Faculty Spotlight: Sara Moussawi

Sara Moussawi is an associate teaching professor in the Information Systems Program. She studies how people connect with conversational AI in order to design systems that are trustworthy, human-centered and seamlessly integrated into daily life.

Tell me about your scholarly work.

People are using conversational AI agents for everyday tasks. But a pervasive emerging trend is that individuals are also connecting with them and relying on them in more personal ways. My research has been exploring these dynamics since the early days of Siri and Alexa – before such interactions became mainstream – examining how humans form attachments and develop cognitive and emotional perceptions that shape adoption and long-term use. I study design factors such as proactivity, interactivity, voice, humor and personalization, and how they influence whether people trust and continue using these systems. I also write about the macro-level social implications of AI, including bias in their design and deployment. Ultimately, my goal is to generate insights that help us design systems that people not only adopt but also integrate into their lives in responsible and empowering ways.

How is your scholarly work adding to the greater field?

At its core, my work is about helping people have better experiences with conversational and agentic AI. I study how users form connections with these systems, and how we can design technologies that people trust, enjoy and find truly useful. Paying attention to the user is essential to ensure these systems genuinely support people and serve their needs. These insights matter at the user level, the design level and the organizational level where questions about trust and AI’s role are increasingly front and center.

How did you become interested in this topic?

I began studying conversational AI just after Siri was introduced. At the time, these systems were marketed as basic tools for reminders or quick searches. Even then, users could customize the voice or hear a joke, simple features that hinted at something more human-like. In my early studies, I found people weren’t just using these agents functionally; they were joking with them, expressing gratitude and even treating them like companions. My 2018 paper documented these attachments long before the mainstream conversation caught up. That early work continues to shape my research today.

What are you most excited to accomplish as a faculty member at CMU?

One of the most rewarding parts of my nearly decade at CMU has been seeing students push ideas beyond the classroom: launching startups, presenting at conferences and joining national and international conversations about AI adoption and trust. A recent example is my AI & Emerging Technology Entrepreneurship course, which brought alumni together with senior IS students to test ideas, develop prototypes and even pursue pre-seed funding. What’s unique about CMU is the space to bring cutting-edge research straight into teaching, so students engage with these questions in the classroom. Looking ahead, I am excited to strengthen this full loop connecting classroom learning, research and alumni mentorship into a cycle of innovation that defines our community.

What are your goals for the next generation of scholars?

I want the next generation of scholars to keep questioning not only how systems work, but whether they should work that way. My goal is to help them pair curiosity with responsibility, so they design AI systems that resonate and are truly human-centered.