IT Automation is the process of making tasks automated by a machine to improve workplace efficiency.

Automation works by setting rules for the machine, which tells it to do the tasks when triggered or automatically, depending on the rules set.

IT Automation can be very beneficial for your business. By automating simple tasks, it can help you save money and resources, as your employees can use their time doing tasks that are more complex. As the tasks you are automating are repetitive, having a machine do them can increase the speed and efficiency at which the task is completed. Also on this point, it can create fewer errors, as it is programmed to do the same task repeatedly for a long period.

For example, common examples of IT Automation is at the supermarket. Self-serve checkouts have changed the way we shop, and saved supermarkets money and resources paying more checkout employees.

It creates more efficiency in the store, as customers with fewer items can quickly put the items through themselves, instead of waiting in a line to be served. Supermarkets overseas have trialed checkoutless stores, creating apps for shoppers to scan their own items, and the final amount be charged to their account. Automation and machine learning similar to this example is changing industries as technology develops.

When setting up IT Automation in your business, remember not everything can be automated.

In our very digital reality, yes it probably can be, but we need humans to do some tasks that machines cannot. Machine automation is best for tedious repetitive tasks. A good start to automating tasks is to identify which ones take the most time to do, but involve the lowest skill. These tasks can be automated to assist you saving time and resources.

IT Automation is definitely going to be in the future of our business world.

As technology is evolving, machine learning will improve, and we will be able to automate all types of tasks in our businesses. Automation will also enable us to have insights into new metrics that we are not able to track now. Machines are getting smarter and smarter each day; the possibilities for machine learning are endless.