There’s a buzz in the world of business lately, and it’s caused by the growing potential of technology and automation. The concept of “Robotic Process Automation” or RPA, and Artificial Intelligence (AI), has sparked controversial debates throughout the world, as companies struggle to determine how combining these two technologies might provide a roadmap to progress.
Although both technologies already exist and have the potential to drive change, through simple form-filling features for RPA, and data management in AI, the real magic happens when the elements are combined.
While AI and RPA are highly different technologies, they complement each other perfectly in some instances. While you can use either solution separately, the combination of both together can be particularly revolutionary.
The Connection Between RPA and AI
Simply put; Robotic Process Automation is a software solution that copies the actions of humans to run business processes.
The software robots can only mimic a simple set of instructions, which means that they might be used for entering data into a form, or transferring information between systems. Because they automate basic processes, RPA can offer significant cost savings for businesses, and they also deliver a level of accuracy that’s impossible with standard teams, by eliminating “human error”.
Of course, the abilities of a robot who only knows how to follow a strict structure, are highly limited. Processes automated through RPA need to be incredibly repetitive and rule-based but add “AI” and machine-learning to the mix, and you get something entirely different. By combining task automation technology with intelligence that allows this software to learn, evolve, and innovate, you create something that’s closer to real human performance. Spooky or what!
The Evolution of Robotic Process Automation
Today, RPA systems are restricted to basic processes. They can’t make decisions, or adapt to their environments, and there lies the real value of modern business. While the current software is brilliant in terms of what it can do and achieve on behalf of brands, the robots can only do exactly what they’ve been told to do in any instance.
While this does mean that processes are carried out accurately and compliantly, it also means that the potential for growth is missing.
The inability to learn from actions presents two serious issues for RPA, but both can be addressed by the abilities of AI. For instance, the first problem is that any robotic entity requires some manner of continuous data to help it perform. Structured data refers to the information in a database or spreadsheet. Of course, a lot of the data we use today isn’t structured at all, from customer emails to variable data like invoices. AI can transform unstructured data into structured data, making it easier for RPA robots to understand.
The other problem with RPA is that there’s no way for the technology to make important decisions or access judgement. The good news is that a type of AI called “cognitive reasoning” can be implemented to support the RPA process. With cognitive reasoning, AI systems can read the context of a situation and provide responses based on the most likely outcome. Adding AI to RPA systems frees the technology from its restrictions, and begins to set a path for the future of the digital workforce. I still shake my head at the options now available to us when it comes to automation; don’t you?
What Does RPA and AI Mean for Today’s Workforce?
Ultimately, RPA will transform the workplace landscape, leading to new requirements for different skill sets, and potentially eradicating the need for other kinds of staff who focus on more routine tasks and activities in a workplace. To begin with, the move into the digital workforce might start with employees using RPA to help them perform their tasks more efficiently. However, as AI and RPA converge, there will be less need for certain professionals in many industries.
The coming generations in the world of technological evolution will have a world-altering impact on the way that we do business across all sectors. In fact, there’s a risk that this combination of technology will help to determine which skills are taught in the future, and which people will have jobs, as well which will not.
Some of the industries that will notice the impact are evident, including those with many highly repetitive tasks like finances, healthcare, and accounting. Of course, we can only wait and see how significant the coming transformation will be.
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