While tech giants pour billions into hiring elite AI researchers, millions of everyday professionals are asking: *How can I get in on this?*
The incentive is clear. Job postings requiring one AI skill pay **28% more**—about **$18,000 extra**—than non-AI roles. Those asking for two AI skills? A **43% premium**.
But AI isn’t just for researchers in lab coats. The field spans five key roles:
1. **Researchers** – Pushing boundaries in algorithms (usually PhDs).
2. **Engineers** – Building AI-powered products.
3. **Business Strategists** – Integrating AI into operations and products.
4. **Domain Experts** – Applying AI within specific industries (healthcare, law, finance, etc.).
5. **Policymakers** – Shaping ethical guidelines and governance.
Most opportunities lie outside the ivory tower of research. So once you’ve picked your path, what’s next? Industry insiders—from LinkedIn and Amazon to AI startups—agree on four proven strategies.
### 1. Learn AI *On the Job*—Even If It’s Not in Your Title
Only **40% of employees** receive AI training at work. But that doesn’t mean you’re stuck.
**Cheryl Yuran**, CHRO at Absorb Software (an AI learning platform), advises: *“Get AI experience at your current company before jumping ship. Even one project gives you something real to talk about.”*
Her company often hires non-AI specialists—product experts, communicators, designers—as long as they show they can contribute alongside AI-literate teammates.
Take **Gabriel Harp**, a former product manager with degrees in English and German. In 2023, he led the launch of an AI writing assistant at Research Square—handling vision, branding, go-to-market strategy, and quality testing—despite not being an engineer. That experience helped him land a senior product role at **Mozilla**.
*“I wasn’t an AI expert,”* he says. *“But I was using the tools before most people even knew they existed.”*
### 2. Take a Course—Even If You Think You Know the Basics
When on-the-job AI exposure isn’t possible, structured learning fills the gap.
**Amanda Caswell**, formerly a copy lead at Amazon, dove into AI during the pandemic. She took a prompt engineering course from Arizona State University, an OpenAI boot camp, and LinkedIn’s generative AI masterclass.
She started freelancing as a prompt engineer on Upwork—earning nearly **$200,000** part-time—and later became an **AI journalist at Tom’s Guide**.
Similarly, full-stack developer **Cesar Sanchez** transitioned into AI engineering after taking a Coursera course on large language models. He also joined a cohort-based program that gave him access to a network of AI engineers and free tool credits—key for hands-on practice.
*“Start with the fundamentals,”* Caswell advises. *“Even if you know some things, grounding yourself in best practices helps you teach others—and that’s a valuable skill too.”*
### 3. Build Side Projects—Your Portfolio Speaks Louder Than Your Resume
Recruiters notice candidates who tinker outside work hours.
**Taylor King**, CEO of Foundation Talent, says: *“The ones thriving are those constantly experimenting—building bots, fine-tuning models, shipping demos. An active GitHub shows genuine curiosity.”*
**Nico Jochnick**, with no formal AI background, landed a lead engineer role at Anara—an AI startup for scientific writing—thanks to side projects built with AI coding tools like Cursor and participation in hackathons.
While job hunting, **Gabriel Harp** created a ChatGPT-powered recruiting tool that let interviewers query his experience—and even coded a bingo game for his favorite podcast using AI. *“I didn’t want to get rusty,”* he explains. *“Staying hands-on kept me sharp.”*
### 4. Create Your Own AI Role—Or Even Your Own Company
Sometimes, the best way in is to invent the job.
**Ben Christopher**, a screenwriter, taught himself to code and built **Speed Read AI**—a tool that summarizes film scripts and estimates production budgets. After showing it to Hollywood execs, he turned it into a startup with five employees.
**Victoria Lee**, originally a lawyer, took a coding bootcamp and began feeding legal contracts into ChatGPT to test its analysis. She quickly spotted where AI excelled—and where it failed. That insight helped her land a product strategy role at **eBrevia**, an AI legal tech firm. But she didn’t stop there: she now runs her own consultancy, helping mid-sized law firms adopt AI responsibly.
Her advice? *“Identify your specialty. Then figure out how AI can enhance it—or where it still needs human judgment.”*
Jochnick, now building a stealth AI startup, puts it bluntly: *“The biggest mistake is not trying. In just a few months, you can become dramatically more capable. This is a fun, fast-moving journey—and everyone should be on it.”*
You don’t need a PhD or a Silicon Valley pedigree to break into AI. What matters is **curiosity, initiative, and proof of application**—whether through internal projects, coursework, side hustles, or even launching your own venture.
As AI reshapes every industry, the door isn’t just open for engineers. It’s wide open for **strategists, creators, domain experts, and problem-solvers** who are willing to learn by doing.
Start small. Build something. Share it. And don’t wait for permission—create your own path.