Using AI To Build A Modern Field Service Organization

By Sajith Sahadevan, Senior Product Marketing Manager, Dynamics 365 Field Service

Field service organizations have traditionally operated under the break-fix model, responding to device failure after the customer reports an issue. This operating model has grown costly and inefficient and has proven less than effective in satisfying the customer’s rising needs.

As the field service industry rapidly evolves toward a proactive and predictive model, cutting edge technologies including automation, artificial intelligence (AI), new learning tools, and augmented reality are helping transform field service by providing optimal device uptime, along with greater visibility, efficiency, and profitability.

Why AI for field service?

The ability to capture, digest, and derive actionable insights from data is critical in modernizing field service organizations. Intelligent, predictive systems driven by AI can automate manual, time-consuming tasks like collecting data, diagnosing problems, and identifying the best solutions to resolve issues. AI optimizes resource management, empowers field teams through mixed reality and mobilization, and improves customer service with proactive and predictive service. In short, AI is providing organizations with the ability to optimize every facet of field service delivery.

While service organizations lay frameworks of sensors and solutions to capture data across every facet of their organization, AI and machine learning represent the next steps that organizations are taking to leverage the value of the captured information. The ultimate goal is to transition from a reactive, break-fix service model to one that is proactive and predictive, achieving a near constant uptime.