If you want a career in AI, start with these 5 steps

Your existing skills can help open doors in the booming AI field. Here's what you need to know and do before you pivot.
Written by David Gewirtz, Senior Contributing Editor
People studying a brain machine
Malte Mueller/Getty Images

Since I've been covering the new boom in AI, I've been getting reader letters asking how to grow into that industry. This letter from Rick is representative of many of them:

I just read your articles pertaining to free AI courses at IBM, OpenAI, and Deep Learning and wanted to see if you could offer some advice.

I'm trying to transition from my industry of life science to big tech. I want to continue to learn more about AI and its applications, with the focus on becoming a product manager who can showcase knowledge and use cases for it.

Do you have any suggestions for an experienced product manager, with very little machine learning experience, starting out on what to learn in the AI/ML space to become marketable? I'm going to start by taking the free courses from IBM as you mentioned. I would love to work with engineering and development teams on crafting products utilizing these technologies specifically.

What stands out about Rick's letter is that he's experienced as a product manager, but his field is life sciences rather than traditional tech. This experience is important because he does have skills that can transfer into other fields.

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I also receive letters from readers who don't mention experience or pre-existing skills, but just see that prompt engineers are raking in the big bucks and want to be part of the windfall. I mention this because a lot of less experienced folks see stories about app developers making millions or prompt engineers making six-figure incomes and think that just one course, or just wanting it hard enough, will get them the gig. 

Back when I taught entry-level programming, about half my students wanted to program. The other half wanted programming jobs because they paid well. Unfortunately, that second set of students wasn't all that willing to apply themselves to the craft. They just thought that the mere fact that they took a course in programming would get them a job. And it might have. But without demonstrable skills, that job wouldn't have lasted more than a few weeks.

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My point here is that you have to be willing to do the work, and you also have to be able to bring something to the job. Rick seems willing to do the work, and he has skills he can bring to the job. Below are the five steps I'd recommend Rick -- and anyone interested in pivoting to AI work -- take. 

1. Identify your current skills

This is important if you want to switch careers. What skills do you already have? 

As a product manager, Rick undoubtedly has some people-wrangling skills. Product managers have often been described as CEOs without the authority or the pay. That's because they need to manage and cajole people from multiple disciplines and departments.

He probably has some serious writing skills. Writing a product requirements spec is not a trivial task.

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Depending on what kind of product manager he is, he might also have marketing communications skills. By this, I mean the ability to write promotional copy describing his products for prospects, not just the implementation teams.

As an experienced product manager, he probably also has strong project management skills, strong organization skills, and some level of product knowledge (in his case, for life science-related offerings). 

2. Identify skills that might transfer

Rick might not be aware of this, but he has skills that are particularly well-suited to the world of AI. Prompt engineering (the writing of instructions for generative AI tools) is much more about structuring requests in natural language than it is about writing code.

Also: 6 skills you need to become an AI prompt engineer

If a product manager can do anything, it's writing clearly articulated specifications that take into account known constraints. That's already very close to prompt engineering. He'll have to learn the particular nuances of prompt engineering and how to battle those constraints, but he's in the perfect place to move into that role.

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He also understands development teams, projects, and the product management process, which is as important to tech companies as it is to life science businesses.

What about if you're not a product manager? What skills do you have that might transfer?

Back in the old days of AI, expert systems were built by modeling specific expertise of subject matter experts. But today's large language models pull information from vast tracts of information, often straight off the internet. If you have a domain-specific expertise that's valuable, say medical knowledge or petroleum modeling, or even how a house is constructed, that knowledge may be valuable to AI companies trying to break into those industries.

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Don't assume that knowledge needs to be high-tech or super high-end. If you're a teacher, you have expertise in teaching and communicating knowledge, as well as the fields you teach in. If you're a parent, you sure have experience with the real ins-and-outs of raising kids. If you have warehouse experience, go to the front of the supply chain line.

To be clear, just because you know something doesn't mean you're instantly going to get an AI gig in that area. But make sure you are aware of the subjects you're strong in, and make sure you communicate those subjects as part of your transfer search.

Let's go back to that teacher example. Teaching involves breaking down information into understandable chunks, creating lesson plans, and creating validation procedures to ensure students have learned the material. That's very valuable in the AI process as well.

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What about if you're a good salesperson? Sales skills are perhaps the most important skills anyone can have because selling pays for our salaries. Learn about the AI business, especially the types of prospects and sales cycles. And then present yourself to an engineering-driven company desperate for sales skills. Here's a hint: most engineers don't have a clue how to sell.

What if you don't have so-called professional skills? What if you're a secretary or administrative assistant? If you're smart, can apply yourself, and can learn, you also have an opportunity here. All companies need strong organizational skills and the ability to structure and manage projects. Do the learning tasks outlined in this article, do the resume-building tasks described at the end, and you might be able to change that title from administrative assistant to logistics manager for an AI company.

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What about if you're a coder, but not familiar with AI coding? Coding skills are hugely important. Just focus on the next section and train yourself on how your coding skills can use AI. Build a project or two. I talk about that in-depth next.

3. Train yourself

But, Rick says he doesn't know the AI field. He doesn't know the business of AI (all the players, how they relate, their competitive landscape). He doesn't really know how it all works. And he's never done any actual AI work.

The first is very easy to improve on. Read publications like ZDNET. Read voraciously about the AI industry. In fact, the very best way you can learn about a business you want to move into is to consume all the trade materials you possibly can. Read constantly. If you put in an hour of reading every day for six months, all of it centered on your desired target industry, you'll build a strong familiarity with that industry.

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Taking the free courses is also a good idea. But it's very important not to just consume the material, but to do the exercises. The ChatGPT Prompt Engineering for Developers course offered by OpenAI (the folks who make ChatGPT) and DeepLearning (an education provider) has a hands-on simulator where you can construct prompts with code, and play with them.

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The IBM course has a module where you can use IBM's tool to do some project work. Use it and practice with it. Amazon, too, has free courses that include hands-on experience.

I'll be spotlighting more free courses. Take them. Take as many as you possibly can. Give yourself time to really work the assignments and learn the material.

Then, get yourself a ChatGPT Plus and Midjourney account. You'll spend about $30/mo, but you'll have access to more powerful tools than just the free stuff. Use those tools. A lot. Experiment. Learn their limits and explore their strengths. Become comfortable with what they can do and how they fall short.

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My point here is simple: make yourself knowledgeable. If you want to get a job in a field where you don't possess the experience, expertise, or credentials, you won't get anywhere without any of them. Fortunately, AI is a field that doesn't require board certification or a specific terminal degree. But it does require knowing stuff.

4. Build yourself some AI resume points

By the time you're ready to ask for a job interview, make yourself into someone who can answer those interview questions with confidence and competence. When asked, "Show me what you've built with AI," have something you're proud to show off. When asked about the future of AI, have enough knowledge to clearly articulate all the issues, opportunities, and concerns. When asked about the strengths and weaknesses of offerings by Amazon, Google, Microsoft, OpenAI, and others, know enough to be able to answer.

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Another thing that will make you more attractive to hiring managers in the AI space is some experience in the AI space. Now, obviously that's the Catch-22 that's existed with jobs since there were jobs. Hiring managers want folks with experience, but how are you supposed to get experience without the job?

Well, here's how: Be creative.

For someone in product marketing, there are two clear ways to add some fairly easy line items to your resume.

The first is a writing a blog or a newsletter. Starting a Substack is super easy. Write about marketing and business observations involving the AI industry. Deconstruct products and strategies of the various AI players. Even talk about your journey into learning more about AI. Use your product marketing background to provide weight to your discussion.

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Now, for those of you not of the product marketing ilk, find how you can relate what you do know to AI and write about it. Experiment with the AI tools you do have and see how they might apply to your unique set of skills. Let yourself tinker, but ultimately, you want to do something you can put up on LinkedIn that has the word "AI" in it.

Speaking of that, especially for our product marketing friend Rick, find an AI Kickstarter project or a small AI startup, and offer to be a part-time advisor. You can offer services like looking over their marketing plans and offering advice or editing, or you can offer to write some marketing copy. The point is, if you don't require payment, and put in a few hours a week, you can start relating with folks in the AI field.

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Now, here's the trick that will better help you move the job needle: Agree to do these services in return for giving you a title associated with the company. It doesn't have to be a line title, like "marketing manager." It can simply be "advisor." The point is, you want to be able to legitimately list on your LinkedIn profile something like, "Advisor, Happy Valley AI Enterprises," or something similar.

5. Give it six months

I know. Now that you've decided you want to transition into AI, you want the gig tomorrow. Well, pal, that's not going to happen. But if you give yourself six months, and you work it seriously, you'll have a pretty good chance of moving into this new field.

Put in an hour each day. Make sure you read relevant articles every day. Do some project work and tinkering in the field every few days. Make AI part of what you do. Try using AI in your current job, just to see how it can fit in.

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The point here is that by the end of six months, make it so that AI isn't this new thing you want to move into, it's this thing that you're already very familiar with and use as a matter of your daily activities.

That way, by the end of the six months, you're not asking to "move into AI," but to "use your AI skills and knowledge in the AI field." That'll come across as much more powerful to hiring managers.

What to consider when working in AI 

A career in AI could be rewarding for a number of reasons. You get to help push the limits of technology almost into the realm of science fiction. AI is definitely the new hotness, so it's in high demand. That, in turn, means those with strong AI credentials can demand competitive salaries. In some cases, the work also can make a big impact across the board, and it's undeniably exciting.

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But keep in mind that a career in AI also comes with challenges. It's a moving target, so you need to be learning constantly and your skills could prove to be out of date six months after you learned them. There are tremendous ethical concerns and missteps that are possible at every stage along the value chain. Because the field is moving so fast, it's also likely to be a very high pressure career. And, of course, there's the question of job security. Will you engineer yourself right out of a job as you integrate AI into your organization?

There. That'll get you thinking. Good luck.

Let us know how it goes

Feel free to share your journey of exploration and transformation in the comments below. Or, even better, share it in your new blog or Substack. Good luck. Be strong. Be curious. What do you think? Let us know if Rick's path seems like it might be similar to yours. Did you learn anything you can put to use? What ideas do you have that I didn't share? Let us know in the comments below.

You can follow my day-to-day project updates on social media. Be sure to subscribe to my weekly update newsletter on Substack, and follow me on Twitter at @DavidGewirtz, on Facebook at Facebook.com/DavidGewirtz, on Instagram at Instagram.com/DavidGewirtz, and on YouTube at YouTube.com/DavidGewirtzTV.

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