AI agent coordinator: a new profession that bridges technology and business

What would this professional do?

The growing use of artificial intelligence agents is creating a need for a new role that doesn’t yet have a widely accepted name. This professional would be responsible for defining the agents’ tasks, monitoring their performance, correcting errors, and integrating these tools into the company’s daily operations. Unlike traditional chatbots, AI agents can access databases, use other tools, and execute process steps with minimal human intervention.

In practice, a company could have agents dedicated to organizing customer information, creating reports, tracking metrics, or supporting sales teams. For this to work, someone needs to decide which tasks can be automated, set clear rules, and verify that the system’s output is accurate. The ideal candidate wouldn’t necessarily be a programmer, but someone who combines technical AI knowledge, an understanding of business processes, and familiarity with the industry where the technology will be applied.

The market is already starting to create these roles

While there isn’t yet a single, officially recognized profession for this role, positions that combine parts of these responsibilities are already emerging. A LinkedIn study, released by the World Economic Forum in January 2026, projected the creation of 1.3 million new AI-related jobs over two years, including roles such as AI engineer, forward-deployed engineer, and data annotator. The same study identified growth in leadership positions focused on artificial intelligence.

The World Economic Forum has also begun discussing the possibility of managers treating AI agents as “digital workers,” which would require new skills in supervision, trust-building, and task definition. The Forum’s Future of Jobs Report 2025 estimates that nearly 40% of workplace skills will change by 2030, with artificial intelligence, big data, and technological literacy being the fastest-growing competencies.

A role that bridges technology and business

The emergence of this occupation reflects a shift in how work is distributed. Instead of using AI only to answer questions or generate text, companies can now delegate entire processes to it. A practical example would be a workflow where one agent collects data, another organizes it, and a third prepares an analysis for human review.

Typical responsibilities of this role include:

• defining the objectives and limits of agents;
• monitoring results and identifying errors;
• organizing the data used by the systems;
• connecting different tools;
• deciding when a task requires human review.

The name may come after the role

History shows that new jobs don’t always start with a clearly defined title. LinkedIn found that over 10% of workers hired globally now hold positions with titles that didn’t exist in 2000. With artificial intelligence, the same process may repeat: new responsibilities emerge within companies first, then these tasks are grouped into roles, specializations, and eventually into a profession recognized by the market.