How to Keep Up with AI At Work (Without Losing Your Mind)

**Ryan Knutson** (0:08)
Recently, I called on my colleague, Callum Borchers, to talk about AI in the workplace, in our workplace, The Wall Street Journal, and workplaces in general. Do you use AI for work?

**Callum Borchers** (0:19)
You know, I do. Maybe less so than some folks. I mean, probably it's most helpful during our headline brainstorming session. You know, my editor and I often use it, in fact, he jokingly refers to it as the intern, and I think that that's often a good way to think about it.

**Ryan Knutson** (0:38)
I tend to use it mostly like a research assistant, like a way more helpful version of Google. And I've gone to some newsroom training sessions about harnessing its potential while avoiding its pitfalls. This is probably where a lot of people are. You're hearing about it at work, you're dabbling a bit, but man, what exactly are we supposed to do? Callum's been talking to people on all sides of the AI conversation at work, both employees and bosses. His column, On the Clock, is about people's careers and work lives.
How would you describe people are feeling about it?

**Callum Borchers** (1:15)
Uneasy, I think, is the word that comes to mind. I mean, I think that for every worker who sees some time savings, who sees some opportunity, there's another worker I talked to who feels really threatened by AI. And frequently, those feelings co-exist within the same person.

**Ryan Knutson** (1:36)
So how can you use AI at work in a smart way? What are the tricks and tools that are worth your time? Is it worth your time? And how do you stay sane in AI frenzy?
From The Journal, this is Work Mode, a special series that will air over the next four Sundays, where we take a look at how work is changing. I'm Ryan Knutson, let's get to work.

**SPEAKER_4** (2:13)
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**Ryan Knutson** (2:52)
So one of the things that's motivating people to learn AI, obviously, is the risk that they could be replaced by AI, and the risk of layoffs.

**Callum Borchers** (2:58)
Sure.

**Ryan Knutson** (2:58)
How real do you think that threat is?

**Callum Borchers** (3:00)
In the short run, the risk is relatively low for most professions, because most of the tasks that AI can do still require human oversight and monitoring. That very well may change in the coming years, but I look at the so-called AI layoffs of recent months with a degree of skepticism because-

**Ryan Knutson** (3:25)
These are all the companies that are saying, oh, we're reducing our workforce because of these AI advancements.

**Callum Borchers** (3:29)
Well, that's right. I mean, there's a great incentive on the employer's part to look like you're ahead of the curve, that you're some kind of AI genius. It's a whole lot better to tell the public, to tell your investors, oh, we've achieved some efficiencies through AI and we need fewer people.

**Ryan Knutson** (3:49)
Hypernaut, AI is here and it's getting smarter every day. What would you say to somebody that is not thinking about AI right now, and just sort of saying, I don't need to bother with this.

**Callum Borchers** (4:02)
I guess I'd ask, where are you in your career stage?
If you're five years from retirement, maybe you can get away with it, right? You figure, okay, is it really worth investing all this time? I've got a pretty short runway left. Maybe you can ride it out. If you're 25, my advice would be a little bit different.

**Ryan Knutson** (4:22)
What would your advice be for somebody who's 25?

**Callum Borchers** (4:24)
Gosh, I mean, take a breath, for one thing. I mean, I think it's, yeah, very good. It's exciting, it's a little nerve wracking, but I just think that none of us makes our best decisions amid a panic.

**Ryan Knutson** (4:38)
Now that we are all calm and not in a panic, Callum says his biggest piece of advice from the outset is that you need to lean into your human skills, the things AI can't do, and maybe will never be able to do.

**Callum Borchers** (4:50)
So it's communication, it's critical thinking, it's being a reflective person, right? Somebody who is able to say this went well or this didn't well and why, and what do I learn from that to do better the next time? It's being able to be that AI editor or manager who can, you know, not just accept at face value the AI output, but also evaluate, you know, its quality. I think those are the kinds of skills that will continue to be in demand down the road, more so than any particular job title, which may or may not exist in the future.