Companies are under increasing pressure. Processes are fragmented, information is scattered, and many tasks consume valuable time without directly contributing to value creation. At the same time, expectations are rising: respond faster, make better decisions, and align the organization for the future.
Artificial intelligence can provide targeted support—especially in the form of AI agents. These intelligent software components take on tasks autonomously, consolidate information from various sources, and noticeably ease the workload for employees. As extensions of standard generative AI tools like ChatGPT or Microsoft Copilot, AI agents are tailored to specific tasks and build on existing tools. Rather than being generalists, they access defined data sources with a clear purpose in mind. Whether as a research assistant, for quality checks, or supporting day-to-day project work—their strength lies in executing specialized tasks efficiently and reliably.
AI agents can be integrated directly into existing workflows without adding complexity. They improve decision-making, increase efficiency, and adapt flexibly to company-specific requirements. As context-sensitive solutions, they blend seamlessly into familiar applications—and in many cases, can even be created without deep programming knowledge. Dedicated tools support configuration and make it easy to get started.
What exactly are AI agents and what makes them so powerful?
AI agents are specialized software components powered by generative AI. Unlike traditional automation tools that follow fixed rules, AI agents are context-aware. They take on tasks, access data from different systems, and interact directly with users. In practice, there are three main types of AI agents:
- Retrieval agents search internal data sources and answer specific questions. They're ideal for knowledge management, customer support, or checking requirements and policies.
- Task Agents perform targeted tasks, such as filling out forms, generating text, or triggering processes. They are often the first step in agent-based automation.
- Autonomous agents work in the background. They coordinate multiple tasks or other agents, monitor workflows, and intervene only when necessary.
This clear focus on specific tasks makes AI agents incredibly versatile. They provide immediate relief without requiring new tools or disrupting existing processes.
AI Agents in Microsoft 365 – How Copilot Agents Work in Daily Business
Many AI agents don’t operate in new tools but are embedded directly into familiar platforms like Microsoft Teams, SharePoint, or ERP systems. Depending on your needs, they can be built with various tools—from simple use cases with Agent Builder to more advanced setups using Copilot Studio or fully customized agents with a backend in Microsoft Azure. The result: tailored solutions that reflect your company’s specific requirements.
The following examples from Microsoft 365 Copilot illustrate how specialized agents are already supporting employees in daily business:
Microsoft 365 Copilot Agents
Tap into customizable knowledge sources and support users with content creation and inquiries.
SharePoint Agents
Enable targeted research and analysis within existing SharePoint content.
Facilitator Agent
Assists in Microsoft Teams by generating summaries or providing context during meetings and chats.
Project Manager Agent
Manages tasks in Microsoft Planner, creates status updates, and reduces workload for project leads.
Interpreter Agent
Translates spoken content in Microsoft Teams meetings in real time, facilitating international collaboration.
Employee Self-Service Agent (currently in private preview)
Allows employees to submit HR or IT-related requests—such as vacation planning or support ticket creation—directly and efficiently.
These use cases demonstrate just how adaptable AI agents can be—regardless of industry or department. More important than the business area is identifying repetitive tasks that slow down operations.
How companies can get started
Getting started with AI agents doesn’t require a big, complex rollout. In fact, the best results often come from small, focused use cases. A structured approach leads to quick wins.
These three steps can help:
Diese Anwendungsfelder zeigen, wie flexibel KI-Agenten eingesetzt werden können – unabhängig von Branche oder Funktionsbereich. Wichtiger als das Einsatzfeld ist die Frage, wo wiederkehrende Aufgaben Zeit binden und operative Abläufe ausbremsen.
Conclusion: AI agents as a practical lever for efficiency
AI agents represent the next stage of AI adoption in the enterprise. They address the most time-consuming tasks and provide real relief. Routine work is automated, information becomes more accessible, and decision-making improves.
Early adopters reap multiple benefits: time savings, improved process quality, increased responsiveness, and more focus on value-added activities. Best of all, no new tool landscape is required - just smart integration with what already exists.
The barriers to entry are low and the benefits are tangible. Now is the time to explore AI agents and unlock their everyday value.
Want to learn more about AI agents or already have a use case in mind? Get in touch with us today!
