Future of Artificial Intelligence (AI) in Maintenance and Service

Are you an artificial intelligence (AI) optimist or pessimist? Today, AI is often thought of as either the end of the world as we know it; when robots will take all of our jobs; or the answer to all our problems, when AI is the ultimate solution to save the planet. It’s ironic that such a complex technology often provokes such a simple, binary response. Ultimately, that’s a problem when it comes to utilizing AI’s full potential. 

Anyone who actually works with AI will tell you that the truth about the technology is less dramatic, at least in the short-term, but far more relevant now than you can imagine. The key to successfully utilizing AI is to combine its strengths with the human brain. With that in mind, there are three areas where AI can make a real difference:

AI augmentation and decision automation

The reason people believe AI will deprive them of their jobs is because they confuse AI with automation. According to the research firm Gartner, Inc., 2020 will be a pivotal year in AI-related employment dynamics as it becomes a positive job motivator.

“Unfortunately, most calamitous warnings of job losses overshadows the greatest AI benefit: AI augmentation— a combination of human and artificial intelligence where both complement each other,” explains Gartner Analyst, Svetlana Sicular.

In an expanding global market, industries constantly wrestle with increasing complexity. Businesses are increasingly tasked with producing or delivering more from fewer resources while using leaner, faster operations. As a consequence, demand for products and services may shift instantaneously in markets across the world. In this case, AI augmentation can be used to improve decision optimization.

Imagine a manufacturing company selling products in 50 markets. A sudden increase of raw material prices in one region, or new trade tariffs, will make it important to be able to adjust demand and possibly pricing on short notice. Here, AI can help you create an overview of a large number of factors simultaneously to produce a plan for how to adjust demand planning and pricing. Historical data can be used to help AI quickly and strategically propose decisions while detecting anomalies and patterns. That way, some decisions can be automated by the AI based on past actions and specified priorities.

AI-enhanced predictive maintenance and service

High-profile stories like driverless cars always grab the headlines, but in reality, how the car is maintained and serviced is where AI will impact first. Such factors include which algorithms will use what sensor data to predict the car’s specific needs in context, ahead of time, whatever the climate, whether on the open road or in the service bay.

In fact, the global advising firm McKinsey & Company found that predictive maintenance enhanced by AI allows for better prediction and avoidance of machine failure in manufacturing. By combining data from advanced Internet of Things (IoT) sensors, maintenance logs, as well as external sources, asset productivity increases of up to 20% percent are possible, and overall maintenance costs may be reduced by up to 10%.“

Asset-intensive industries, like manufacturing or energy, are ideal applications for AI since, these days, most of the key equipment are fitted with loads of sensors that generate mountains of IoT data that can form the foundation for building machine learning algorithms. Based on the data, AI can turn maintenance from preventive to truly predictive.

AI-supported system interaction

The area where AI perhaps is most advanced already is interaction with people or systems. AI-powered voice assistants represent a major opportunity for many organizations, both internally and externally. The key is to use it for the uncomplicated queries or transactions that occur in great volumes. These tasks can be uncomplicated in nature but still require you to log in to an application and perform a short series of actions every time you do it, which in the long run takes time.

In a company setting, AI chatbots have a great potential to make this process more effective. One example could be when employees need to call in sick, ask for leave, or simply want to find and access certain items in their enterprise software. Making it possible to access this information, and actioning it, using your voice or by chat enables significant time and cost savings. The added AI capability can in time refine the process so the path to executing the task will be smoother next time.

Outside of a company internal workings, taking calls at a service helpdesk is a natural way to use AI chatbots. Calls are often simple requests such as establishing opening hours or determining when an engineer is due to arrive. As many contact centers are now developing omnichannel solutions, to include voice, e-mail, social media, and chat as contact options, the AI capability could also help to identify your preferred contact option and quickly guide users through the contact process.

In the very near future, an AI-powered approach could be essential to the quality of service you can deliver. As smart as AI technology is, only you can decide if it’s a wise decision for your company.

Written by:  Bas de Vos, Director of Industrial and Financial Systems (IFS), a global enterprise software provider, for SNIPS.