The possibilities of utilizing artificial intelligence are vast — and it’s worth digging deeper than just the surface-level applications.
This is the third part of our blog series on using AI in the maintenance business. This time, we’re focusing on more specific features that can bring significant value to maintenance entrepreneurs. Beyond the obvious AI applications, such as customer service chatbots, integrating AI into more advanced tasks is key to unlocking its full potential.
Automatic Classification of Fault Reports
AI can automatically classify and prioritize customer fault reports, speeding up the processing of service requests and improving response times. For service coordinators, this means incoming reports are already sorted, for example, by type or urgency. AI can also push the most critical issues to the top of the queue, ensuring timely handling.
Spare Parts Logistics Optimization
AI can predict spare part needs and optimize inventory orders, helping reduce downtime and unnecessary stockpiling. Integrated into inventory management systems, AI assistants can detect when parts are running low and anticipate order requirements. Over time, with enough historical data, the system can even recognize seasonal demand spikes — like increased usage of certain parts during colder weather.
Automatic Detection of Anomalies
AI systems can automatically identify unusual working hours, delays, or recurring complaints, and suggest corrective actions. This capability helps reveal inefficiencies in processes or early signs of equipment failure. Addressing these issues early can result in substantial cost savings. Such cases have already been reported internationally.
Speech Recognition in Service Reports
Maintenance technicians can dictate their reports, which AI then transcribes and stores in the system. Since both hands are often occupied during maintenance work, voice recognition brings a clear advantage. It saves time and reduces the risk of forgetting key details, as actions can be recorded right after they’re performed.
Machine Learning for Service Contract Optimization
AI can analyze the profitability and utilization rates of service contracts and suggest customized adjustments for different customer segments. Through machine learning, AI learns which contract types perform best in specific scenarios and recommends optimized changes. Drafts can be sent to customers quickly, and overall, updating and modifying contracts becomes faster and easier.
When used correctly, an AI assistant can generate significant savings for maintenance entrepreneurs and streamline operations across many areas. To fully reap the benefits of AI in maintenance business, it’s important to boldly integrate it into a wide range of tasks.
