What is agentic AI?
Agentic AI is an approach in which AI systems do more than generate answers: they set sub-goals, plan, use tools and carry out multi-step work with limited human intervention. The term describes not a single agent but the whole system: agents, tools, permissions and human approval points designed together around a business process.
Definition
Agentic AI is an approach in which AI systems do more than generate answers: they set sub-goals, plan, use tools and carry out multi-step work with limited human intervention.
How does agentic AI work?
A piece of work is split across several AI agents. One agent classifies an incoming request, a second finds the relevant documents, a third acts in a business system. Each agent has a defined set of tools and data it may access, and tool connections increasingly use standards such as MCP. At critical decisions the flow pauses for human approval. Every step is logged, so you can later see why an outcome was reached.
When is it a good fit?
For processes whose input varies every time, that touch several systems, and that today rely on an employee’s judgement: supplier correspondence, complaint resolution, preparing sales quotes. Where the steps are known in advance, classic RPA or workflow automation is cheaper and more predictable. Starting with a small, measurable process and widening scope step by step keeps risk manageable.
Governance and regulation
Because agents access personal data and take actions, permission boundaries, logging and human approval points should be documented for GDPR, for KVKK in Türkiye, and for internal audit. Organisations whose systems are placed on the EU market or used there should also assess their obligations under the EU AI Act. Together, these rules form your AI governance.
Related terms
- AI agentAn AI agent is software that uses a language model to decide which steps to take towards a goal and then carries out those steps with tools such as APIs, databases and email.
- MCP (Model Context Protocol)MCP (Model Context Protocol) is an open protocol, introduced by Anthropic in November 2024, that gives AI applications a standard way to connect to tools, data sources and business systems.
- RPA (Robotic Process Automation)RPA (robotic process automation) is an automation method in which a software robot clicks through screens and enters data like a person to carry out rule-based, repetitive tasks.
- AI governanceAI governance is the set of policies, roles and processes that determine how an organisation selects, uses, oversees and manages the risks of its AI systems.
- LLM (Large Language Model)An LLM (large language model) is an AI model trained on very large amounts of text that answers questions, summarises, translates and writes by predicting what text should come next.
Frequently asked questions
Are agentic AI and an AI agent the same thing?
Close, but not the same. An AI agent is a single software component. Agentic AI describes the broader approach in which agents are embedded in business processes, hand work to one another and operate under managed permissions.
Will agentic AI replace RPA?
Not entirely. RPA stays predictable for rule-based, fixed-step work. Agentic systems take on the steps that require decisions on ambiguous input. In practice the two often run in the same process.
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