AI will predict potholes on Kazakhstan's roads before they appear

Kazakhstan announced a system that will predict the appearance of potholes: AI will analyze pavement condition, load and climate data — and point to sections where deterioration is about to begin. The point is a change of model: not patching on drivers' complaints, but repairing preventively while the defect is still cheap.

This is classic predictive maintenance — the approach industry is mastering on machine tools and turbines: sensors and statistics let you fix equipment before the breakdown. The economics are the same everywhere: planned intervention is several times cheaper than emergency work, because it does not drag along downtime, urgent purchases and consequences for customers.

A business owner should try the principle on their own assets, even if those are not roads but a vehicle fleet, refrigerators, servers or the coffee machines of a cafe chain. The first step is available to everyone: start recording breakdown and maintenance history digitally. Even simple statistics reveal what fails most often and when to step in — and as data accumulates, the forecasting can be handed to an algorithm. Potholes are cheaper to prevent than to drive around — on roads and in business alike.