How should a field service company approach understanding how AI can benefit their business?

Mark Tatarsky, SVP Marketing, FieldAware

Field Service organizations need to take a proactive approach to build a platform infrastructure that is capable of capitalizing on AI. This selection is critical to set up early and helps pave the way for the future. Field Service Management platforms that are purpose-built on the cloud and leverage a robust, open API communication structure are best poised to help organizations take advantage of the growing use cases for AI.

Anticipating the future needs of the organization and investing appropriately in the current systems is critical. We are just starting to scratch the surface of the potential use cases for AI. As the global communications infrastructure continues to become more sophisticated, powerful, and high-speed, it will support higher volumes and larger packets of remote data, opening up the potential to use even more data from remote sources.

Field service organizations can start to look at their current processes and think through how they can be further digitized and automated. AI offers Field Service organizations the opportunity to reduce the mundane tasks of monitoring, analyzing, and actioning data-driven activities, freeing up the organization, and precious skilled resources to focus on high-value activities.

Amit Jain, Senior VP of Product, ServiceMax. 

I think it is important to understand that increasingly AI will become a standard aspect of many field service solutions.

One of the major benefits of the ‘Cloud revolution’ is that more and more your field service solution providers can and should be expected to do much of the heavy lifting in terms of updating and developing the systems that you rely on to deliver service excellence.

Therefore, I think it is crucial to understand if, where and how AI is utilised within the solutions. For example, with regards to Machine Learning, ask if it is a genuine ML application and if so, how will it adapt and evolve overtime within your business?
As a starting point, a field service company can list out its business processes which are automated by configuring static rules as a candidate for ML.

The business can then evaluate which processes have a high cost to maintain or whether the processes are even being executed well to begin with. With this evaluation, the business can rank which business process to focus on and give itself the best shot for a positive ROI on the ML project.

The final part of this Big Discussion will be published next week, when the pair debate AI as a standalone technology or something that should be part of a bigger technological picture. If you missed the previous parts you can read the first part of the big discussion here and the second part here.