Background: AI innovation, an emerging concept, refers to innovation capabilities that incorporate AI technologies. In recent years, generative AI has garnered significant attention, emphasizing the need for a deeper understanding of its role in innovation. The importance of AI innovation is exemplified by its transformative impact on various industries and sectors. However, the ways in which AI influences factors related to Innovation Capability remain unclear. Additionally, ensuring ethical and socially responsible AI innovation is an underexplored area that demands further investigation. Purpose: The purpose of this research is to better understand the ways in which AI influences factors related to Innovation Capability. By exploring this relationship, this study aimss to identify strategies that organizations can employ to harness the potential of AI technologies in their innovation capabilities. Additionally, this research seeks to investigate and address the challenges of ensuring ethical and socially responsible AI innovation, providing insights and recommendations for stakeholders to develop and implement AI innovation that align with ethical principles and societal values. Method: This study features a case study involving three well-known high-tech companies in China: Baidu, ByteDance, and Alibaba. This study employed a qualitative method, designing interviews with both internal and external actors associated with these companies. Additionally, this study analyzed existing reports and news articles to gain a more comprehensive perspective on conclusions. The frameworks proposed in the Literature Review section guided research. This study jointly analyzed the data from interviews, reports, and news articles. Initially, this study utilized interview data to update and evaluate frameworks. Subsequently, the information from reports and news articles helped us examine the updated frameworks and potentially identify new themes within them. Conclusion: The framework highlights AI's primary features: error reduction, routine task automation, data-driven decision-making, new job opportunities, and interaction with existing technologies.