trying to spot a needle in a haystack of a thousand simultaneous feeds.
How does creating a “security ecosystem” that links video, access control, and critical communications change the speed and effectiveness of an incident response?
The real magic happens when you break down the silos between different security technologies to create a closed loop of detection, analysis, and resolution. In a traditional setup, a camera might see a breach, but then the operator has to pick up a phone or find a radio to tell someone else what happened, which wastes precious seconds. In a modern integrated ecosystem, an AI-detected incident can automatically push an alert directly to the handheld radios of the guards closest to the scene, complete with a snapshot of the suspect. This link between detection and response is a total game-changer for critical infrastructure where every second counts. It turns a fragmented series of tools into a single, cohesive nervous system that can identify a problem and put a person on the scene before the situation has a chance to escalate.
We are seeing physical security tools being used for things like monitoring retail foot traffic or workplace safety. How are these “business intelligence” applications changing the way companies justify the cost of these systems?
Security is no longer just a “grudge purchase” or a cost center; it has become a source of valuable operational data that helps the bottom line. For instance, a retail manager can use heat maps and traffic analytics generated by their security cameras to see exactly when the store gets busy and adjust checkout staffing accordingly. By identifying peak hours through AI, they can prevent long lines and improve the customer experience, which directly impacts sales. In a warehouse or office setting, the same cameras can monitor for workplace health and safety violations, potentially preventing expensive accidents before they occur. This dual-use capability means that departments like Operations, HR, and Marketing are now contributing to the security budget because they see the tangible value in the data being harvested.
The shift from physical swipe cards to mobile credentials like Alta Access seems like a small change, but it reportedly has a massive impact on daily operations. What are the secondary benefits of moving toward a mobile-first access strategy?
It sounds simple, but the “forgotten card” syndrome is a massive, daily friction point for security managers that drains hours of productivity. By moving credentials to a mobile device—something people are far less likely to lose or leave at home—you almost entirely eliminate the constant stream of requests for temporary badges. This frees up the security team to focus on higher-value activities like risk assessment or system optimization rather than playing receptionist for employees who left their wallets in the car. Beyond that, mobile credentials allow for much more granular control; you can issue or revoke access instantly from anywhere in the world without needing to physically handle a piece of plastic. It’s a cleaner, faster, and more secure way to manage the flow of people through a building, and the user experience is significantly more intuitive.
What is your forecast for the future of decentralized security infrastructure over the next few years?
I expect we will see a total convergence where the distinction between “cyber” and “physical” security disappears entirely, and systems will become almost entirely self-healing and autonomous. By the end of this decade, the edge-computing power in a single camera will likely exceed what a full server rack could do just a few years ago, allowing for incredibly complex AI analysis to happen right at the point of data capture. We will move toward a “zero-trust” physical environment where access is granted based on a combination of biometric markers, behavioral patterns, and real-time risk scores rather than just a digital key. Ultimately, the infrastructure will become an invisible layer of the building, silently managing safety and efficiency without the need for constant human intervention, turning our environments into truly intelligent spaces.