AI agents are software-based systems that independently carry out tasks, support decision-making, or automate processes by using artificial intelligence in a targeted way. They do not operate in isolation; instead, they are embedded in existing processes, data sources, and systems, and act according to clearly defined goals and rules.
Unlike traditional automation or simple chatbots, AI agents can act in context, connect information from different sources, and handle multi-step tasks. This includes, for example, analyzing data, making recommendations based on defined criteria, or independently triggering downstream process steps. For instance, an AI agent can assess incoming information, prioritize it, prepare it, and route it to the right place within the company.
A key aspect of AI agents is their task orientation. They are designed for specific use cases—for example, to support procurement, quote preparation, reporting, customer service, or internal knowledge work. This clearly sets them apart from generic AI tools, which may be flexible but often cannot be integrated seamlessly into existing workflows. This fit is exactly what is crucial for sustainable value.
For AI agents to be used effectively, processes must be clearly defined and data must be reliably available. This is where upstream questions come in, such as “Which processes can be automated with AI?” or “How do I identify specific AI use cases in my company?”. They help identify realistic deployment scenarios and avoid missteps.
Tailor-made AI agents are typically developed based on an AI potential analysis as part of strategy development. Strategic anchoring ensures that AI agents do not become a technical experiment, but instead become a permanent part of efficient, scalable business processes.
