AI for Business: Your Career When Your Colleague Is an AI Agent

How to use an AI agent for your career: Marina Lomadze, head of talent acquisition and hiring at Cloud.ru, published a column on Habr on July 1, 2026 with a concrete, practical question. If in 2–3 years every specialist has an AI agent or multi-agent system beside them, what role will the human play in that pairing, and how do you build a career path now, without waiting for your job to change on its own?

Competitor or colleague?

Lomadze proposes changing the frame. She considers the question "will AI replace my job?" a dead end and rephrases it: "What exactly am I better at than the agent, and how do I turn that into a specific role?"

An agent reliably handles repetitive tasks, processes data streams without fatigue and does not lose quality on the hundredth iteration. A human brings what an agent does not accumulate on its own: the political context inside an organization, client trust built over years, ethical judgment in a nonstandard situation, and the ability to answer for the outcome to real people.

The author describes the key professional shift this way: from executing tasks to defining them. A specialist who can explain to an agent what exactly needs to be done, in what context and under what constraints, is worth more than one who simply does the same work by hand.

Which new roles have already appeared

The author highlights several areas where hiring demand shifted in 2025–2026:

• AI Product Owner — defines requirements for agent systems, sets the limits of automation and the criteria for acceptable quality
• AI Trainer / RLHF specialist — trains models through data labeling and by correcting agent behavior
• Prompt engineer / Conversation Designer — designs the instructions and scenarios in which an agent solves real business tasks rather than just generating plausible text
• AI Compliance & Ethics — monitors agent systems for regulatory compliance, decision transparency and the absence of bias
• Multi-agent system orchestrator — manages a team of agents, distributes tasks, checks results and answers to the business for the outcome

Many of these roles first appeared in large technology companies and AI labs, but in 2026 corporate customers are also actively opening them: financial organizations, retail, media and industry.

How familiar professions are changing

Most specialties, in Lomadze's view, will not disappear; they will shift in the level of tasks. A recruiter working alongside AI screening spends time not on filtering by formal criteria but on assessing a candidate's motivation and cultural fit, something an agent cannot do reliably. A marketer delegates the generation of content variants to an agent and concentrates on strategy and brand narrative. A developer writes less routine code and spends more time on architectural decisions and oversight of output quality.

The author states the general principle briefly: the human moves up a level in complexity and responsibility, leaving the reproducible work to the agent.

What this means

For career decisions right now, this means a concrete inventory: what in your work is repetitive and can be algorithmized is a zone of vulnerability; what requires contextual judgment and interpersonal relationships is a zone of growth. Moving into AI-adjacent roles does not necessarily require changing professions: in many cases it is enough to learn to work with agents within your current specialization.

How do you rephrase the question about an AI agent replacing your job?

Lomadze reframes the task: instead of asking "will AI replace my job," ask "what exactly am I better at than the agent, and how do I turn that into collaboration." This helps identify your unique skills and build a career path alongside an AI agent.