Agentic AI
What is Agentic AI?
Agentic AI is a special form of artificial intelligence in which so-called «agents» autonomously take on tasks, make decisions, and respond to situations – almost like a digital colleague. Unlike traditional systems, Agentic AI doesn't wait for commands but actively works toward a goal. Each agent has the following key characteristics:
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Goal-oriented: The agent works toward a specific outcome.
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Aware: It recognizes what is happening and adapts accordingly.
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Autonomous: It knows what needs to be done and can carry out tasks independently.
What is the difference between traditional AI systems and Agentic AI?
Traditional AI systems only perform tasks when they receive a specific input. They react – usually based on fixed rules or trained patterns. Agentic AI goes far beyond that:
It thinks proactively, stays active, plans steps independently, and pursues defined goals. This allows it to handle complex workflows – especially when flexibility is required or multiple steps build on each other.
Example from customer service:
Traditional (reactive):
A chatbot answers simple questions like «How do I change my password?» or «Where is my package?» It only responds to direct inquiries and follows predefined rules.
Agentic (goal-driven):
An intelligent AI agent understands the underlying concern, searches the CRM for information, asks follow-up questions, initiates a return, orders a replacement item – or forwards the case to support if needed.
All in one smooth process – without separate instructions.
How does Agentic AI work?
For an AI agent to operate autonomously, it needs several interconnected components:
- A goal or task
The agent knows the desired outcome, such as «verify invoice» or «schedule a customer appointment». - A context
The agent understands the situation it’s in: What information is available? Are there constraints or rules? - Data sources and tools
The agent accesses internal databases, emails, calendars, APIs, or other systems to complete its tasks. - Autonomous decision logic
Using artificial intelligence (e.g., LLMs like GPT), the agent analyzes content, makes decisions, or asks targeted questions. - Coordination and collaboration
Often, multiple agents work together. A «supervisor agent» coordinates activities, a «task agent» executes tasks, and a «memory agent» retains important information. - Learning and adaptation
Some agents can learn from experience and improve future decisions. They adapt to new situations without needing to be reprogrammed.
Agentic AI is not a single tool, but a system of goal pursuit, perception, decision-making, and action working together in harmony.
What are the benefits of Agentic AI?
Agentic AI is relevant for businesses, public institutions, and teams because it goes beyond what traditional automation can achieve. Agents act flexibly, think ahead, and adapt to new situations – without constant human intervention. This makes them especially valuable in dynamic environments – where processes often change, new information emerges spontaneously, fast decisions are needed, or tasks are complex.
- Saves time: Many work steps run automatically
Flexible: Even edge cases are recognized and handled - Creates structure: Decisions are transparently documented
- Scales easily: Agents can be extended or adjusted with minimal effort
- Enhances customer experience: Agents respond faster, more personally, and around the clock – for example in support requests or appointment scheduling
- Reduces errors: AI agents work consistently and don’t forget steps – ideal for repetitive tasks like checks or approvals
- Increases speed: Processes run significantly faster, as there’s no need for manual follow-up or handovers
- Improves collaboration: Agents bridge systems, gather information, and make it accessible to all stakeholders