GLOSSARY
Agentic AI
Agentic AI refers to AI systems able to pursue a goal autonomously: planning steps, using tools (ATS, email, calendar), executing actions and self-correcting. Generative AI answers, agentic AI acts.
IN DEPTH
Agentic AI is the generation of artificial intelligence that follows generative AI: instead of producing content on demand, it pursues goals. An agentic system combines four building blocks: a goal phrased in natural language, access to business tools (through standards like MCP), a planning loop (decompose, execute, observe, adjust) and guardrails defining what is automatic, subject to approval or reserved for humans. Recruitment is ideal ground: many execution tasks (about 40% of recruiters' time), structured data in the ATS and clear business rules. Production applications include application qualification, continuous sourcing, follow-ups, scheduling and document production. Agentic AI powers AI workers, its business embodiments. Beware of "agent-washing": a tool that only generates text is not agentic; a real agent accesses systems and produces traceable actions.
Frequently asked questions
Generative AI produces content (text, summary, image) and you act afterwards. Agentic AI acts itself: it chains actions in your tools to reach a goal, with human intervention limited to important approvals.
Three criteria: read/write access to business systems (ATS, email, calendar), the ability to chain several actions without intervention at every step, and traceable actions subject to approval rules. Without these three properties, it is a rebranded text generator.
Related terms
- AI Worker (digital worker)An AI worker is an autonomous AI agent that owns a complete, continuous scope of work, like a digital colleague: it sources, qualifies, follows up, schedules and reports, with human approval on sensitive actions.
- MCP (Model Context Protocol)MCP is an open standard created by Anthropic that lets AI assistants (Claude, ChatGPT) connect directly to business tools like an ATS or CRM, to read data and execute actions in natural language.
- AI Matching (candidate-mission)AI matching uses machine learning models to evaluate a candidate's relevance to a mission by crossing skills, experience, availability and cultural fit. It replaces Boolean search.
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