RPA is the combination of several technologies, brought together under one toolkit for different automation purposes. Though the term ‘RPA’ emerged in the early 2000s, the initial development was started after the 1990s.
‘Machine Learning (ML)‘ is one of those technologies that helped towards innovation, which eventually lead to the creation of RPA. In 1959, ‘Arthur Samuel‘ developed Machine Learning. Machine Learning allowed computers to perform several critical tasks, such as translation and text summarization, etc. However, there were limits on how computers could process language. It led to the development of ‘Natural Language Processing (NLP),‘ which helped computers to understand and process human language more accurately. In 1960, NLP combined ‘AI (Artificial Intelligence)‘ for establishing the interactions between computers and human languages. Then, the technology progressed further towards the establishment of RPA, and there were few more developments in the 1990s.
Because of the continuous developments, there was an emergence of technology that most closely resembled RPA. The history of RPA tells that there were three key predecessors of Robotic Process Automation that are given below:
Screen Scraping
Screen Scraping technology is considered as a significant step towards the creation of RPA. This technology is used to extract data from web, programs, and documents, which is further displayed by another application.
While there were many benefits of screen scraping over manual labor, screen scraping was also limited to some extent. Due to limitations and lack of availability of source codes, programmers, and documentation, it became difficult to understand for the average business user.
Workflow Automation and Management Tools
Workflow automation is the process that includes a series of automated actions, which helps in reducing the human task. These actions must be repetitive so that their steps are predictable. Such actions can be automated by using automated management tools. Workflow automation uses business rules to decide when the step has been completed, and the execution of the next can be started.
Artificial Intelligence
Artificial intelligence is the ability of computer machines or robots to perform tasks that typically require human intelligence. AI programming is based on three techniques: learning, reasoning, and self-correction.
The applications for artificial intelligence are endless and can be applied to many different sectors and industries. Some of the commonly used technologies of AI are:
- Image Recognition – It is the technology that identifies and detects objects or attributes in images or videos.
- Speech Recognition – It is the technology that identifies words and phrases in spoken language and converts them into a machine-readable format.
- Natural Language Generation – It is the technology that transforms structured data into natural language.
- Sentiment Analysis – It is the technology that uses natural language processing, text analysis, and biometrics to identify, extract, quantify, and study subjective information.
All these technologies together made RPA such an impactful technological platform and added more benefits for the business users.