“Hey Gianluca, how do I build a career in AI?”

Hi all,

I’ve had quite a busy first half of the week. In 3 days I gave:

• a keynote at the European Investment Bank

• a 2-day training for the executive MBA class at the Luxembourg School of Business (LSB)

• a public keynote at LSB

Here are a few pics:

At the end of the keynote at EIB I got approached by a few young ambitious interns who asked me the same question: how do I build a career in AI?

I want to share with you the 4 tips I gave them (if you’re short on time, #4 is my favorite one).

1. Leverage your existing expertise

Every industry will be impacted by AI. Let’s say your expertise is in finance: try to position yourself as an expert in AI use cases in finance. If it’s healthcare, research use cases for AI in healthcare, and so on.

This will ensure that you have an edge over people like me who are generalists and understand AI use cases in a broad sense. It will also help you kickstart your career as you have something to leverage (your existing domain).

2. Invest in basic AI training.

You don’t need a master's degree and $20k to get proficient in AI. And you don’t need to know EVERYTHING about AI to get started.

I often make a comparison with cars. There are 4 levels of understanding of how a car works:

• No understanding: you can’t drive

• User: you can drive but nothing else

• Mechanic: you can replace parts, but don’t understand thermodynamics and can’t design a car from scratch

• Engineer: you know everything it takes to design and build a car

With AI it’s kinda the same thing:

• No understanding: you’re clueless. Don’t be that person.

• User: you know basic prompting. This is where EVERYONE will be (get there ASAP), and it takes a few days/weeks to get to a decent level.

• Builder: you know how the technology works from an operational point of view and can prototype new products or services. This is where there will be lots of opportunities, and it takes a couple of months to get to

• Researcher: you can build entirely new products. You’re a nerd and have an MSc in computer science or similar and have spent at the bare minimum 1 year on AI

3. Get your hands dirty

I can’t stress enough how important it is to get practical.

And please don’t come up with excuses. Your company doesn’t want you to use ChatGPT? Cool, come up with a random use case (writing business plans for a new shoe for dogs, building an automation tool for social media, whatever) and use AI to solve it.

Whenever your company will wake up and realize they can’t compete without giving you access to AI tools, you’ll be already kicking ass and be ahead of everyone else.

4. Don’t ask for permission to position yourself as someone working on AI

I’m not promoting a “fake it ‘till you make it approach”, but start sharing with people that you are actively investigating how AI can help you and your company.

Have you written a business plan for a random crazy company as an exercise? Was it good? Tell your boss. Tell LinkedIn. Tell everyone. Did you build a small automation? Same thing.

Remember: you don’t need to be 100% knowledgeable in something to help others. If everyone around you is at 1% knowledge and you’re at 10%, you are 10x better than them and can help them in their journey. There’s no need to fake anything: get ahead, and start building your reputation with honesty and humbleness but realism too. You can get a lot of shit done with some basic understanding of AI.

This process will lead others to understand you have experience in the field and start asking you to lead or test new technologies, and your journey as an AI expert in your field will start.

This is how I started, and how many of my friends or students did too.

Don’t wait for someone to give you a chance.

Take it.

The best place to get started is our Master in Prompt Engineering, where I’ll lead you and a small group of ambitious people to build your own AI prototype so you can get your journey started.

Early bird discounts end tonight at midnight CET. 

Will I see you in class?