TRANSFORMING REVENUE MANAGEMENT WITH UX-DRIVEN GENAI FOR ENTERPRISE CPQ SYSTEMS

Revenue management in enterprise environments has traditionally relied on static, rule-based models that often fail to adapt to dynamic market conditions and complex product configurations. This study examines how the integration of UX-driven Generative AI (GenAI) into enterprise Configure-Price-Quote (CPQ) systems transforms revenue management by simultaneously enhancing financial performance and user experience. A mixed-method design was adopted, combining survey-based quantitative data from 320 participants with qualitative insights from 25 expert interviews across technology, manufacturing, and telecommunications sectors. Results demonstrate significant improvements in deal win rates, pricing accuracy, gross margin, and cycle time reductions following the adoption of GenAI-enabled CPQ systems. Regression and structural equation modeling confirmed that GenAI features such as recommendation accuracy, personalization, and automation directly predict revenue outcomes, while UX design mediates adoption and utilization. Comparative analysis further revealed sectoral and organizational size differences, with technology firms and larger enterprises realizing the greatest efficiency gains, and smaller firms benefiting most from personalization and customer engagement. The findings highlight the dual importance of technological intelligence and human-centered design in shaping the next generation of enterprise CPQ systems. This research contributes to the growing literature on AI-enabled revenue management and provides actionable insights for managers seeking to optimize both user adoption and financial outcomes.