What’s the best job for robotic process automation?
Robotic process automation is one area of artificial intelligence that is getting a lot of attention as organizations looks to streamline processes and cut costs. But RPA isn’t right for some jobs, where human intervention and decision-making are still required.
Information Management spoke with Harel Tayeb, chief executive officer at Kryon Systems, about the growing interest in RPA and how organizations decide when and where to adopt it.
Information Management: Robotic process automation is getting a significant amount of press in the past 12 months. How do you see RPA most impacting the work done by data professionals – data scientists, data analysts and data stewards?
Harel Tayeb: As RPA systems progress and become more advanced, more and more professionals from different industries and fields will find use and advantage in utilizing RPA.
IM: What types of work is RPA most ideally suited for?
Tayeb: Organizations that rely on labor on a large scale for general knowledge process work, in which people perform high-volume, highly transactional functions, will Improve process efficiency, reduce costs and eliminate human error with robotic process automation (RPA) software.
RPA can be effectively deployed to handle many different types of tasks in the workplace, all of which can be characterized as being high volume, repetitive, and manual. For example, the technology can help add efficiencies to enterprise applications such as customer relationship management, ERP, supply chain management.
Human resources, finance and back office processes are ideal candidates for automation in any industry, and the technology is only now beginning to explore its own potential to maximize workforces and bring work efficiency to the next level.
IM: What is your sense of how widely RPA is really used right now and what are the latest forecasts for the growth of this technology?
Tayeb: RPA is a relatively young technology that’s being used for the execution of rote tasks by enterprises in the finance and insurance industries, but now is the early stage of RPA’s development as a powerful tool for companies hoping to raise their bottom line.
Adoption is currently among larger corporations, and RPA hasn’t yet reached smaller enterprises or non-traditional sectors that could benefit from RPA. Even the enterprises that are experimenting with RPA are selectively testing them before rolling it out to the rest of their departments, so you’ll be seeing enormous growth for the market over the next few years, with projections reaching as high as $8.75 billion by 2024.
This is all before you consider the technological advancements occurring today that will influence the scope and capabilities of RPA such as artificial intelligence and propel this growth even further.
IM: There has been significant debate on the impact that RPA will have on jobs – job killer versus job creator. What types of jobs are most threatened by the rise of RPA and what sorts of jobs is RPA likely to create or bolster?
Tayeb: RPA, and in fact all automation or robotic innovations, are part of the future of the workplace, but that workplace will always involve human employees as well. It is not a tool used to simply replace human employees, rather to empower them to focus on tasks that require their unique skills and capabilities that cannot be automated.
While certain jobs like data entry may become automated, many more jobs will be created—particularly directly stemming from the advancement of RPA technologies, as has always happened with the introduction of new means of economy and production.
IM: In an industry in which RPA is in significant use, what skills are most likely to benefit the data professional to ensure their value to the organization, and their survival and growth professionally?
Tayeb: It is important to remember that the integration of RPA is about having “virtual workers” take care of tasks that are routine and repetitive, to benefit employees and the business as a whole. As tasks that require minimal skill sets are removed from a company’s workload, emphasis will be placed on increasing the number of employees skilled in newer fields, such as analytics, cloud services, as well as robotics and automation management.