Generative artificial intelligence is transforming organizational innovation by extending its role beyond automation toward collaborative knowledge creation and creative problem-solving. Despite rapid adoption across knowledge-intensive industries, limited evidence explains how generative AI functions as a co-creator that complements human creativity, organizational learning, and strategic decision-making during innovation processes. This study aimed to examine the relationships among generative AI utilization, collaborative intelligence, AI literacy, trust in AI, knowledge integration, organizational learning, and organizational innovation performance through a human-centered collaboration framework. A mixed-methods sequential explanatory research design was employed involving 760 professionals from thirty-eight technology-intensive organizations that had implemented generative AI in research, product development, engineering, and innovation management. Quantitative data were collected using validated measurement instruments and analyzed through Structural Equation Modeling, while qualitative evidence was obtained from semi-structured interviews, innovation project documentation, organizational observations, and AI governance records. Findings revealed that collaborative intelligence significantly mediated the relationship between generative AI utilization and organizational innovation performance. AI literacy, organizational learning, and trust in AI strengthened knowledge integration and enabled professionals to transform AI-generated outputs into contextually meaningful innovations without diminishing human judgment or ethical responsibility. Results suggest that sustainable innovation emerges from complementary human–machine collaboration in which generative AI operates as a co-creator, while human expertise remains essential for strategic interpretation, ethical governance, contextual reasoning, and organizational value creation.