After reviewing workplace automation, you may be asking yourself whether you should consider it a positive or a negative thing in terms of employment. The answer is … that depends. Let’s look at the implications automation is having on the employment landscape.
The Automation Skills Gap
The rapid development of technologies like artificial intelligence (AI), big data, and machine learning (ML) has already been disrupting job roles and businesses. Then the COVID-19 pandemic came along and forced many companies to adopt these tech solutions almost overnight. According to Larry Clark, Managing Director of Global Learning Services for Harvard Business Publishing Corporate Learning, “There is a massive gap in organizations […] around basic awareness of the critical aspects of technology. These include data and analytics, AI & machine learning, process-enabling technologies, privacy, cybersecurity, and managing an online brand and market presence” (Spiceworks).
Automation is creating a greater need for people with strong soft skills like critical thinking, emotional intelligence, empathy, and communication. Edward D. Hess, author of Hyper-Learning: How to Adapt to the Speed of Change, asserts that, “Humans are going to have jobs [only] if they can […] think in ways that technology can’t and […] emotionally connect and relate in positive ways with other human beings” (TechTarget).
The perfect employee would appear to be somebody with an amalgamation of tech know-how and people skills. This mix of skills can be hard to find. An organization’s willingness to hire people with the right soft skills and then reskill and upskill them is very important. On-the-job training or continuing education programs to get employees up to speed in the new jobs that automation is creating needs to be part of the organization’s learning and development and HR strategies.
Job Demand Shifts
So what does this mean? In broad terms, workers who can perform tasks in harmony with machines or beyond machines’ abilities are in good shape. But workers who perform tasks that machines can docould be in trouble.
Specifically, robotics automation has created jobs for machinists, advanced welders, and technicians who maintain or use the machines. AI and ML has created jobs for programmers, software engineers/architects/developers, machine learning engineers, data scientists, business intelligence developers, research scientists, big data engineers/architects, and data analysts, among others (Springboard.com).
However, automation has the potential to eliminate millions of jobs for vehicle drivers, retail workers, health care workers, lawyers, accountants, finance specialists, and many other professionals (Brookings.edu).
In the face of rapid changes caused by automation in the workplace, it’s more important than ever for companies and L&D professionals to retrain displaced or under-skilled workers to perform new responsibilities in different or changing roles. More workers will need reskilling or upskilling, and organizations need to provide high-quality training in the economy’s high-demand sectors.
Along those lines, institutions should pay special attention to their DEI (diversity, equity, and inclusion) policy, as cohorts such as people of color, women, and older workers tend to be particularly underrepresented in tech fields (EE Times). With automation and technology as prevalent as it is, every industry is a tech industry from the standpoint of productivity and performance.