The Best Careers In The Age Of AI

[00:00:00]Every time I open YouTube, I see two completely different stories. One says that AI is replacing workers. Tech companies are going through layoffs. The other says that AI engineers are making more money than ever. Founders are raising billions of dollars. And honestly, those two stories don't really seem like they can both be true. If AI is replacing workers, why are some AI engineers getting paid millions of dollars? So, I went digging through research on the future of jobs to figure out what's actually happening. And what I found completely changed how I think about the future of work. Because according to the research, AI isn't just creating one future. It's creating two.

[00:00:42]Some workers are becoming more valuable while others are becoming less. And the difference isn't what most people would think. Today, we're going to answer three questions. Why are some careers benefiting from AI while others are being replaced? What are the winning jobs and what can you do right now to be on the winning side? First, we'll start with the big picture. And thanks to HubSpot for sponsoring a portion of this video. Who are the biggest winners in the age of AI? Most people assume it's the AI itself, the companies building or selling models. But an MIT economist Barren argues that the future isn't determined by how powerful AI becomes.

[00:01:20]It's actually determined by how we choose to use it. Does AI replace workers or does it make workers more productive? The winners are not competing against AI. They're working with AI. Take software engineers. Many are using tools like cloud code to write code faster, debug issues, and handle repetitive work. The engineer still decides what to build, how to build. The AI helps you execute it. Or take lawyers. Tools like Harvey AI can speed up legal research part, but the lawyer still provides the judgment and the advice for the client. But the AI helps get the information and also analyze it.

[00:01:59]Different jobs but same pattern. Their expertise become more valuable when combined with AI. Most people are asking, can AI do my job? A better question might be, can AI make me better at my job? So, what determines if you're amplified or replaced by AI? According to the research, one thing stood out to me as a pattern. It's judgment. AI is becoming very good at generating information like writing reports or summarizing documents. It can even analyze data and write quotes for you.

[00:02:30]But if information becomes cheap, does expertise become less valuable? No.

[00:02:35]Because many of the highest paying jobs aren't paid for producing information.

[00:02:40]They're paid for making decisions. Think about a doctor. AI can help analyze scans and suggest possible diagnosis.

[00:02:48]But who decides on the actual treatment plan, the doctor will or take an engineer. AI can generate five different solutions to a problem. But you are the one still reviewing and making decisions. When there's ambiguity and uncertainty, AI still struggles. And the more consequences attached to a decision, more valuable human judgment becomes. So, if the biggest opportunity is combining AI with expertise you already have, the next question becomes, how do you actually put that into practice? And if you're serious about getting ahead of the competition, I recommend checking out HubSpot's free 2026 AI agents playbook. One thing I like about this guide is that it cuts through a lot of the hype around AI agents. Instead of asking, "How can I replace people with AI?" It focuses on much more practical questions like how can humans and AI work together more effectively. The guide covers what AI agents actually are, where they're creating real value today, common mistakes people make when implementing them, and how to identify opportunities for AI inside your own work. My favorite section is the low precision versus high precision task framework. The idea is really simple. Use AI for tasks where 90% accuracy is good enough like research, data gathering, and content drafting, but keep human involved for highstake decisions that require judgment, expertise, and accountability.

[00:04:13]If you would like a copy, you can download the AI agents playbook for free using the link in the description.

[00:04:19]Thanks to HubSpot for sponsoring this portion of the video. Now, let's look at what the winning careers in the age of AI actually are. The biggest opportunities may be combining AI with expertise you already have. We talked about this. So think about health care.

[00:04:33]Let's say you have two nurses. One understands how to use AI tools to summarize patient information, identify risks, maybe do the documentation and administrative work for her. The other doesn't use AI. So who becomes more valuable? The same thing is happening in engineering. Knowing how to use AI is helpful. Knowing how software systems actually work is even more valuable.

[00:04:57]That's why most experts say that foundation is the most important for engineers. And that's good news because most people don't need to start over.

[00:05:05]You don't need a PhD or start building foundation models from scratch. You can start with expertise you already have.

[00:05:12]Then learn how AI can make you better at it. The people who win may not [clears throat] be the people who know the most about AI. They may be the people who know the most about their industry and learn how to use AI effectively to improve their workflow.

[00:05:28]So what exactly are the winning careers?

[00:05:30]Based on the research, they tend to fall into four different buckets. First is the people building AI. These are roles like machine learning engineers, AI researchers, AI product managers.

[00:05:41]They're building the models, the applications, and the AI systems that other people are relying on. Think tools like Chachi PT, Claude, Cursor, GitHub, Copilot. People are creating tools that everyone else is using. Second group of people are making high stakes decisions with AI. Think about executives, investors, senior architects. AI can provide the information they need so they can do their job better. Third group is people combining AI with deep industry expertise like doctors who know how to use AI or lawyers or teachers using AI. And the focus here isn't the job titles itself, but it's that AI helps them do their job better. And there's one more category worth mentioning which is people doing work in physical world. Think about plumbers, electricians, HVAC technicians, caregivers. These jobs involve unpredictable environment. They have to navigate physical environment, interact with it and also require a lot of human trust. There are some physical AI like robots being developed in this area, but replacing them is much harder than doing a spreadsheet. So, robot can work in a factory where everything is controlled and predictable, but it's much harder to send a robot to someone's house to do the kitchen work or redo the plumbing or take care of children for them. That doesn't mean these jobs won't change, but many face less pressure than jobs built around moving information from one screen to another. So, which job categories should be more concerned?

[00:07:14]According to research, the biggest risk isn't your job title. It's the task you perform every day. Jobs built around repetitive information processing will be the first to be replaced. For example, for my own business, I use Calendarly for scheduling, Otter for transcriptions, notion for documentation and reports, Zapier for operation, Air Table for tracking data. In the past, I would have needed multiple people helping me with many of these tasks.

[00:07:42]Today, I use mostly AI tools. According to one study, many of the occupations are facing most pressure or informationheavy jobs. They warn about administrative work, legal research, financial analysis, and some healthcare support roles. Not because the jobs disappear overnight, but because more of their day can be automated. The biggest risk isn't your entire job title is how much of your work consists of repetitive information processing. If you think about software engineering, decades ago, programmers use physical punch cards first. Then higher level programming languages came about. Then we had Stack Overflow and people were worried that we're only copy pasting code now. It was supposedly the end of software engineering and now AI vibe coding tools do everything for us. The job of a software engineer has been evolving through improvements in tech. So instead of asking is my job safe? A better question might be how much of my day is repetitive? Because the more your work depends on routine information processing the more pressure you may face. And that leads to another problem.

[00:08:48]What happens if you wait too long to adapt? It might be tempting to think, I can always adapt later. Maybe when AI gets better, maybe when your company starts using it. But what happens if you wait? One of the more interesting ideas that I found in the research is something called the mobility trap. The idea is simple. Let's say the skills you have spent years building start becoming less valuable. Maybe it's because part of your job gets automated. Maybe is because your employers need fewer people doing that work. Now you're competing for fewer opportunities. Your income starts falling and now you have less time, less money and fewer resources to learn the new skills. And that is the trap. The danger isn't just one layoff.

[00:09:34]The danger is getting stuck. And that's why I think the biggest risk isn't AI, it's waiting. Because the earlier you start adapting and learning, the more options you have. So, what can you do right now to stay on the winning side?

[00:09:47]Okay, this can be all very overwhelming.

[00:09:49]You might be thinking like, do I need another degree, a PhD, a complete career change? Well, probably not. Instead, in your current job, ask yourself, how can I use AI to make me better at my job?

[00:10:01]Maybe you want to start volunteering to solve problems for other people. Start taking on AI related projects at work.

[00:10:07]Because if your company starts thinking about adapting AI, you're going to be the first one people think of. And even if you get laid off, you'll have something valuable to talk about in your next interview. You're gaining real experiences, real examples, and results.

[00:10:22]If you're using AI to automate parts of your work, redesign workflow, or solve business problems, you're building exactly the kind of experience and the skills that employers are looking for.

[00:10:33]And if you don't have a job right now, you can still do the same thing. Look at your own life. Help a friend or a family member. Ask them, "What are some tasks that you do over and over? What can you automate?" When you're solving real problems, you're creating real stories.

[00:10:48]And these stories are often more valuable than any other certificate or course you can take. The people who win in the age of AI may not be the smartest people or the most technical. They may simply be the ones who start building before anyone else. Now, if you want to explore jobs in AI or AI adjacent or using AI, you can watch this video where I talk about different career paths and I will see you