By Sarah Nicastro, Creator, the Future of Field Service

There has been a lot of news generated around artificial intelligence (AI) over the past year, and back in March, I wrote about short-term and long-term ways that AI can benefit field service. Over the summer, I also talked to Alfonso de la Nuez, who is very bullish on how AI can improve digital customer interactions.

Field service tools are already beginning to incorporate generative AI into their workflows. The idea is that these AI algorithms can help better route customer service requests to specific technicians based on their skills or experience with a particular customer. This provides new functions that can help save time for technicians and improve service for customers, while also automating more the dispatch function so that the dispatchers can focus more on addressing emergencies or other value-added tasks.

However, these tools also provide much more granular visibility into employee activities, which for some, may raise concerns about increasing levels of employee surveillance. A few years ago, Google got into trouble because a calendar tool extension was seen as a way to monitor employee meetings and possible crack down on unionization efforts, and there has been consistent pushback in some industries around how AI can enable employee surveillance. In field service, particularly with a lot of younger technicians entering the workforce, concerns about “Big Brother”-style employee monitoring going to be a problem?

Visibility Vs. Micromanagement

There is a fine line between increasing visibility and insight using technology and enabling an invasive level of surveillance or micromanagement. For a lot of desk workers, this usually involves software that keeps track of their productivity and Internet usage. In some industries, companies use software to record and evaluate customer calls and other interactions.

There have been some studies that indicate heavy employee surveillance actually encourages rule-breaking or can be detrimental to productivity. This has gotten a lot more attention since the COVID pandemic created an influx of employees working from home. Gartner says the number of large employers using these types of tools has doubled since 2020 to 60% of firms and will probably rise to more than 70% in the next few years.

And various surveys show that, as you might expect, a lot of employees do not like that. This is especially true since, in some instances, worker surveillance is discriminatorily targeted more frequently at women, minorities, and workers in low-skill jobs. According to a report from the Institute for Public Policy Research, both non-unionized women and black workers are 52% more likely to face workplace surveillance, and young people in low-skilled jobs are 49% more likely to be monitored.

Field service is a lot different than the work-from-home desk jobs usually profiled in articles about workplace monitoring, and I suspect that young workers are probably less worried about it than their older coworkers because they have grown up in a culture of online data sharing. According to one study, just 22% of employees aged 18-34 were concerned about employers having access to personal information and activity on their work computers.

In field service specifically, workers are already used to a high-level of visibility. Routing and scheduling systems live and die on accurate data about location, job completion, and other data points. Field service organizations regularly evaluate data around drive times, time to completion, and other information, most of it related to SLA compliance, safety, and reimbursement. 

What can sink a technology deployment that involves this type of visibility, though, is a lack of communication. Most technicians don’t mind this type of data collection, provided they know why it's being deployed, and how it can help them do a better job. 

According to a study that appeared in the Journal of Computer-Mediated Communication this year: “Attitudes toward workplace surveillance grow more negative when there isn’t a clear rationale for collecting this more sensitive data, and workers may see this as an abuse of power ... Therefore, it becomes essential for employers to clearly communicate both the purpose for collecting data, how they will use that data, and constraints on future data use.”

If you have any thoughts on AI in field service, or how increased visibility is accepted by the technicians in the field, feel free to drop me a note about your experiences.