Meet our Team
Juliette Schuster
Core Competences
- Digital Transformation
- AI Governance
- Natural Language Processing
- Human–Technology Interactions
Juliette specializes in the human and organizational implications of artificial intelligence. Drawing on her background in Human Resources and a B.Sc. in Psychology, she examines how AI technologies influence workplace dynamics, decision-making processes, and employee experience.
Her work aims at supporting organizations in implementing AI in ways that are not only technically sound but also socially sustainable and aligned with human needs. She contributes to the analysis and evaluation of AI applications, the development and communication of compliance approaches, and the creation of research-based insights on human–AI dynamics. She is particularly interested in questions of trust, responsibility, and self-efficacy in human–AI collaboration.
Within the team, Juliette strengthens the human-centered perspective of AI strategy and helps translate technological innovation into practical, people-oriented impact.
Juliette was a key contributor to the development of the 9senses Chatbot Audit framework and methodology.
Sample Projects
Chatbot Audit
9senses product development: the objective was to develop a test methodology to measure and evaluate chatbot performances in business applications with a standardized tool.
Conversational AI Audit & Benchmarking
Development of a multidimensional Blackbox Chatbot Audit framework for evaluating chatbot user experience and business value in customer service environments. The audit methodology combines structured use-case testing with qualitative and quantitative evaluation dimensions, including answer quality, response speed, dialogue quality, and user interface assessment.
The framework also incorporates hallucination testing and edge-case analysis to assess robustness and real-world usability. The project included extensive market and user-frustration research, methodology development, pilot implementation, and iterative testing and retesting phases. The resulting audit framework is used to evaluate chatbot performance, identify optimization potential, and assess user retention likelihood and overall business impact.