The concept of open innovation, characterized by leveraging external ideas and collaborations, has evolved significantly with the advent of artificial intelligence (AI). This study explores how AI technologies are transforming open innovation by enhancing collaboration, improving idea generation, and optimizing innovation processes. The integration of AI allows for more efficient data analysis, real-time collaboration across geographically dispersed teams, and the automation of routine tasks, thereby accelerating innovation cycles. However, this transformation also presents challenges, including data privacy and security concerns, integration complexities, and the need for ethical guidelines. This research employs a qualitative approach, combining a comprehensive literature review with focus group discussions involving experts in the field. The findings provide insights into the key AI technologies driving these changes, the resulting transformations in innovation management models and practices, and the future trends and opportunities for AI-driven open innovation. By addressing these challenges and leveraging the opportunities, organizations can harness the full potential of AI to drive future innovation and achieve sustained competitive advantage. This study contributes to the existing body of knowledge by providing a detailed analysis of the implications of AI for open innovation theory and practice.