This niche is highly exposed to AI because predictive maintenance is fundamentally a data science problem. AI excels at anomaly detection, sensor data analysis, and predictive modelling of failures. Much of the methodology is codifiable and already integrated into software platforms. Human consultants are still needed for integration, stakeholder engagement, and interpreting outputs in business and financial terms, but the technical side is increasingly automated.