Automation is the use of technology to reduce the human input required in a task, process or system, especially those involving manual or repetitive actions. In any automation, there will be an input (the data entered into the system) and an output (the system outcome). In feedback control systems (Principle 3), the input (also known in these systems as the ‘set point’ or ‘reference value’) can be understood as the desired state the system is to achieve (e.g. in the case of a thermostat the desired room temperature) and the output as the current state (or system variable) that might need modification (e.g. the actual room temperature).
Automation systems are programmed to determine the output based on the input (Principle 2) and feedback controls can achieve a specified output by self-adjusting to environmental feedback (Principle 3). These simple concepts can be scaled beyond one discrete task across a whole process, using technology within a self-governing system to replace the control and operation of the system itself.
This flexibility has seen automation employed in many different ways across a wide array of sectors. From robotic process automation that uses rule-based applications to simply replicate human action, to more complex AI-based automation tools that replicate human judgment and decision-making. This flexibility allows users to tailor the use of automation to meet their specific needs, resource availability and technical expertise, and decide whether it replaces or simply augments existing processes or systems.