AI Skills are Now Mandatory

Learn These Skills Right Now.

Author

Mike West
July 16, 2025

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This week we talk about the AI skills you need for the new job market. 👀

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Indeed’s Hiring Lab reports a staggering 3,000% surge in generative AI job postings between January 2023 and February 2024. The World Economic Forum echoes the shift, projecting that while 85 million jobs will be lost to automation, 97 million new, AI-powered roles will emerge in their place.

Meanwhile, 87% of hiring leaders say AI experience is a valuable asset for candidates—and here’s the kicker: 8 out of 10 are more likely to hire someone comfortable with AI tools than someone with more experience but less AI fluency.

In short, if your résumé doesn’t speak AI, you’re showing up to a gunfight with a rubber chicken.

But don’t worry—you don’t need a PhD in machine learning. You just need to know which AI skills matter and how to show you’ve got them.

Reality Check

PwC’s 2024 Global AI Jobs Barometer found that workers with AI skills earn up to 25% more than their peers without these capabilities.

Oxford research confirms that employers in the AI sector are prioritizing skills over formal education, with practical expertise commanding higher salaries than university degrees alone.

This isn’t some distant future where robots take over. Companies are scrambling right now to find people who can bridge the gap between human creativity and AI efficiency. Most of your competition is still figuring out how to use ChatGPT for basic tasks.

The 10 Skills Employers are Demanding

According to Coursera and the World Economic Forum, here are ten of the most in-demand AI skills employers want to see in job seekers right now.

1. Prompt Engineering: Your superpower in the AI age. Understanding how to communicate with AI systems to get consistent, useful results.

2. Generative AI (GenAI): Beyond just using ChatGPT for emails, leveraging AI for content creation, problem-solving, and workflow automation across different platforms.

3. Machine Learning Fundamentals: Understanding how machine learning works, when to use it, and how to interpret its outputs without needing to code neural networks from scratch.

4. AI Literacy: Understanding AI capabilities, limitations, and ethical implications. Knowing when AI is the right tool for the job and when it’s not.

5. Big Data Handling: AI runs on data. Understanding how to collect, clean, and prepare data for AI systems is becoming as essential as knowing Excel used to be.

6. MLOps (Machine Learning Operations): Making AI work in real business environments. Deploying, monitoring, and maintaining AI systems that actually deliver value.

7. Critical Thinking: Your built-in BS detector for AI outputs. As AI becomes more sophisticated, your ability to question, verify, and validate becomes more valuable.

8. Creative Thinking: Where humans still reign supreme. AI can generate ideas, but it takes human creativity to connect the dots in ways that truly matter.

9. Analytical Thinking: Making sense of what AI tells you and turning insights into actionable strategies. The difference between having data and having wisdom.

10. Resilience: AI tools change faster than TikTok trends. The ability to adapt, learn, and bounce back from constant technological shifts is your career insurance policy.

According to a recent AWS survey, 93% of employers planning to use generative AI say critical thinking is one of the top skills they’re looking for.

It’s not just about technical know-how like prompt engineering or big data anymore; companies want people who can think clearly, communicate well, and stay adaptable.

While technical skills can go out of date in a couple of years, power skills like these stick with you and work across any industry or role.

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How to Prove You Know What You’re Doing

Connect every AI skill to real results with hard numbers.

  • “Developed custom AI workflows that reduced content production time by 60%”

  • “Used prompt engineering to improve customer service response accuracy by 40%”

  • “Implemented machine learning models that increased sales predictions by 25%”

Notice the pattern?

Skill + Action + Measurable Result = Hiring Manager’s Attention

Where Do You Start?

I’m building a Skool Community to teach people how to quickly and competently learn to build agents in the real-world using low code tools. I’ll be teaching and acting as a data curator. That means I’ve created a path and will enlist the help of others to teach key topics. Here are three videos that are part of my course that are also applicable to the research in this article. These are fantastic.

Take notes. Do not watch these videos like you normally do. These are micro-courses filled with content you must know. Most people don’t know where generative AI lives within the AI Hierarchy. Hell, most don’t know the AI Hierarchy. You must understand and be able to have a conversation about these topics to be taken seriously.

I’ll be sending out updates and specifics about my Skool Community over the coming weeks. Buckle up. In a few years you can be an agent engineer earning a great salary in one of the fastest growing fields on earth.

Thanks and have a great day! 👏