The AI Skills Gap

Let’s be honest: if you’re trying to break into AI or level up your career, it can feel like everyone’s got a different opinion about what skills you “absolutely need.” The truth? There’s a real gap between what people think matters and what companies are actually looking for right now.

What Most People Think You Need

A lot of folks still believe that to get into AI, you need a PhD, years of coding experience, and the ability to recite algorithms in your sleep. There’s this idea that AI is only for math geniuses and hardcore engineers. And sure, those skills are valuable, but they’re not the whole story.

Some people also think that just adding “AI” or “machine learning” to your resume will get you a job with a sky-high salary. But employers are looking for more than buzzwords and certificates.

What’s Really in Demand

Here’s what I’m actually seeing out there:

• Solid Programming Skills: You don’t need to be a coding wizard, but you should be comfortable with Python and able to work with data.

• Applied AI Know-How: Employers want people who can use AI to solve real problems, not just talk theory.

• Generative AI & Prompt Engineering: With the explosion of generative AI tools, knowing how to write effective prompts and guide these systems is a big plus. (Read the previous article to learn more about prompt engineering: iterai.beehiiv.com/p/prompt-engineering-is-good)

• Domain Knowledge: Understanding the industry you’re working in (like healthcare, finance, or retail) is often just as important as technical chops.

• Soft Skills: Communication, teamwork, and creative problem-solving are huge. Can you explain your results to non-technical folks? Can you work across teams?

• MLOps & Deployment: More and more, companies want people who know how to move models from the lab into the real world and keep them running smoothly. (Check out the full IterAI page to learn more about MLOps and Deployment: iterai.beehiiv.com)

How to Bridge the Gap

So, what should you actually focus on?

• Mix it up: Don’t just learn to code. Work on your communication and business sense, too.

• Get hands-on: Real project experience beats a stack of certificates every time.

• Stay curious: AI is changing fast. Be ready to learn new things and adapt.

• Think beyond tech: AI isn’t just for engineers. There are growing roles for analysts, designers, project managers, and more.

Wrapping Up

The biggest thing to remember? Companies want people who can connect the dots between technology and real-world needs. If you’re building your AI skill set, aim for a balance: technical skills, creative thinking, and the ability to communicate clearly. That’s what will make you stand out, no PhD required.