A good field service results in revenue growth and high customer satisfaction. However, problems tend to pop up — such as miscommunication between the office and field, scheduling conflicts, and route planning. To solve these issues, and prevent any from happening in the first place, companies need to use real-time data and alerts. Fortunately, technology has evolved to make these processes much easier and more efficient. And one such growing technology is artificial intelligence (AI).

In the field service sector, AI can help improve the transparency and streamlining of
processes.

The increasing interest in AI for field services has added to the demand for software developers. Currently a there is a big shortage of qualified professionals. As of 2020, most companies are looking to hire around 50 of these professionals, with some wanting to hire up to 100. There’s also an urgency to fill these positions, and companies are fighting over a small talent pool. As such the education sector has evolved to meet is growing demand. Top universities now offer online management information system programs that can be completed 100% remotely and are just as comprehensive as traditional on-campus degrees. These online courses teach professionals hard skills like programming and application development as well as soft skills like problem-solving, which are important for AI software development. In the field service sector, AI can help improve the transparency and streamlining of
processes. More than that, here are a few ways AI can help companies improve
their field services:

Easier scheduling and dispatching

A team is typically assigned for scheduling and dispatching. For scheduling, people will have to coordinate information from their telematics software, inventory management system, and event calendars. But AI will be able to do all that for them and easily find the best schedule and technician available for the job.

Meanwhile, there are also a number of factors involved in dispatching, such as return trips and route planning. AI-optimized routes let technicians service as many customers as possible by organizing their priorities. This means that they can focus on the hardest jobs first. In relation to this, AI can also use algorithms to predict whether a job will be successful or lead to a return trip, depending on the information it collects.

More efficient customer service

AI can also serve to directly improve the customer experience. For instance, having intelligent self-services capabilities on your site can let customers upload pictures of their issues and schedule a technician on their own. This request, and the information involved, can be integrated into another AI-powered scheduling and dispatching software.

AI for customer service can also be used through chatbots. Modern customer service chatbots can understand and answer a variety of customer concerns, from a quote for a certain job to upgrading a service. This is thanks to the mass of data that trains the AI behind the chatbot. These chatbots are available 24/7 and can answer a customer more quickly than human agents.

Better preventative maintenance

Planned maintenance doesn’t always work since it may be hard to spend money and effort on problems that aren’t obvious. However, this will only cost your company more in the event that something does break down. As such, preventative maintenance may be more prudent. The difference between preventative and planned maintenance is that, while the latter leans on a service schedule, the former relies on monitoring equipment for initial red flags.

AI can help with suggestive preventative maintenance by collecting data from equipment through sensors and other similar technologies. Asset
performance data and anomalies are then analyzed and reported through
dashboards. This will make it easier for technicians to spot problems and
would-be problems. AI can help reduce unexpected equipment downtime and
unbudgeted expenses.