We’ve researched the market, answered the questions and corrected the misunderstanding for years now. In this post we gather and explain some of the most common myths about RPA and IPA.
False: While this is natural for someone non-professional to assume, this is not true. As the terms suggest, Robotic Process Automation is about automation and Artificial Intelligence is about intelligence. Where RPA robots base their actions on pre-defined rules, AI on the other hand can learn and simulate human intelligence.
One more constitutional difference is that RPA as a technology is process centric while AI is driven by data.
Mostly false: It depends on what you use and what you want to achieve. Basic RPA is relatively simple and people without programming knowledge can develop bots using drag and drop tools or “recorders”.
However, the better your skills, the more you can do with RPA. For example, if you master Python, you can create more complex, versatile, and impactful automations using open-source technologies, and at that point, one could argue that it is not easy anymore.
False: RPA itself will only become more important in the coming years. A report by Deloitte claims that 50 percent of the tasks performed by employees are mundane, administrative, and labor intensive, most of this could be automated with RPA.
So, that is about RPA itself. But when we add the other hyperautomation tools like BPM & Data Mining, AI, Advanced Analytics, and software development to the mix, then it’s a different ballgame. Hyperautomation will broaden the range of processes that can be automated by tackling increasingly complex tasks. This all translates to cost savings. As Gartner predicts, companies leveraging intelligent- and hyperautomation will reduce their operational costs by nearly 30 percent by 2024.
So, RPA is not outdated and hyperautomation (or Intelligent Process Automation) is definitely not outdated.
Mostly false: It is true that open-source tools don´t have a customer service hotline to call to, but on the other hand the tools have been developed and maintained by a global pool of developers. These libraries are undergoing a significant rate of usage and testing in various applications, which makes them robust and, in some ways, even more scrutinised than commercial tools. Technical support is also widely available in public online forums.
False: In many ways, open-source tools and libraries have been more rigorously tested than their commercial counterparts. These tools have been widely used globally in different applications with hundreds or thousands of different developers utilizing them in their solutions. A lot of developers support them, and FAQs can be found in different forums around the internet, which cannot always be said about commercial tools.
False: When RPA is implemented with the right tools and by experienced developers, it results in resilient business processes that leverage all layers of modern computer systems (APIs, data, UI, interactions).
False: Hyperautomation is about applying a comprehensive toolkit of validated and proven technologies to increase overall automation rate in an organization. What we’ve seen happen in manufacturing industries and factories, now comes into the office.
Partly false: Automation has been around since ancient Greeks and Arabs built machines to track time. Since that automation has changed the world and work many times, but never has it eliminated jobs in total. Even during the industrial revolution, people were able to find new, more meaningful jobs.
Now with the modern RPA taking over the mundane repetitive work tasks from humans, it is understandable to worry about the future. Even though the past is not a mirror to the future, the general belief is that RPA and automation in general will more likely, once again, change the way people work, rather than dramatically decrease the net number of jobs out there. Jobs will most definitely disappear, but new ones will also arise.