Renewed value in being a Generalist in the Age of Generative AI

Welcome Back!

If you haven’t yet, check out my piece on gaming and preparing the next generation of white-collar workers.

This week, I’m diving into why the case for being a generalist remains strong. A recent report on the potential impacts of generative AI from McKinsey inspired me.

Hope you enjoy!

-Welty

Why I’m prioritizing being a generalist

It’s definitely not because I don’t know what I truly want out of my career yet…. Jokes aside, I’ve always been focused on being a generalist. Part of it comes naturally to me through constantly chasing new ideas, reading about a variety of topics, and ultimately joining a startup where I work in various roles.

I fundamentally believe this is the right approach to an early career. From a young age, my parents (the career educators they are) explained to me the virtues of a liberal arts education to establish a knowledge foundation that would make future learning more intuitive. In college, I took this approach by studying both business and sociology. In my first job as a consultant, I tried to work on engagements with different problems, in different industries, and for different clients. I wanted to be exposed to a variety of knowledge. I ultimately left consulting for a startup, because I felt an expectation to specialize in a topic at too young of an age, and in an area of expertise I was not interested in.

To me, being a generalist is all about flexibility of learning. The ability and desire to learn about new topics, understand how to approach learning something new, and becoming comfortable with the unknown is crucial. I’m confident that being able to flex into a new situation while maintaining a high level of intellectual curiosity will continue to set me up for success. I believe this is more important than ever given the expectations for ease of access to specialized knowledge due to the advancements in generative AI, and the corresponding changes in employment.

Generalists in the Era of Generative AI

The flexibility provided by being a generalist is valuable in the context of the expected changes to white-collar worker productivity in the coming years. By far the largest expected implication of the proliferation of Generative AI is the productivity increases to knowledge-workers. At a high level, generative AI could speed up tasks associated with research, brainstorming, analytics, and more. Historically, innovations in automation largely impacted blue-collar and back-office white-collar work. Consider the replacement of workers by factory line robots, and the automation of software workflows at banks. Instead, with this coming productivity revolution, McKinsey estimates that 75% of productivity improvements will come largely from Software Engineering, Sales, Marketing, and Product roles (Figure 1).

The implication of these productivity increases will likely lead to the shedding of jobs across these business functions. Much like how manufacturing employment has steadily declined as factories become more automated, more white-collar roles are now exposed to this kind of risk. Some companies have already started laying off employees due to improvements in AI, notably IBM with 8000 expected to be replaced, and Dropbox laying off 16% off its staff for similar reasons.

Moving from the business function level to specific work tasks, McKinsey finds that applying expertise, which we can think of as being specialized, stands as the activity with the highest technical automation potential across decision making and collaboration (Figure 2). Meanwhile, interfacing with stakeholders, a skill that typically benefits from a generalist mindset, is lower on the list.

Long Term Implications

As advances in AI continue, we can expect traditionally specialized roles to be cut, and worker expectations to increase from leveraging new AI tools. Of course, there is still uncertainty around exactly how these advances will impact work as we know it. To protect against this uncertainty, workers who build a strong generalist foundation early on are more comfortable solving a variety of problems and will be more equipped to handle the coming technological changes.

If you’re early in your career like I am, build a strong base to your skills using a generalist mindset, continue growing and adding new experiences to your belt, and hold off on specializing until you are confident enough to make a strong bet based on your core foundation of skills. Such a foundation will set you up for success in a continued period of intense technological change.

Have additional thoughts? Connect with me on Twitter and let’s chat about it! Make sure to share with your friends too if you enjoyed.