Recent strides within the data science technology field have left many people interested in artificial intelligence, machine learning, and RPA. Artificial intelligence and machine learning techniques have been around for years. It is easy to spot artificial intelligence on a daily basis in our Netflix queue, Amazon recommendations, targeted ads, and self-driving cars.
Machine learning is actually what makes artificial intelligence possible. Machine learning is a type of computer science that utilizes mathematical algorithms and data mining to imitate the process through which humans learn. Humans learn through a collection of past experiences and reinforcements the same way machine learning uses historical data and reinforcement training. So what is RPA? How does it relate to AI?
RPA stands for Robotic Process Automation. The term RPA refers to the software technology that creates and deploys simulated human intervention in digital systems. In other words, RPA automation can accomplish simple tasks and decision-making processes that do not require empathy or human interaction. For example, robotic process automation software can process and understand on-screen information, execute keystrokes, and identify which items within a large volume of data are essential.
This automation of mundane tasks decreases the need for human intervention within the overall data management process. When unattended robots can accomplish business processes like data entry and filing, many data governance and analytical systems become streamlined.
Robotic process automation is not meant to replace the careers that humans hold. Robots cannot make decisions involving empathy or human judgment. Intelligent automation eliminates time-consuming and mundane tasks that do not require human interaction. To get through arduous or boring tasks, many people have to take breaks or parse out their work overtime not to feel fatigued or bogged down by repetition.
By eliminating these tasks, human employees can focus their efforts and attention on collaboration and creativity. Robotic process automation can boost employee morale by removing those monotonous tasks that don’t necessarily require humans.
Artificial intelligence techniques enable robotic automation. By inserting artificial intelligence techniques into machine learning models, we can determine areas of application for robotic process automation. In other words, AI and RPA are very closely tied to one another.
There are some key differences to observe when comparing these two systems, despite the fact that both of them are often viewed as a form of technology that replaces human labor. AI technology collects and processes unstructured data to use for logic development. Whereas RPA is inputted with structured data and logic that it then uses for its automation processes.
AI and RPA technology is not limited to data scientists or programmers anymore. You can find a variety of data science technology information and resources on TIBCO’s website – an industry leader in data science software. They offer low-cost software licensing and valuable insight regarding how business intelligence practices can positively impact your organization. RPA technology is user-friendly, non-disruptive, and operable from a centralized location. Additionally, the software “bots” do not require any programming expertise to manage.
RPA workflow can save your employees from tedious tasks, skyrocket productivity, and eliminate mistakes that arise from human errors and biases. Data science technology has been helping to streamline business processes for decades. If you are considering adding RFA to your current business model, it can be beneficial first to outline the areas of your organization that weigh down the human workforce.
Departments that handle accounting, risk management, and data entry tend to have the most significant data input and output volume; you may consider starting there. What will your organization do with all the time it has saved with RPA?