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Ask Gorick: “Will AI take my job?”

Last Updated:

June 5, 2025

Table of Contents

Welcome to Edition #25 of Ask Gorick Anything. This AMA is part of Gorick's Newsletter, where Harvard career advisor and Wall Street Journal bestselling author Gorick Ng shares what they don't teach you in school about how to succeed in your career.

→ Read time: 5 min

ASK GORICK ANYTHING

“Will AI take my job?”

Have a career question? Ask me here.

Subscriber’s question:

“I read your AMA on deciding, scoping, and doing and wanted to ask what you recommend for someone already in their career whose job may or may not be replaced by AI?

I’ve been in admin work for over 6 years at 2 different law firms. I am paid well and actually like it. But I know there are some things that I do that are now or soon to be replaceable by AI. For example, the partners I work with always have me schedule meetings for them, but there are a ton of scheduling apps out there that would eliminate this task for me if they used them. What do I do? Am I just catastrophizing? How would I know the real risk of something like a single task (or my whole job) getting replaced by AI or not?”

— Amanda from Toronto, ON, Canada

Gorick’s response:

Hi Amanda,

Thanks for your question!

You’re not just catastrophizing. As you already know because you read my post from a few weeks ago, AI and automation are directly competing with “doing” jobs—just like the scheduling example you brought up.

So, how do you know you’re at risk for being replaced by AI—and what do you do?

First, use what economists call the “task approach” to analyzing the labor market. Then, not unlike what I told Daniela, look for ways to (A) do your job more efficiently and (B) be someone that people can rely upon.

How to use the “task approach” to see if you’re at a higher risk of getting replaced by AI and automation

One of my favorite frameworks for making sense of where the economy is headed is the “task approach” framework by MIT and Harvard economists David Autor, Frank Levy, and Richard J. Murnane.

It’s a 2x2 matrix that uses 2 dimensions to categorize all tasks one can expect to do in a job: (A) routine vs. non-routine and (B) cognitive vs. manual.

Routine tasks follow a clear, repeatable process (e.g., data entry).
Non-routine tasks require judgment, creativity, or adaptability (e.g., writing a novel, designing a new product).
Manual tasks require moving things or interacting with the physical environment (e.g., construction).
Cognitive tasks require thinking, analyzing, or decision-making (e.g., financial analysis).

Once we pair up the 2 dimensions into a 2x2, we end up with 4 quadrants—and, in turn, 4 types of jobs:

Routine manual like warehouse packers or dishwashers (who are putting items into the correct bin or washing dishes over and over)
Routine cognitive like customer service reps or data entry clerks (who are following a script or inputting numbers into a database)
Non-routine manual like movers or plumbers (who are moving furniture of different sizes from and to different places or crawling under the sink to fix your drain)
Non-routine cognitive like management consultants or software developers (who are analyzing companies’ operational issues or writing custom code)

At this point, you can probably imagine for yourself which jobs are at the highest risk of automation (if they haven’t already been automated): the ones with simpler tasks that you’re also doing over and over again.

You probably also have an idea which jobs probably won’t be automated as quickly: the jobs that involve ever-changing circumstances or that require lots of human interaction.

If most of your work day is spent doing the same thing over and over without having to think much, you may be in a highly automatable role. A non-repetitive job that requires lots of creativity may still have automatable components, though.

The job automation matrix: the more repetitive and less complex a job is while also falling in the
“routine” and “manual” categories, the more likely it is to be replaced by AI/automation.

Let’s now return to your job as an administrative assistant.

Finding a suitable time on a law firm partner’s calendar may seem “routine,” but the instant the partner tells you, “I’m going to be busy next week, so only book meetings with important clients or people on my team,” is the instant that same task becomes non-routine.

Moreover, you offer your law firm partner (and their team and clients) 3 elements that no calendar booking app can replace:

The human touch
The sense of importance
The ability to get things done by asking (and not having to press any buttons)

#1 and #2 are reasons why fancy places still have people opening the door for you when you could have opened the door yourself.

“But what about Generative AI,” you ask? Can’t you just ask ChatGPT to tell you “How were ramen noodles invented?” rather than type “ramen noodles” + “history” into a search engine and dig through all the information yourself?

Yes! But every new technology has what’s called an “adoption curve” where the technology first reaches a few people (called “Early Adopters”) and then takes its time “crossing the chasm” to reach the masses.

*Research shows that “Early Adopters” are more likely to be younger people (ages 18-34).*

In the case of AI, sure, ChatGPT may have acquired users faster than any other piece of software in history, but the people who are using it most religiously and pushing its limits are students and hardcore tech people.

The “laggards”? Probably many of the law firm partners you work for (especially those who are still printing out documents to read).

So yes—your job will probably change, but, depending on how tech-savvy a place you work at, it could take some time.

What does this mean for you?

Look for ways to (A) do your job more efficiently and (B) be someone that people can rely upon.

→ Here are 3 questions you can ask yourself if you want to find efficiencies (inspired by the launch of ChatGPT’s international competitor, DeepSeek AI)

→ Here’s an exercise to help you hone in on your assets and strengths as a reliable teammate rather than as a replaceable cog in the machine (inspired by Orangetheory’s founder)

The more familiar you are with the tools that could ultimately put you out of a job, (A) the more effective you’ll be at doing your job while you wait for the laggards to catch up and (B) the more time you’ll free up to do the things that AI either can’t do, can’t do as well, or can’t do yet.

There’s plenty more to cover on this topic, so if you have any other questions, let me know!

See you Tuesday for our next story and unspoken rule,

Gorick

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