Gartner is encouraging businesses to enter into the machine customer "megatrend" which it calls "one of the biggest new growth opportunities of the decade".
The introduction of machine customers will be viewed as a more significant technological milestone than the advent of digital commerce, according to Gartner.
In a new book by Gartner, "When Machines Become Customers", analysts conclude that machine customers will be used in a number of business and consumer purchases. They also dissect the main challenges and opportunities that companies will face and offer advice on how they should act.
Don Scheibenreif, VP Analyst at Gartner, said:
The machine customer era has already begun. There are more machines with the potential to act as buyers than humans on the planet.
"Today, there are more than 9.7 billion installed IoT devices, including equipment monitoring, surveillance cameras, connected cars, smart lighting, tablets, smartwatches, smart speaker, and connected printers.
"Each of these has a steadily improving ability to analyze information and make decisions.
"Every IoT-enabled product could become a customer. In fact, Gartner predicts that by 2027 50% of people in advanced economies will have AI personal assistants working for them every day."
Gartner advises that executives should work together to prepare for the machine customer revolution. This preparation will include numerous areas within businesses.
For example, legal officers will need to determine what ways the company can implement the technology with its customers. CIOs will need to manage the construction of the machine learning platforms to ensure they can effectively serve customers. Marketing officers will need to reappraise customer needs. HR, supply, and revenue officers will also need to project the ways in which machine customers will affect their businesses.
The Machine Customer Evolution
Gartner divides the machine customer evolution into three phases. The first phase, "bound customers", which we are currently in, is defined by performing limited functions on the owner’s behalf i.e. machines executing rules created by people. Examples of this can be seen in Tesla’s cars, Amazon Dash Replenishment, and HP Instant Ink.