Sebastian Spicker, Managing Director DACH at IFS (Source: IFS)

They independently plan the deployment of service technicians, detect anomalies in machines and suggest countermeasures, or train new colleagues: AI agents are set to transform technical field service in the long term. IFS demonstrates how diverse their applications are in this area.

Agent-based AI heralds a new era of automation. AI agents that perform tasks autonomously without human input and make decisions in the process promise companies significant efficiency gains. One area that can benefit particularly from this is field service, as it operates in a highly dynamic environment with complex information. IFS, a leading provider of industrial AI software, demonstrates how agent-based AI can provide end-to-end support for technical field service.

1. Resource planning and route optimisation. A planning agent can dynamically and fully automatically plan and assign service orders. It prioritises orders, minimises travel times and takes into account the qualifications of service technicians. In this way, it ensures that the right technicians with the right equipment are in the right place at the right time as efficiently as possible.

2. Anomaly detection and prevention. Specialised agents continuously monitor sensor data and operating parameters of machines, independently detect deviations and classify their significance. Based on this knowledge, other agents then proactively suggest countermeasures or service calls before a failure occurs. This minimises downtime and reduces costs.

3. On-site support. Agents provide technicians with context-sensitive help during their assignments by analysing manuals, sensor data and previous cases, and then guiding the technicians step by step through the troubleshooting process based on the results. In this way, they ensure that technicians can quickly diagnose faults and eliminate them in a targeted manner.

4. Creation of service reports. During the service call, agents automatically collect all relevant information from sensors, call logs and the service technician’s communications, summarise it in a structured form and distribute it to the recipients. The technician no longer has to spend time and effort creating the report afterwards, freeing up time for more productive activities.

5. Forecasting spare parts requirements. Agents analyse historical and current data, derive the expected demand for spare parts and reorder them. This avoids delays due to missing spare parts.

6. Onboarding new employees. AI agents can efficiently train new service colleagues. They recognise their level of knowledge, dynamically adapt the learning content, provide interactive support, give continuous feedback and further develop the training content with the employees. This significantly reduces training times.

‘Agent-based AI is still in its infancy in field service, but it is becoming increasingly important and will continue to permeate and transform the industry,’ says Sebastian Spicker, Managing Director DACH at IFS. ‘With its ability to mimic human activities, agent-based AI will make service organisations more efficient, increase customer satisfaction and help them cope with demographic change and skills shortages.’