Rather than only responding to input – like many generative AI tools – Agentic AI can carry out tasks independently within clear boundaries. It enables process support where software not only thinks, but also acts.
This article explains what Agentic AI is, what components make up an AI agent, and how it can be applied to automate work processes.
From generative to goal-oriented: what is Agentic AI?
Generative AI is mostly used to produce text, ideas, or summaries based on input. Agentic AI takes this further: it enables software to take actions, make decisions, and handle steps in a workflow on its own. Not as a passive assistant waiting for prompts, but as a digital colleague that actively performs tasks – always within defined limits. The key is: clear boundaries, transparent processes, and verifiable outcomes.
What are the components of an AI agent?
An AI agent typically consists of four key components that enable it to function autonomously within a process:
- The brain – the language model
- Memory – maintaining context and internal knowledge
- Tools – access to systems
- Task execution – planning and follow-up
1. The brain – the language model
This is the thinking part of the agent, powered by a language model like GPT. It can interpret language, make plans, process information, and decide the next logical step.
2. Memory – retaining context and knowledge
Agents use memory in various forms:
- Short-term memory (what just happened?)
- Long-term memory (what happened earlier?)
- Internal knowledge (rules, documents, instructions)
3. Tools – access to systems
Tools are connections to other systems, allowing the agent to act. Examples include:
- CRM platforms
- Email clients
- Reporting systems
- Document databases
4. Task execution – planning and following through
An agent can break tasks into steps, perform actions, evaluate results, and escalate if needed.
Where can this be applied?
Agentic AI is suited for automating tasks like:
- Handling customer requests
- Compiling reports
- Evaluating leads
- Writing emails
- Summarizing documents
- The value lies in integration
Generative AI excels at creating content. But true value comes when AI agents are embedded into workflows. They can:
- Retrieve data
- Combine and analyze information
- Make decisions based on rules
- Handle follow-ups
- Escalate exceptions
In summary
Agentic AI allows software to operate within processes autonomously – always within clear boundaries and with human oversight when needed. It supports process efficiency and makes automation of routine tasks more accessible.