Robotic process automation (RPA) is emerging as one of the most effective tools for businesses looking to maximize efficiency and to cut down on costs. With RPA, you can use artificial intelligence-enabled technology to automate repeatable, high-volume workflow tasks, thus freeing up your employees and allowing them to focus on more challenging work.
McKinsey & Company has concluded that RPA will have a total economic impact of $6.7 trillion by 2025. In fact, McKinsey believes that such automation software will have a bigger impact than many other “hot” industries, including 3-D printing and autonomous vehicles, and may only trail mobile Internet for phones and tablets.
RPA has become one of the most talked about topics in automation over the last several years. While RPA is relatively new, the foundational technologies it’s built upon have been around for years.
Optical character recognition (OCR) has been in development for over a century, although it’s evolved rapidly in the last few decades. Screen scraping software emerged in the 1990s, while workflow automation software has been in use even longer. Artificial intelligence has been a topic of discussion for decades, although many major breakthroughs have occurred over the past several years.
Many RPA programs rely on the above technologies. Meanwhile, the term “robotic process automation” was first coined in 2000. By leveraging screen scraping software, workflow automation software, and AI, it soon became possible to replicate human interactions with digital systems.
RPA’s technological capabilities are increasing every day while developers continue to replicate complex human interactions and activities. Already, basic RPA programs can accomplish a host of “simple” tasks, such as pulling out structured and semi-structured data, filling out forms, and logging into applications. RPA programs can also move and copy files, scrape data, and more.
RPA will likely become more prominent and powerful in the coming years. First, the technologies that underpin RPA are continuing to evolve at a rapid clip. Screen scraping software, AI, and workflow software have all advanced by leaps and bounds in recent years. This will accelerate the development of RPA.
AI, in particular, could have a major impact on determining how RPA is deployed and what it is capable of. Many of the tasks automated by RPA may seem simple, but for software programs, the tasks can be immensely complex. As AI becomes more robust and is better able to learn and interact in dynamic environments, it will be able to handle increasingly complex tasks.
Automation software has typically been limited to rule-based processes where no deviation is expected. This has greatly limited what can be automated. However, once equipped with AI, RPA software may be able to handle exceptions. This should allow for many more tedious processes to be automated.
Machine learning could also prove vital for RPA. A type of artificial intelligence, machine learning allows software bot programs to learn on their own. This could prove to be especially important for RPA. If software can learn from changing conditions, mistakes, and more, it’ll be able to adapt and enhance its efficacy.
Meanwhile, more companies, entrepreneurs, and investors are focusing specifically on RPA software, recognizing its potential. This should yield even more creative software solutions. RPA is also expected to have a dramatic impact across most industries, including human resources, medicine, and more.
Currently, many RPA programs focus on automating just a small part of a given process. However, as technology and software advances, RPA solutions will be able to automate an increasingly large part of the process.
For companies, more advanced RPA solutions should make business processes much more efficient. RPA also eliminates human error and is especially appealing as it can eliminate tedious bottlenecks, such as processing forms.
As employees are freed up from such tasks, they can shift focus to more complex challenges, such as working one-to-one with customers. This should increase productivity and could boost employee morale, which could then lower turnover.