Undocumented logic, fragile dependencies, and silent errors. Artificial intelligence is replaying that trajectory at far greater speed and scale. As highlighted in a recent TechRadar analysis on so-called “zombie projects”, organisations are increasingly burdened by AI initiatives that consume resources yet deliver little enduring value. The risk is not that AI fails, but that it succeeds too easily without discipline.
In the fluorescent glow of a modern fulfillment center, the future of automation is on full display, along with its most glaring vulnerability. Autonomous mobile robots glide effortlessly between storage pods, conveyor belts hum with precision, and robotic arms sort packages with mechanical efficiency. On paper, the system is a marvel of productivity, capable of processing tens of thousands of orders per hour. But in the control room, the reality is far less seamless.
While public cloud remains indispensable for certain workloads, it’s no longer seen as the default, “cheap,” or inherently secure solution for all operations. Industry reports reveal a seismic shift.
