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Robotic Process Automation: AI Learning To Walk Before It Runs

 3 min read / 

Robotic Process Automation (RPA) is a class of automated software that can use and understand a company’s existing applications through the user interface and automate routine rule-based operations such as reading emails and systems, calculating, generating documents and reports, checking documents and so on. Therefore, the application of RPA is extensive. In the future, those boring jobs that workers do not want to do will probably not need to be done by a human. Duplicated and standardised work can be done effortlessly by robots.

Standardised Processes

RPA is applicable to areas where companies have clear business rules, structured input and output operations, such as finance, human resources, supply chain, and information technology. The RPA technology itself is suitable for tasks with high-frequency, large-scale, clear-cut rules, repeated manual operations, and which take large amounts of time. The clear definition of the rules is an operation manual that can be written down for detailed, manual operations. In short, RPA can be effective where the level of process standardisation is sufficiently high.

To give some examples, the IT operation and maintenance department generally takes care of machines on a regular basis during the early hours of the weekend. All of them are similar commands to restart the machine and perform inspections. In fact, it is also suitable for RPA. The HR department’s formalities for the entry and exit of personnel, etc., can also be completed step by step. In addition to back-office departments, front-end business lines such as bank opening, membership registration, and order processing can also use RPA.

Standard Business Rules

The easiest way to judge whether a process is suitable for RPA is to compare the cost of implementing and maintaining RPA with the saved manpower. General return on investment can be considered above 1 (one year or less). Detailed operations guidelines are needed in processes if RPA is to take over. At present, many large state-owned enterprises and foreign companies will have them, while domestic SMEs are lacking in having detailed business rules. From this point of view, in fact, each enterprise will have a process that meets the conditions. However, in considering the early stage of RPA, the priority is to look at whether or not the level of standardisation of processes is sufficiently high. Otherwise, the process standardisation should be undertaken before investigating RPA.

If RPA is the robot’s neural network, then AI is the robot’s brain.

AI is a technical field for researching and developing theories, methods, technologies, and application systems for simulating, extending and expanding machine intelligence. It attempts to understand the essence of intelligence and to produce intelligent computers and programs that can respond to a variety of stimuli and inputs. Research in this area includes robotics, language recognition, image recognition, natural language processing, and expert systems. In general, one of the main goals of learning artificial intelligence is to make machines capable of performing complex tasks that usually require human intelligence.

The Key Difference Between RPA and AI

There is a big difference when comparing RPA and AI. RPA is process automation. It automatically completes the repeated processes according to one rule. It does not need to make a lot of judgments, whereas an AI needs to come to conclusions about what to do. The relationship between the two is like human hands and feet and brains. RPA is executed according to instructions and AI is more inclined to issue instructions.

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