How to Stay Relevant and Succeed in Your Career in the Age of AI
by Kashyap Kompella
A specter has been haunting workers—the specter of mass unemployment due to automation. In 2013, two University of Oxford academics published a paper, “The Future of Employment: How Susceptible Are Jobs to Computerisation?” It claimed that 47% of American jobs were at high risk of automation. In its wake, there were several other studies that echoed similar sentiments, adding to the angst and anxiety of employees everywhere about impending mass job losses.
| I recommend that you take a step back and remember that AI (at least for the foreseeable future) is another technology that you can leverage.
Fast-forward 7 years, and unemployment levels are at record lows in the U.S and in several countries across the world. In 2020, there is a realization that fears of massive job losses due to AI are overblown. At the same time, there has been significant (even several orders of magnitude’s worth) improvement in the capabilities of narrow AI—i.e., systems that are designed to handle a single task. Investments in AI technologies continue at a fast clip, and enterprise adoption of AI is also growing. The nature of existing jobs, job routines, and job descriptions is changing—more so for knowledge workers, whose jobs are likely to require a greater degree of technological proficiency.
WHAT TO LEARN
Against this backdrop, how can nontechnical professionals stay relevant? There is a school of thought that everyone should learn to code, but I don’t share that belief. It is not very practical—there are about 25 million (professional) developers in the world, according to Evans Data Corp., while the number of knowledge workers, according to Gartner, is around 1 billion.
There is also a great deal of interest in enrolling in an online AI course, and “What AI course should I take?” is a question that I often get asked. There is no dearth of resources for learning about AI, and nontechnical professionals can thrive by focusing on the applications and implications of AI for their businesses. I recommend that you take a step back and remember that AI (at least for the foreseeable future) is another technology that you can leverage in your organization’s business processes and products. So you’ll want to gain an understanding of how AI systems work, what they excel at, and what their limitations are. AI can seem daunting because of the technical terms or jargon, but once you learn the terminology and what it means in plain English, AI concepts are much more accessible.
WHERE TO LEARN
You’ll also want to keep an eye on key AI developments related to your line of work (for example, unless you work in that industry, self-driving cars are fascinating, but they are not likely to affect your work relative to a software bot that automates scheduling meetings). Keep track of what AI capabilities are being added to the software stack used in your organization. Follow what technologies your industry peers are investing in. Notice the AI startups in your industry and where venture capital is being deployed. These are leading indicators of innovation that your organization can potentially tap in future years.
Industry conferences are an efficient and effective avenue to stay abreast of such trends. Remember that even if your organization does not have the budget for conference participation or you can’t attend in person, you can still partake in conference live streams, video recordings, event write-ups, and social media.
STEP UP IN YOUR ORGANIZATION
Just as there is a huge demand for technical experts to build AI systems, there is an equally large demand for nontechnical professionals who can help their organizations better harness AI. If you follow the suggestions outlined here (and add to them with your own organization-specific experiences), you’ll soon become a go-to person in your company and be invited to contribute to its AI initiatives.
You may have noticed that I have not made specific recommendations for skills that you should pick up; instead, I have outlined a practical, top-down approach. This is applicable not just to AI, but to other technology domains as well. In fact, it’s a playbook for mastering the ability to learn continually and adapt to change. Today, the useful shelf life of skills is getting shorter. In previous generations, organizations took more responsibility for training employees, but now the onus for reskilling is shifting to the individual. Adaptation is perhaps the most important skill of them all as AI rewires the future of work.