In het kortAI agent design determines which tasks in a process can be performed by an AI agent, what type of agent is most suitable and how it integrates with existing systems. Unlike RPA, an AI agent handles unstructured input and makes contextual decisions. Business Design Studio automatically suggests the best specialist based on task type.
An AI agent is a software programme that autonomously performs tasks within a process — from analysing emails to processing invoices or generating documentation. Unlike traditional automation, an AI agent can handle unstructured input and make decisions based on context.
📧 Communication agent
Processes incoming messages, answers questions, sends notifications
📄 Document agent
Analyses, generates or reviews documents and contracts
🔍 Analysis agent
Recognises patterns in data, detects anomalies, reports
⚙️ Process agent
Coordinates steps, triggers actions in ERP or other systems
After building the process flow in the Process Step Builder, Business Design Studio suggests the best-in-class specialist for every AI step. The AI evaluates the nature of the task, the required expertise and integration options with your systems.
Frequently asked questions
What is the difference between an AI agent and RPA?
RPA (Robotic Process Automation) follows fixed, structured scripts. An AI agent understands context, processes unstructured data and can make decisions. AI agents are more flexible but require more configuration.
How do I choose the right AI agent for a process step?
Consider the nature of the input (structured vs. unstructured), the required decision complexity and integration with existing systems. Business Design Studio helps determine this automatically.
What does it cost to implement AI agents?
Costs depend heavily on complexity and platform. Simple agents (document analysis, email sorting) can be operational within weeks. More complex agents require more configuration and data training.
Can one AI agent perform multiple process steps?
Yes, but that is rarely the best architecture. One agent per logical task type gives better maintainability, testability and replaceability. Use multiple specialised agents collaborating rather than one generalist doing everything.
What are the risks of AI agents in critical processes?
The biggest risks are hallucinations (incorrect output), integration issues and lack of human oversight. Mitigate by: human validation step for high-risk decisions, output quality monitoring, and a clear fallback process if the agent fails.
How does an AI agent differ from traditional automation (RPA)?
RPA executes fixed, programmed steps on structured data — fast and cheap but fragile when processes change. An AI agent understands context, processes unstructured data and can handle exceptions autonomously. AI agents are more expensive but far more flexible.