Clear your Field Service Roadblocks with AI and AR

Field service management (FSM) is in the midst of upheaval—and it’s about time. In the last decade of working with companies on FSM, I’ve seen how field service operations have been slow to evolve until 1) they see enough budget or competitive pressure and 2) there’s technology available to address it.

That’s what’s happening now. Field service operations need to unlock new efficiencies to further reduce costs and keep customers happy, but now it’s going to require more than route optimization and other standard FSM platform functionality. To really stand out among competitors, companies will leverage artificial intelligence (AI), machine learning and augmented reality (AR).

Now, those are broad technologies, but they have highly specific uses in field service. I’ll describe examples of roadblocks that companies are encountering (or will soon encounter) on their path to more efficient field service. AI or AR will be key to clearing these roadblocks.

Companies have the data to improve scheduling—except dispatchers can’t leverage it

Schedule optimization—getting the right tech with the right tools and credentials to each job—has been the most reliable way for large field service organizations to improve their efficiency. The more factors their FSM platform can account for, like traffic patterns and appointment cancellations, the more jobs they can complete each day.

But many companies have reached a point where they can only unlock a new level of optimization by pulling in more datasets, but that data is too granular or complex for human dispatchers to balance. I’m referring to weather, real-time and historical traffic conditions, customer changes in availability, no-contact service calls (for COVID accommodation), predicting parts usage and other information companies have at their disposal that changes too quickly to track without automation.

AI will assist, and in some cases replace, human decision-making

Some companies are currently using automation in their FSM to incorporate more scheduling factors, such as how precipitation lengthens travel times in a certain zip code. They’re using business rules to account for those factors at different weights, and it’s creating more efficiency.

But that’s not the same as AI. In FSM, AI will see patterns emerging in the datasets, like how long it takes a particular tech to complete a particular job, and then apply those subtle patterns to scheduling, which will create an unprecedented level of optimization.

While there’s very little (if any) true AI working in FSM today, it’s coming. In their report, The Future of Field Service Management, Gartner predicts AI will debut in FSM as an “augmentation to the human decision-making process, and then replace it in a higher and higher percentage of cases.”

The field tech workforce is losing experience and expertise as techs retire

It’s no secret that field service sees a talent shortage on the horizon. A Manpower Group survey found 45 percent of employers struggle with recruitment, and skilled labor positions are especially tough to fill. At the same time, 73 percent of organizations see an aging workforce as a potential threat to their field service operations, according to a Field Service News report.

With a limited number of skilled workers entering field service as veterans age out, knowledge becomes more precious, and good training tools become paramount.

AR can support new techs by improving training, safety, collaboration and knowledge sharing

Companies are using AR applications that let customers use their phone camera to show the tech or support agent what they see, and the tech/agent can talk them through fixes and annotate the images with circles or arrows. It’s been a hit with customers and employees alike, we’ve found.

To augment training and knowledge-sharing, companies can use that same AR application to support less-experienced techs in the field. If they’re tackling an unfamiliar problem or working with new equipment, techs can receive remote visual support from senior colleagues a thousand miles away. Gartner notes in The Future of Field Service Management that companies in “specialty services” like oil and gas and HVAC are deploying this AR use case. Other fields can capitalize on it, too; they’re all going to need these scalable training resources during the field tech talent crunch.

Techs are spending too much time on basic tasks like collecting product information

Whenever companies can do something to simplify jobs for their techs, chances are it’s worth doing. A common example is how they’ve automated communications and arrival time updates that customers receive, so techs no longer have to worry about making those calls or sending those texts.

But there are still more tasks that field techs can offload to automation and save time on jobs. A significant one is collecting data on the product to be repaired, from the problem description to the model number. With more sophisticated communication solutions available today, techs should come to each job equipped with that information.

Conversational AI can collect basic information from the customer and pass it along to the tech

Companies are starting to deploy AI as frontline virtual agents to assist customers, which can carry benefits over to their field service operations. When a customer initiates a trouble call through a virtual agent, not only is that interaction automated, but the AI can collect key information from the conversation and send it to the tech who will work on that job.

Gartner predicts that these AI platforms will “perform more of the legwork” so techs can devote more time to what they’re on site to do: diagnostics and maintenance.


What’s on the other side of all these field service roadblocks? Not just a new level of optimization and efficiency, but also happier customers and techs. That’s why AI and AR will be key technologies to advance field service: with the right use cases, they cut costs while improving the total experience. If you’re looking for more information on those use cases and other advances, I highly recommend you read The Future of Field Service Management.