This study explores the future research opportunities at the intersection of Generative Artificial Intelligence (GenAI) and innovation management. It combines a review of academic literature with the results of a Delphi study involving leading innovation management scholars. The study identifies ten major research themes that can guide future research developments: 1. **GenAI and innovation types**: GenAI is likely to facilitate both incremental and radical innovation without significantly changing the basic types of innovation. 2. **GenAI, dominant designs and technology evolution**: GenAI is currently in the early stages of its technological lifecycle, with a fast adoption rate but no dominant design yet. 3. **Scientific and artistic creativity and GenAI-enabled innovations**: GenAI will enhance and empower scientific and artistic creativity, potentially leading to new conceptualizations of creativity. 4. **GenAI-enabled innovations and intellectual property**: The advancement of GenAI may render existing intellectual property protections obsolete, necessitating new frameworks. 5. **GenAI and new product development**: GenAI will change the dynamics of new product development teams and processes, enabling more real-time experimentation and validation. 6. **Multimodal/unimodal GenAI and innovation outcomes**: Multimodal GenAI systems are expected to play a bigger role in firms' competitive advantage and innovation performance. 7. **GenAI, agency and ecosystems**: GenAI will create dense networks of actors and stakeholders, modifying innovation activities and processes. 8. **Policymakers, lawmakers, and anti-trust authorities in the regulation of GenAI-enabled innovation**: Existing regulatory frameworks need to be updated or modified to address the ethical and legal challenges posed by GenAI. 9. **Misuse and unethical use of GenAI leading to biased innovation**: Ethical concerns about GenAI's misuse, such as deepfakes, can bias innovation and lead to suboptimal decisions. 10. **Organizational design and boundaries for GenAI-enabled innovation**: GenAI will redefine the notions of knowledge and expertise, potentially leading to new organizational structures and boundaries. The study concludes by discussing how these themes can inform theoretical development in innovation management studies, emphasizing the need for a comprehensive understanding of the opportunities and challenges presented by GenAI.This study explores the future research opportunities at the intersection of Generative Artificial Intelligence (GenAI) and innovation management. It combines a review of academic literature with the results of a Delphi study involving leading innovation management scholars. The study identifies ten major research themes that can guide future research developments: 1. **GenAI and innovation types**: GenAI is likely to facilitate both incremental and radical innovation without significantly changing the basic types of innovation. 2. **GenAI, dominant designs and technology evolution**: GenAI is currently in the early stages of its technological lifecycle, with a fast adoption rate but no dominant design yet. 3. **Scientific and artistic creativity and GenAI-enabled innovations**: GenAI will enhance and empower scientific and artistic creativity, potentially leading to new conceptualizations of creativity. 4. **GenAI-enabled innovations and intellectual property**: The advancement of GenAI may render existing intellectual property protections obsolete, necessitating new frameworks. 5. **GenAI and new product development**: GenAI will change the dynamics of new product development teams and processes, enabling more real-time experimentation and validation. 6. **Multimodal/unimodal GenAI and innovation outcomes**: Multimodal GenAI systems are expected to play a bigger role in firms' competitive advantage and innovation performance. 7. **GenAI, agency and ecosystems**: GenAI will create dense networks of actors and stakeholders, modifying innovation activities and processes. 8. **Policymakers, lawmakers, and anti-trust authorities in the regulation of GenAI-enabled innovation**: Existing regulatory frameworks need to be updated or modified to address the ethical and legal challenges posed by GenAI. 9. **Misuse and unethical use of GenAI leading to biased innovation**: Ethical concerns about GenAI's misuse, such as deepfakes, can bias innovation and lead to suboptimal decisions. 10. **Organizational design and boundaries for GenAI-enabled innovation**: GenAI will redefine the notions of knowledge and expertise, potentially leading to new organizational structures and boundaries. The study concludes by discussing how these themes can inform theoretical development in innovation management studies, emphasizing the need for a comprehensive understanding of the opportunities and challenges presented by GenAI.