Read Astea’s whitepaper on machine learning and artificial intelligence and how it will impact the field service management industry. By Liron Marcus
A few months ago, my six year old son saw me working on my thesis and asked me what I was writing about. I responded, “I am writing about teaching computers how to learn.” My response seemed unsatisfactory and left him puzzled. He proceeded to ask me, “Dad, how can computers be taught to learn? They are not human.” I found myself struggling to find a simple explanation to his questions.
From small start-ups to large international corporations, a wide range of field service industries are investing considerable resources in cognitive technologies such as learning algorithms and artificial intelligence. So we know that there is a lot of buzz around these technologies, but are service organizations actually adopting them? How are they applying the concepts to their business operations? And lastly, what results have they experienced thus far?
What is Machine Learning? How is it Different than Artificial Intelligence?
Before we answer those questions, let’s clear up some confusion by defining both machine learning and artificial intelligence (AI) and exploring their differences. There’s probably no singular definition that would be accepted universally, but there are certainly some basic concepts. To understand those concepts, think about what machine learning actually does. The machine finds patterns in the data and uses these patterns to predict the future. In contrast, artificial intelligence provides automated reasoning and decision-making capabilities. The two are intertwined; in fact, machine learning is considered to be a branch of AI.
How have these Cognitive Technologies Evolved?
If you are wondering when these concepts were created, you can look all the way back to the original logical machines–computers. The computer’s end goal was that it could eventually function like a human brain. As we learn more about how the human brain works, we build that knowledge into artificial intelligence. And when you couple our deeper understanding of how the brain works with the massive amounts of data that the internet provides, you understand why AI and machine learning have grown so much in the last few years.
Machine Learning and AI Adoption in Field Service Industry
Now, let’s tackle some adoption rates among field service organizations:
- Gartner predicts that by 2020, 10% of emergency field service work will be both triaged and scheduled by artificial intelligence, up from less than 1% in 2017.
- By 2022, Gartner predicts that one-third of complex field service organizations will utilize machine learning to predict work duration and/or parts requirements, up from less than 2% today.
- According to a recent survey of customer experience management leaders by Aberdeen, only 14% of their organizations were currently using machine learning and only 9% were using AI.
- Yet 40% of the surveyed companies are planning to deploy machine learning and 34% are planning to deploy AI.
In short, adoption has been slow thus far, but it will grow rapidly as the early adopters show positive results.
To learn more about how machine learning and artificial intelligence will impact the field service industry, download the whitepaper “Machine Learning and Field Service Management in Practice.”
In the whitepaper, we provide a deeper dive into the origin and evolution of cognitive technologies. We also explore adoption trends more in-depth and perhaps more importantly, the results that early adopters have experienced. Then we review some real-world applications, such as dynamic scheduling, contact center management and inventory management. Lastly, we walk through a step-by-step process using the concept of machine learning to answer the most prevalent and important question in field service: ‘What is the best resolution to a given problem?’
Download the Astea whitepaper “Machine Learning and Field Service Management in Practice” now to learn:
- The origins and evolution of machine learning and AI
- The two breakthroughs that have made them so popular today
- Impressive results from early adopters: from customer service, to CX, to employee engagement, and revenue growth
- 4 real-world applications in field service
To learn more about how Astea can help your field service organization embrace emerging technologies such as machine learning and artificial intelligence, click here.