AI operator and automation specialist
The most accessible entry point. Such a specialist does not write code, but knows how to solve work problems with the help of AI: he automates routines, processes texts and data, and customizes assistants for company processes. The demand is high because almost every department has repetitive work that AI removes. You need prompting skills, an understanding of the capabilities and limitations of models, and practical thinking.
AI engineer and developer
For those who are ready to work with code. Such a specialist embeds models into products: chat bots, agents, document search (RAG), API integrations. You need the basics of programming plus an understanding of how models are structured and behave, how to evaluate them and make them reliable in production. This is a more technical, but also higher paid branch.
Related roles: product, content, analytics
AI permeates every function. Product managers design AI features, marketers and authors scale content, analysts speed up work with data. What's valuable here is the combination of your current expertise and your ability to apply AI—domain plus AI is often stronger than a pure techie. This is the best path for those who do not want to start their career from scratch.
How to enter AI without experience
The classic problem “there is no experience without work and no work without experience” is solved by proof. Collect a small portfolio: 1-2 completed projects that solve a real problem and that can be shown. Describe them as cases (problem → solution → result). Analyze real vacancies, write down common requirements and close the main gaps. Don't wait for perfect readiness - create proof and respond.
Use past experience to your advantage
Switching to AI does not reset your background—on the contrary. Knowledge of a subject area (finance, medicine, law, sales) makes you more valuable for AI tasks in this area than a generalist technician. Communication, understanding of business problems, and the ability to get things done are in short supply in technical teams. Combine the past with new skills - it's a rare and powerful combination.