The illusion of control: Can we ever fully secure autonomous industrial systems?
In the rapidly evolving world of industrial IoT (IIoT), the integration of AI-driven decision-making into operational technology (OT) systems has created the impression of tighter control, smarter response times and predictive efficiency. This feeling of having control might actually be a risky illusion. Autonomous systems are now responsible for critical infrastructure: smart grids, manufacturing lines and water treatment facilities, all relying on interconnected sensors and AI for autonomous decision-making. But as the layers of automation deepen, so too does the complexity, making it increasingly difficult to understand or audit decisions made by machines. As more layers of automation are added, the number of interconnected components – think of sensors, AI algorithms, communication network, and control systems- grows exponentially. Each new layer introduces more variables, dependencies and potential points of failure. AI models themselves often operate as “black boxes,” makin...