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University of Graz IDea_Lab Digital Community Lab Micro-Degree AI and Society Featured projects AI Scheduling Assistant for WhatsApp Groups
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AI Scheduling Assistant for WhatsApp Groups

Field of action: Economic aspects of AI
Supervised by: DI (FH) Michael Freidl MA
Students: Anton Herrschel, Julia Kindermann, Alisa Sopina
Conducted: Summer semester 2026

As part of this course, students developed an AI-powered Scheduling Assistant for WhatsApp groups. The project demonstrates how technical, legal, and business considerations can be integrated into a real-world AI application. Finding a suitable meeting time in WhatsApp groups is often time-consuming and fragmented across numerous messages or external scheduling tools. To address this challenge, the students designed a Scheduling Assistant that is directly integrated into the group chat. The assistant remains permanently accessible, collects availability information from all group members, and uses AI to identify the most suitable meeting time. Once a date has been selected, it can be transferred to a calendar with a single click. The application supports multiple input methods. Users can provide their availability through voice input, direct interaction with the assistant, automated analysis of existing chat messages, or a traditional calendar interface. A color-coded overview (green, yellow, and red) immediately highlights which time slots are most suitable for the group, making the decision process transparent and efficient. Beyond the user experience, the project also addresses key technological and organizational aspects. Students developed a technical concept based on modern Natural Language Processing (NLP), evaluated data protection requirements, considered compliance with the EU AI Act, and designed a viable business model for the solution. Accompanying app screenshots illustrate the complete workflow, from activating the assistant within a WhatsApp group to receiving the final scheduling recommendation. The project provides a practical example of how AI can be applied to solve everyday coordination challenges while balancing usability, regulatory requirements, and commercial viability.

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