Photo circa 2017
Riley Hunter
Riley Hunter is a Lead UX Researcher who specializes in Generative AI (GenAI) product research, development, and benchmarking. He helps teams craft and implement comprehensive mixed-methods UXR programs. He excels in both quantitative research and data analysis, qualitative research question design, and strategic, creative thinking for organizational AI product development strategy. Riley holds an MFA in Design, focusing on UX research with emergent technologies, and an MA in Social Research for Public Health, specializing in health technology adoption.
Riley has extensive experience leading multi-disciplinary teams in AI-powered product design and development. His research spans consulting, biotechnology, robotics, and public health—highlighting his versatility and depth of experience in different high-tech fields. Riley’s background includes collaboration with data scientists, machine learning engineers, and executives to deliver scalable solutions and align on high-impact problems. His roles at BCG, PathAI, Amazon Robotics, and his work in international public health technology adoption provide him with a unique perspective in UX research, design, and technology adoption.
Riley is passionate about leveraging best-in-class product research methodologies, including qualitative and quantitative methods, to drive impactful product discovery, evaluation, and development.
Key Contributions:
Generative AI Research: Lead for BCG’s knowledge management team, focusing on algorithm-powered user experiences and adoption strategies.
Survey Standardization & Optimization: Introduced and improved survey programs, boosting response rates and data quality, leading to better business insights.
Enterprise Adoption Research: Directed quantitative studies for multi-million dollar product decisions, influencing strategies for 20,000+ users.
AI Interface Development: Led research and prototype testing for advanced, action-based conversational agent interfaces.
Open-Source LLM Development & Evaluation Frameworks: Planned strategic R&D initiatives for advanced open-source LLMs, ensuring alignment with organizational needs. Introduced MT-Bench-based LLM evaluation and monitoring plans.
Retrieval to Recommender System Transformation: Guided strategic roadmaps to innovate BCG’s knowledge discovery systems into advanced recommender system