The Jobs Implications of Robotic Process Automation

By Thomas H. Davenport

Robotic process automation (RPA) is probably familiar to you if you’re reading this on the Blue Prism website. I view it as a flexible, easy-to-implement tool for automating and performing digital tasks. For reasons I don’t entirely understand, it’s being adopted more rapidly in Europe and Asia than in the United States, but that probably has something to do with Blue Prism’s UK origins. I expect that will change over time, however, and that the U.S. will catch up.

I’ve just co-authored a new book (called Only Humans Need Apply: Winners and Losers in the Age of Smart Machines) about the implications of various cognitive technologies on human jobs, so the effect of RPA on those jobs will be my focus in this post. The book is primarily focused on the impact of technologies that think and learn, and RPA doesn’t really learn yet. But I think it will over time, and it’s already as smart as many of the “expert systems” that achieved considerable usage in industries like insurance and banking over the last decade.

In comparison to technologies like machine and deep learning that get a lot of attention in Silicon Valley, RPA is much easier to implement, and doesn’t require a Ph.D. data scientist to create or oversee. It also tends to provide faster and higher levels of ROI than other cognitive technologies. That means that it will continue to catch on quickly.

So what does this mean for the humans who do the jobs that RPA takes over? Well, that’s a complicated subject. First, RPA, like other machines, performs tasks, not jobs. As it performs more and more tasks, it probably will eliminate some human jobs altogether—though probably not massive numbers of them.

Secondly, the digital tasks performed by RPA are not generally that fulfilling to us humans. Some of the companies I’ve spoken with or read about who have implemented RPA found that their employees were happy to turn over these tedious activities to machines—particularly if they were able to keep their jobs and focus on more challenging and interesting tasks.

Third, thus far the primary impact of RPA on jobs has been on outsourced workers. If you can outsource a process—particularly to a distant offshore provider—you can probably perform it with RPA. While this is not a positive thing for the economies and societies of places like India and Eastern Europe, it has fewer negative effects on the situation at home.

Fourth and finally in this list of factors to consider, there are jobs to be had in working alongside RPA. Our book is primarily about five ways that humans can augment the work of smart machines (rather than being entirely automated by them), and a couple of the five are specifically applicable to RPA/human collaboration. There is the “step in” role, in which humans work day-to-day with an RPA robot, monitoring its performance and stepping in when it can’t handle a particular task or exception. There is also the “step up” role of overseeing automation at a company, and thinking about whether more or less of it is needed in a particular situation. Several of the companies I’ve interviewed that have made substantial commitments to RPA have established roles of this type.

For individual workers affected in some way by RPA, it’s pretty clear that the best thing one can do is to learn how RPA works and how to add value to its operation. For organizations implementing RPA, it’s important to make clear that humans won’t lose their jobs just because of RPA or some other smart machine. That will free up people to be creative and enterprising about how to use automation technologies to make their organizations more successful.

With RPA its now apparent that the robots aren’t just coming; they are already here, and they are eminently capable of working in white-collar environments as well as factories. There will undoubtedly be some effect on the jobs that we humans have historically thought of as our own, but an optimistic and enlightened perspective on these technologies can minimize the negative implications and enable more creativity and job satisfaction in those jobs that humans continue to perform.

Thomas H. Davenport is the President’s Distinguished Professor of IT and Management at Babson College, a Fellow of the MIT Initiative on the Digital Economy, and a Senior Advisor to Deloitte.