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

0:08Ryan Knutson: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? 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. 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.

0:49Ryan Knutson: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? Uneasy, I think, is the word that comes to mind. I mean, I think that, you know, for every worker who sees some time savings, who sees some opportunity, There's another worker I talk to who feels really threatened by AI. And frequently those feelings, you know, coexist within the same person.

1:36Ryan Knutson: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 the AI frenzy?

1:52Ryan Knutson: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 Knudsen. Let's get to work.

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2:51Ryan Knutson: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. Sure. How real do you think that threat is? 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— These are all the companies that are saying, oh, we're reducing our workforce because of these AI advancements. Well, that's right.

3:30I 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, right? 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.

3:49Ryan Knutson:Hype or not, 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, ah, I don't need to bother with this? I guess I'd ask, where are you in your career stage? You know, I mean, if you're five years from retirement, you know, maybe you can get away with it, right? You know, you figure, OK, is it really worth investing all this time? And I've got a pretty short runway left. Maybe you can ride it out. You know, if you're 25, you know, my advice would be a little bit different. And what would your advice be for somebody who's 25?

4:24Gosh, I mean, take a breath, you know, for one thing. I mean, I think it's, yeah, very good, good, good. You know, it's exciting. It's a little nerve wracking. But I just think that none of us makes our best decisions amid a panic.

4:37Ryan Knutson: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. So it's communication. It's critical thinking. It's being a reflective person, right? Somebody who's 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 not just accept at face value the AI output, but also evaluate 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.

5:25Ryan Knutson:With those human skills, we'll be doing a lot of evaluating of what AI spits out. If you use AI to write an email or analyze a spreadsheet, you still need judgment to decide what to do with that information. Callum says the AI future means we'll need to rethink how we define ourselves at work. I think a good way to think about it is that we're all managers now, right? You may not have direct report humans coming to you, but if you're outsourcing any of those tasks to a bot, you're now the manager. And so I think that's a skill in its own right, right, is that ability to critically evaluate somebody else's output and judge it to be good, bad, somewhere in the middle, need some tweaking.

6:10And so I think that is going to be a big test, I think, for a lot of people because a lot of rank and file workers don't fancy themselves managers. But really, you know, mentally, you need to function more like that.

6:22Ryan Knutson:So for people that work in a white-collar job and have not really dabbled with AI much but feel like they really need to get on the bandwagon, how do you recommend that they start to approach this? Like how should they learn about it and how should they get up to speed and start using it? I think one way to start is kind of comparing notes with coworkers, right? I mean sort of every workplace or many workplaces kind of have the sort of informal go-to. as somebody who kind of has good tips and tricks for one another. And often that person is a really, really good resource. So sort of ask like, hey, is anybody using AI?

6:57Ryan Knutson:Anybody got any good ideas out there? Let me try to learn from you. Exactly. I think that's a really great way to start, partly because it's also going to be very role-specific. Knowing exactly how AI can be applied to your job can also guide what kind of AI skills you focus on learning. Callum says that sites like Coursera and LinkedIn are full of courses that for most people are too generic to apply to their particular jobs. Be really targeted in what you spend some time training on, right? So it's not just a generic AI 101, but it's AI for attorneys. It's AI for accountants. It's finding something that is going to be really specific to your job.

7:36I guess both the job you have now and also where you want to go.

7:40Ryan Knutson:So there's like a whole range of ways that people can use AI from like writing emails to like building sophisticated agents that do half your job for you. Where should people begin? Yeah, I mean, I think you sort of nailed the spectrum. I mean, on the low end, it really is just kind of using it as an assistant, thinking of it as the intern, something on the side that works with you all the way up to kind of like a fully autonomous agent or kind of a duplicate of yourself. I think the tricky thing though about the high end of that spectrum is you need to continue training it. As you implement AI into your work, there are certain pitfalls to avoid.

8:17Ryan Knutson:Like because AI writing can be easy to spot, it can make your coworkers cringe if they notice you're using it. It can hallucinate, so you've got to be sure to check its work. And then there's what it does to your brain. For example, I'm thinking of a story I did recently about people who kind of fret about sort of automating all the busy work out of their careers. And so in the short run, yes, it saves me from some data entry, saves me some menial tasks that aren't all that stimulating. But at the same time, some of those folks also told me it's in those sort of quiet, repetitive task moments when sometimes they have an epiphany.

8:54And so it's sort of this give and take. Because I think if we're honest with ourselves, we can only spend so much time really in deep thought. I mean, we do need mental breaks. We want to guard against burnout.

9:06Ryan Knutson:So if workers are able to get better at AI and outsource more of their work to AI, how should they talk to their bosses about it? Because on the one hand, they might want to brag about it and be like, look how great I am. I'm an AI superstar. But on the other hand, if they are too open, their bosses might be like, great, you've got all this extra time and I'm going to put more projects on your plate. So how do you balance that? I mean, what I have found when I talk to people about this is it sort of depends on the industry. So like salespeople, right, is a good example. When I talk to salespeople, they're not shy, right?

9:38They'll tell you everything because they reap the rewards, right? Right. So if AI makes them better, if they generate more leads, I mean, that's a good example, right? They're trying to sell more stuff. And if they can sell more than another guy, they're going to make more money.

9:50Ryan Knutson:And so it's sort of clear, like, it doesn't matter how they want it, they go for it. Exactly. So there's an incentive there. Great. If I can do more, you know, my commission goes up. So, you know, those kinds of roles. I think what I'm curious about is whether some of these other white collar professions, a lot of professional services firms, I mean, like, quite literally, it's billable hours, right? Like, it's the hours that are the measure of what you earn. And if suddenly your week is fewer hours, yeah. Yeah, what's your incentive to reduce your billable hours, right? So I think one thing for companies to figure out, or maybe entire industries, is like, how do you structure the incentives for your workforce so that they want to kind of raise their hand and say like, yep, this is what I'm able to achieve.

10:31Ryan Knutson:And Callum says a lot of workers are raising their hands. He calls them AI power users. And they're impressing their bosses and leaving co-workers in the dust. And I think that the biggest thing that distinguishes them is experimentation. It's the lay folks who have just spent some time experimenting. And so what they do is just a lot of trial and error. The power users are very good about tailoring their prompts and then following up, right? Instead of just taking that first draft or being disappointed because it didn't live up to your expectations, you come back and you re-prompt, hey, that was good.

11:06can you make it shorter? Hey, that was okay. Can you tailor it to an executive audience? But the folks who I talked to who were probably most excited were folks who were kind of had an entrepreneurial streak, you know, and so they were either using AI to do the tasks of, you know, two or three people as they were trying to get a startup off the ground.

11:30Ryan Knutson:After the break, one AI power user on how he did it and made a lot of money in the process

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12:24Ryan Knutson:So how would you describe right now your relationship with AI? I'd say AI is, it's my coworker. It's my co-founder. It's my best friend. It has enriched my life by, I'd say, speeding up work, opening new opportunities and new doors, and giving me access to information faster and better than I could have ever had before. Michael Rookroot loves AI. And he says it's totally changed the way he works. He's a marketing director for a hospitality company in Salt Lake City. When Michael first started experimenting with AI chatbots, he was floored by the potential. It was a surreal moment. It was honestly magical.

13:05It was the first time you were engaging with something that felt a bit intelligent. And by the way, I don't have a technical background. I didn't go to school for computer science.

13:14Ryan Knutson:I was going to ask, you were never a developer or anything like that? Never have any coding experience? No. I could do like some HTML code, right? I'm sure back in the day, like MySpace pages, you know, a little HTML here and there. I can make this page green in the font italics. Boom. Michael integrated AI into his life by building an array of AI projects using Claude, the AI chatbot from Anthropic. Each project becomes an expert in its particular area because Michael can upload documents to it and give it feedback. And it remembers and gets better the more he uses it. Those projects act like coaches that help Michael manage different aspects of his life.

13:55Ryan Knutson:He made these coaches for all sorts of things. He built a fitness coach that knows his diet and fitness routines. He's got a financial coach, which has access to his portfolio. And he's also got a career coach. For example, my career coach helped consult me on this conversation. What did it say? What did it advise you to do? I mean, first of all, it said it's a great opportunity. And it advised me on... And it said Ryan Knutson is the best podcast host in the world, so... It did. It actually looked you up.

14:27Ryan Knutson:The biggest impact has been at work. In his marketing job, Michael oversees a number of hotel and ski resort brands. I have projects set up for each of them. And so if there's work for a hotel or a ski resort, I could take it directly to an AI. You call it like an agent that has been pre-trained on that business. It knows the brand, it knows the goals, it knows the objectives, it knows what we're working on. So he could help me just like rapidly work faster. Michael started playing around with AI in his old job. when he worked in the marketing department for one of his company's sub-brands, a ski resort in Utah called Snow Basin.

15:04Ryan Knutson:For example, every week, Michael had to write a report on how customers felt about their experience at the ski resort. He would take data from surveys, reviews, and general feedback, and he'd break it down into actionable items that would improve the customer experience. It would take me probably three or four hours to kind of go through, understand what is the pulse of the customer, and I would take the data and see kind of what changed week over week, and I would send out an executive summary to our management team and I would present on it in management meetings. And this is the first thing I built, essentially an agent for.

15:36I called the agent Monty, Monty the Moose, which the Moose is like our de facto mascot at the ski resort. We have a big moose statue on the plaza.

15:44Ryan Knutson:Love Moose, yeah. Love Moose. So I built Monty and I fed it probably 30 different reports and emails I had written about this. So I'm like, hey, here's the data. Here's how I've done it. You've seen it 30 times. I need you to do this for me. And at first it did it with maybe 80 % accuracy. It wasn't that great, but it would get me there. And it gave me a little bit of a head start. And then as AI models continued to improve, it got better and better and better. And to the point where last winter, Monty got so good that Monty was coding little video games in the reports and adding little Easter eggs to keep people engaged and started turning it into interactive web dashboards.

16:21And you give it a goal and it really took it far beyond anything I ever used to do.

16:27Ryan Knutson:Michael started to turn to AI to solve other problems at work. And in early 2025, he had a breakthrough. This ski resort, it's called Snow Basin Resort, was largely unknown. Kind of like a hidden gem ski resort. And we had built the brand into being ranked number one by several leading media outlets, like Ski Magazine, Outside Magazine, and so forth. But despite that, Michael noticed that when he asked an AI chatbot to recommend ski resorts in the U.S., Snow Basin didn't really show up, which is a problem when more and more people are turning to AI to build their vacation itineraries. Michael took it upon himself to figure out how to fix that.

17:07How can I reverse engineer this? How can I understand how AI makes that decision and start to position my brand in that pathway?

17:14Ryan Knutson:In other words, how do I get my brand on the top of these lists? When I asked a chatbot, what's the best ski resort? The one, my brand is the one that comes up top. Exactly. And what better way to reverse engineer AI than to ask AI to do it? In his free time, Michael used Claude, his favorite chatbot, to vibe code a piece of software to help him do this. First, he asked AI to create around 50 versions of the question, where should I go ski? And then he built a tool that asked those questions to all the chatbots and exported the answers into a spreadsheet. It turned out SnowBasin was only showing up in about 3 % of responses.

17:55Ryan Knutson:Then Michael asked Claude how the chatbots came up with those answers so he could try to fix it. And then he used his human skills, his expertise as a marketing director, to come up with some solutions, like specific media outreach, incentivizing customer reviews, and updating the Snow Basin website to make it more AI-friendly. In the end, his AI mind meld worked. The ski resort went from showing up in 3 % of responses to 33%. Michael posted the software he built on LinkedIn, thinking it might be useful beyond a specific company. And so I put it out on LinkedIn saying, hey, I built this thing and I want to test it on some other businesses.

18:35Free of charge, I just wanted to get some feedback and see what people thought about it. And when I put it out, the response was massive. And I had hundreds of brands reaching out. I ended up working with about 50 to kind of test and refine the product before ultimately putting it out to the market in about October.

18:54Ryan Knutson:Michael realized that what started out as a tool to help him with his job might actually be a business. So he founded his own startup called Sentium. Sentium offers an AI version of search engine optimization. It helps clients improve how often they show up in AI chatbot answers. And Michael says the company's doing well, with more than 200 brands using it. Michael charges customers a subscription, between$99 and$250 a month. He says he's bringing in around$7 ,000 a month in revenue. This is a solo business with just me. No payroll, no employees, no developers. And this is what this world of AI enables.