This study explores future research opportunities in innovation management related to Generative Artificial Intelligence (GenAI). It combines a review of academic literature with results from a Delphi study involving leading innovation management scholars. Ten major research themes emerged that can guide future research in the intersection of GenAI and innovation management: 1) GenAI and innovation types; 2) GenAI, dominant designs and technology evolution; 3) Scientific and artistic creativity and GenAI-enabled innovations; 4) GenAI-enabled innovations and intellectual property; 5) GenAI and new product development; 6) Multimodal/unimodal GenAI and innovation outcomes; 7) GenAI, agency and ecosystems; 8) Policymakers, lawmakers and anti-trust authorities in the regulation of GenAI-enabled innovation; 9) Misuse and unethical use of GenAI leading to biased innovation; and 10) Organizational design and boundaries for GenAI-enabled innovation. The paper discusses how these themes can inform theoretical development in innovation management studies. The study highlights the transformative potential of GenAI in various industries, including media, entertainment, healthcare, and pharmaceuticals. It also addresses challenges such as ethical concerns, intellectual property issues, and the need for updated regulatory frameworks. The research emphasizes the importance of understanding how GenAI can reshape innovation processes, including new product development, organizational design, and the role of AI in creative and scientific tasks. The findings suggest that GenAI can enable new forms of innovation, enhance creativity, and influence the structure of innovation ecosystems. The study concludes that future research should focus on these themes to better understand the impact of GenAI on innovation management.This study explores future research opportunities in innovation management related to Generative Artificial Intelligence (GenAI). It combines a review of academic literature with results from a Delphi study involving leading innovation management scholars. Ten major research themes emerged that can guide future research in the intersection of GenAI and innovation management: 1) GenAI and innovation types; 2) GenAI, dominant designs and technology evolution; 3) Scientific and artistic creativity and GenAI-enabled innovations; 4) GenAI-enabled innovations and intellectual property; 5) GenAI and new product development; 6) Multimodal/unimodal GenAI and innovation outcomes; 7) GenAI, agency and ecosystems; 8) Policymakers, lawmakers and anti-trust authorities in the regulation of GenAI-enabled innovation; 9) Misuse and unethical use of GenAI leading to biased innovation; and 10) Organizational design and boundaries for GenAI-enabled innovation. The paper discusses how these themes can inform theoretical development in innovation management studies. The study highlights the transformative potential of GenAI in various industries, including media, entertainment, healthcare, and pharmaceuticals. It also addresses challenges such as ethical concerns, intellectual property issues, and the need for updated regulatory frameworks. The research emphasizes the importance of understanding how GenAI can reshape innovation processes, including new product development, organizational design, and the role of AI in creative and scientific tasks. The findings suggest that GenAI can enable new forms of innovation, enhance creativity, and influence the structure of innovation ecosystems. The study concludes that future research should focus on these themes to better understand the impact of GenAI on innovation management.