Guide to AI Career Roles and Paths for Non-Developers

Non-technical / non-developer roles in AI often don’t get the attention they deserve. In this post I’ll shed light on why these roles are so critical and how you can break into AI using your current skills and strengths.

There are plenty of resources that guide you on becoming a machine learning or AI engineer or a data scientist. Here I want to draw attention to the many non-technical roles which are essential for AI success but they often don’t get enough attention.

First, let’s define what I mean by ‘non-technical’. I simply mean, roles in which you don’t have to write or read code or the work does not require a specialized technical skill such as configuring a server on a cloud platform or applying cybersecurity policies to a database.

Here are 5 reasons why non-developer roles in AI are important.

AI is a transformative, general purpose technology which will impact all industries and domains — your active participation shapes its future

AI, as an interdisciplinary field, depends and thrives on collaboration of developers, business experts, engineers and social scientists

Creating trustworthy, human-centric and beneficial AI requires diverse backgrounds and expertise to define values and ethics

The rise of low-code and no-code tools and platforms has empowered non-developers to create, experiment and innovate

With many unsolved problems…