In recent years artificial intelligence has been gaining more and more popularity. Companies have started looking towards it as something that can help them to continue growing while keeping costs under control. According to McKinsey’s State of AI report, 50% of the companies are already using AI for at least one business function. These companies plan to invest even more in automation and digitalization as a response to the COVID-19 pandemic economic crisis. This trend raises a concern among employees whether their job will be automated, and if a robot will be doing their job soon.
While science fiction has made us think that there are only two scenarios for robots – to help us or to destroy us – now that the robots are becoming part of our daily life we realize that they are not here to destroy us but to disrupt our work (HBR, 2021). Thanks to Robotic Process Automation (RPA) a lot of the repetitive processes are now assigned to robots. From data entry, report creation, to providing first-level support to clients, robots are now taking over the tasks that require a low level of skills – those tasks that are usually given to entry-level employees. And while that may sound like a trend that should bother college graduates, it will actually create more opportunities for them as according to the World Economic Forum Future of Jobs Report 2020, 85 million jobs may be displaced by the shift in labor between humans and machines by 2025, while 97 million new roles may emerge.
How does RPA work?
Robotic Process Automation (RPA) could perform manual repetitive tasks that follow a step-by-step (trained) process. It is comprised by computer-coded pieces of software, also called robots or bots, that are developed to mimic human actions by executing a sequence of steps to produce meaningful outcomes without human intervention in that process. It can work across different functions and almost any system without the need for change in the existing infrastructure or underlying systems.
For RPA to be able to imitate human execution of mundane processes via the existing user interfaces, it needs to be trained first. During the training, an RPA developer teaches the robot how to execute the process – the same way as they would teach a new employee. Once the robot is trained it can not only start executing the process on its own faster, with greater accuracy and 24/7, but also propose improvements in the process. RPA can also discover processes that can be automated via RPA.
This all might sound scary for employees, but the purpose of implementing RPA most often is not to replace employees with robots but to make employees time available to perform more value-adding work, providing a critical support framework across the organization. By assigning repetitive, mundane tasks to a robot, employees’ productivity is optimized. For example, when an employee in a contact center receives a call, they need to check multiple systems to gather the information they need before even they can ask the client what the problem is. During that time the client is usually put on hold, so when the employee is finally able to ask what the problem is the client is much angrier than they originally were. This is not the only effect – the longer the call is, the longer the next client waits until they can connect. According to Forbes, 96% of customers leave because of poor customer service. In this case, RPA can provide useful data, in a matter of seconds, increasing the speed and quality of the customer service.
Worries of Job Elimination
If history has taught us anything it is that disruptive paradigms shifting business models not only create new opportunities but also lead to some practices becoming obsolete or inefficient anymore. Yes, robots will replace humans for many jobs, but humans will be needed to create value and deliver value in brand new ways as brand-new business models emerge. The goal behind RPA implementation in most cases is not to reduce the workforce but to allow companies to scale. There are so many companies heavily investing in AI, but this doesn’t mean the doom resides in these trends. While machines are good at performing routine rules-based cognitive tasks, they cannot replace people in their innovation, creativity and human interaction which is needed in many jobs.
Automation and AI will inevitably transform the way work gets done but they will not completely replace the human workers. “Up to this point, technology has created more work because it’s another thing you have to deal with,” says Justin Adams, formerly CEO at Digitize.AI and a vice president at its new Chicago-based parent company Waystar. Even to deliver this technology usually a lot of people are needed. Yes, some of these people would need new skills, but when we look at AI, there is a growing need for training, data, maintaining and managing expectations – and all that is done by humans
Changes in How We Work
Gigaom CEO Byron Reese predicts in a recent article that AI will be “the greatest job engine the world has ever seen.” As technology lowers costs, people respond by one of two things: They either buy more of the item (as banks did with branches) or they spend their saved money elsewhere, creating new jobs in those areas. This means that AI will create many jobs that are now beyond human imagination, but also help some jobs develop even better.
The results of research by Dixon et al. (2021) at Wharton University suggest that robots do not affect employment within the firm uniformly, leading to net increases in the headcount of non-managerial employees, but also decreases in the headcount of managerial employees, especially middle management. AI and RPA are already able to do the administrative tasks that consume most of the managerial time. According to research performed by Accenture, 54% of the tasks performed by managers are administrative tasks, or in other words, tasks that can be automated.
Figure 1 – How Managers Spend Their Time (Source: HBR.ORG)
Taking that load away from managers doesn’t mean that the managerial profession will disappear, but that as many others they must focus on developing those skills that cannot be automated. According to HBR.ORG in the world of AI and automation managers should focus on judgment work – applying their experience and expertise to critical business decisions and practices. But they should not get into the trap of competing against the machines, but rather accept the robots as their new colleagues, as machines can add enormously to judgment work, assisting in decision support and data-driven simulations.
For non-managerial roles, however, skills gaps continue to be high as in-demand skills across jobs will continue to change in the next five years. 94% of business leaders report that they expect employees to pick up new skills on the job according to the World Economic Forum Future of Jobs Report 2020. As RPA and AI take over the work that requires low-level skills, skills, and education requirements in the sectors that require human force may need to be higher than the level needed for the tasks displaced by automation. Any predictable type of work can be performed by the machines, however unpredictable work, like teaching, problem-solving, marketing, etc. will not be affected by automation too much. This trend raises another concern – what will the graduates do? Coming out of college with no experience in an environment scarce of low-skills job opportunities means that graduate students would have to become experts in their industry before graduation and be ready to generate value for the company. This means that a change in the educational system would be needed, too.
In conclusion, while AI and RPA are disrupting the way we work, their goal is not to reduce the workforce, but to allow businesses to scale. Transformation of the way we work is inevitable and skillful workers will continue to be in demand. Those who are willing to invest in their ongoing learning and development will continue to flourish.