With an acceleration in the number of digital initiatives, several International enterprises have used the power of automation to support their digital transformation efforts. Different organisations have used different strategies with respect to their automation journey.
Many organisations started their automation journey using technologies such as macros, data scraping, and desktop automation. While these enterprises were successful in automating certain tasks, the challenges far outweighed the benefits.
Difficulties in integration, security risks, and governance issues were a few of the challenges faced by enterprises who had adopted these tools.
Next steps for organisations was to introduce RPA but seems like it also has its share of problems.
What is RPA ?
RPA is converting or mimicking repetitive human tasks and create software robots, or “bots”.
These bots can learn, mimic, and then execute rules-based business processes. RPA automation enables users to create bots by observing human digital actions.
Robotic Process Automation software bots can interact with any application or system the same way people do—except that RPA bots can operate around the clock, nonstop, much faster and with 100% reliability and precision.
What is Intelligent Automation ?
Intelligent automation is a combination of Robotic process automation (RPA) and Artificial intelligence (AI).
Companies use intelligent automation to cut costs by using artificial-intelligence-powered robotic software to replace workers who handle repetitive tasks.
Intelligent Automation, in contrast to RPA, enables organisations to adopt a more holistic approach towards automation.
It enables proactive identification of new processes with automation potential, aligning/preparing these as required, and finally automating these. Intelligent automation also helps organisations to scale their automation initiatives with ease.
What is missing in RPA ?
With RPA’s help , processes that were repetitive, error-prone, and without variations, became obvious candidates for automation. But RPA too had its challenges. One obvious challenge was the dependency on the underlying application.
RPA is dependent on applications and any change in application will affect RPA. If there is any change in application , RPA bot needs to be updated as well
RPA lacks the ability to create front-end user interfaces and define new workflows plus RPA is prone to application interface changes and process changes. This can increase overall Bot maintenance cost.
How Intelligent Automation is filling the gaps
While RPA tends to focus on automating repetitive and, many times, rules-based processes, intelligent automation incorporates artificial intelligence (AI) technologies like machine learning, natural language processing, structured data interaction, intelligent document processing along with RPA basis functionalities.
Because AI simulates types of human intelligence, automation can process higher-function tasks that require some level of reasoning, judgment, decision, and analysis.