Large enterprises operate in a complex landscape, where bureaucracy can slow down innovation. At T-Mobile’s IT & Project Management sector, teams struggled with cumbersome processes to request and track internal demands. A change was needed: a smarter, more fluid, and intuitive experience. That’s where, through IBM Consulting, I helped design an AI-powered support platform, bridging the gap between technology, efficiency, and people.
Year
2024
Role
As the lead designer, my work went beyond the interface. I dove into Service Design, conversational UX research, and AI adoption strategy, participating in workshops with users and collaborating closely with stakeholders. Beyond technical expertise, this project allowed me to develop key consulting skills, such as strategic alignment, stakeholder management, and cross-team communication.
Team & Stakeholders
IBM | T-Mobile
The Power of Prompted Knowledge
Requesting a new IT project in a large corporation can feel like navigating a maze. For teams at T-Mobile, project managers and product owners often struggled to find the right forms, documentation, or next steps to move their ideas forward. The challenge wasn’t just about building an AI chat assistant — it was about designing a smarter way to access information, cut through bureaucracy, and scale support across departments without losing the human touch. Main challenges: • Fragmented and time-consuming internal processes • Overloaded users with no intuitive way to get support • Implementing AI without making it feel like another generic “corporate chatbot” By leveraging T-Mobile’s Design System and collaborating with a Service Design research team, I designed an AI-powered chat interface that: ✅ Guided users through project requests with natural conversations ✅ Integrated with existing IT tools to provide real-time updates ✅ Reduced dependency on manual support by offering self-service assistance ✅ Ensured scalability for future company-wide expansion I worked side by side with T-Mobile’s Service Design team, leveraging internal research to ensure the assistant asked better questions, provided smarter responses, and became a real ally in users’ daily tasks.
Impact
🚀 Faster response times for internal requests 📉 Lower operational workload – Shifted repetitive inquiries from humans to AI 💡 A first step toward an AI-powered workplace that truly collaborates