“I want to advance my career into the field of artificial intelligence, but I want to focus on strategy and leadership instead of coding.”
I hear this every day from people in multiple countries around the world.
The more I talk to product managers and other non-technical IT professionals, the more I realize how many people want to get into the field of AI.
Do most people want to become data scientists or machine learning engineers?
Most people thinking about making a career transition to artificial intelligence want to do so from a non-technical perspective. They love AI/ML, they believe it’s the future, and they want to help create this new world. However, they don’t want to be involved in hands-on programming as part of their job responsibilities.
Do ‘non-technical’ AI roles exist?
Yes, they do.
Broadly speaking, right now there are two categories of AI roles that do not involve hands-on coding:
- Enterprise sales of AI/ML products and services
- AI/ML product management roles
If you want to make a career transition to AI as a non-technical IT professional, there are certainly options available for you right now. If you are inclined towards sales, the former option is great. If you prefer product management, the latter option is ideal for you.
To prepare for this career transition and get job offers as soon as possible, you want to keep in mind 3 major components:
1) Mastering LinkedIn
When it comes to making a career transition to artificial intelligence, the main purpose of LinkedIn is to build your AI network to attract job opportunities.
You want to add value to your network, but you also want to leverage LinkedIn to get referrals to hiring managers directly.
The process of submitting your resume online and waiting to hear back from HR is extremely inefficient. This passive, powerless approach usually goes sequentially like this:
- Find job opening online
- Submit generic resume (without a cover letter)
- Cross fingers and hope to hear from them soon
- Days and weeks go by without any response
- Receive email from HR saying, “Thank you for applying to position X. Unfortunately, we have decided to move forward with other candidates…”
This is often the case, even when you felt you were an amazing fit for the role and company. HR’s job is not to help you. HR’s job is to screen out candidates and prevent entry into the company.
This process sometimes works, of course, but it’s not efficient. What if you could get referred directly to the hiring manager without ever speaking with HR?
That’s how masters do it, and that’s what LinkedIn can help you do. Referrals are not only more efficient and powerful, but they carry trust with them. This trust carries over the entire job interview process.
2) Mastering AI/ML business fundamentals
Once you know how to maximize opportunities through LinkedIn, the next step is to master AI business fundamentals.
AI business fundamentals involve both technical and non-technical expertise.
For the technical expertise, you don’t have to be a hardcore AI programmer. For non-technical roles, ‘technical’ expertise means you understand artificial intelligence concepts, terminology, and processes.
For example, do you know the difference between classification and regression as they apply to specific use cases? And I don’t mean from a coding perspective. I mean from a conversation perspective like this.
For the non-technical expertise, you want to have a strong understanding of the business value AI brings to an organization. This means subject matter and domain expertise, industry knowledge, ROI parameters, AI/ML team leadership, risk assessment, etc.
If you have a strong grasp of both technical and non-technical business aspects of AI adoption, you will separate yourself from everyone else and become extremely valuable in the marketplace in a short period of time.
3) Mastering the AI interview process
Once you have a strong grasp of LinkedIn and AI/ML business fundamentals, the third step is mastering the ‘non-technical’ AI interview process.
There will not be a coding exercise, but there will be technical questions. You will be expected to have a strong understanding of the machine learning process, how AI teams are structured and why, elements of successful use cases, best practices, etc.
Most importantly, however, are the questions you ask them. If you ask the right questions, in the right order, following a specific process, you will be seen as the strongest candidate.
As you generate referrals for interviews and do the interviews correctly, you will have job offers for non-technical AI roles in no time.
These 3 components encapsulate what I call “AI Career Acceleration.”
People who make a career transition to AI successfully do not do it gradually.
We accelerate and break through in a short period of time. Since the field is evolving and changing rapidly, we realized this is the best and only way.
If you believe artificial intelligence is the future and you want to capitalize on the new career growth opportunities, consider breaking into AI through the non-technical career path (see job options above).
If you need help to accelerate your company’s machine learning efforts, or if you need help getting started with enterprise AI adoption, send me a LinkedIn message or email me at firstname.lastname@example.org and I will be happy to help you.
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