Human-AI Co-Creation: Evaluating the Collaborative Potential of Generative AI in Design Thinking
Abstract
Generative AI is emerging as a co-creator in design processes, enabling novel forms of human-machine collaboration in fields such as product design, architecture, and UX/UI. This paper explores the integration of GenAI in design thinking frameworks, assessing how it augments ideation, prototyping, and iteration. Through qualitative case studies and design experiments, we evaluate creative synergy, user experience, and productivity. We propose a Human-AI Collaboration Index (HACI) to measure effectiveness and provide recommendations for optimized workflows.
References
Manoharan, G., Mishra, A. B., Adusumilli, S. B. K., Chavva, M., Damancharla, H., & Lenin, D. S. (2024, May). Supervised Learning for Personalized Marketing Strategies. In 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-6). IEEE.
Manoharan, G., Dharmaraj, A., Sheela, S. C., Naidu, K., Chavva, M., & Chaudhary, J. K. (2024, May). Machine learning-based real-time fraud detection in financial transactions. In 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-6). IEEE.
Chavva, M. (2025). Automating Cloud DevOps Workflows with Large Language Models: A Path to Self-Managed Infrastructure. American Journal of AI & Innovation, 7(7). Retrieved from https://journals.theusinsight.com/index.php/AJAI/article/view/121
Chavva, M. (2025). Intelligent Cloud Operations: Enhancing Infrastructure Management through Multi-Modal Learning and Predictive Analytics. Australian Journal of Cross-Disciplinary Innovation, 7(7).
Kevin Shah and Abhishek Trehan, (2024) Streamlining Software Development: A Comparative Study of AI-Driven Automation Tools in Modern Tech. International Journal of Computer Engineering and Technology (IJCET), 15(6), 1638-1650.
Trehan, A., & Pradhan, C. (2024). AUTOMATED DATA LINEAGE TRACKING IN DATA ENGINEERING ECOSYSTEMS. International Research Journal of Modernization in Engineering Technology and Science, 06(12), 3305–3312.
Shah, K. N., Gami, S. J., & Trehan, A. (2024). An intelligent approach to data quality management AI-Powered quality monitoring in analytics. International Journal of Advanced Research in Science Communication and Technology, 4(3), 109–119.
Shah, K. N., Gami, S. J., & Trehan, A. (2024). An intelligent approach to data quality management AI-Powered quality monitoring in analytics. International Journal of Advanced Research in Science Communication and Technology, 4(3), 109–119.
Pradhan, C., & Trehan, A. (2025). Integration of Blockchain Technology in Secure Data Engineering Workflows. In International Journal of Computer Sciences and Engineering (Vol. 13, Issue 1, pp. 01–07)
Gurram, H., Trehan, A., Pradhan, C., Bhadade, P., Mathurkar, P., & Dr. Sagar Ramesh Rane. (2025). Blockchain integration in information Systems: Transforming data security and transaction transparency [Research Article]. Journal of Information Systems Engineering and Management, 10(11s), 272–280.
Chavva, M., & Veera, S. (2024). Cognitive Cloud Management: Leveraging Multi-Modal Learning for Intelligent Resource Optimization and Fault Resolution. Australian Journal of Cross-Disciplinary Innovation, 6(6).
Chavva, M., & Veera, S. (2022). Multi-Modal Context Fusion for Cloud Infrastructure Management: Integrating Natural Language Understanding with Real-Time Resource Analytics. American Journal of AI & Innovation, 4(4).
Chavva, M., & Veera, S. (2023). Enhanced Hybrid RAG-LLM Architecture for Domain-Specific Cloud Infrastructure Management: Advancing Context-Aware Decision-Making Strategies. American Journal of AI & Innovation, 5(5). Retrieved from https://journals.theusinsight.com/index.php/AJAI/article/view/70
Chavva, M., & Veera, S. (2023). Dynamic Cost-Aware Language Models: A Real-Time Framework for Optimizing Cloud Resource Recommendations. International Journal of Machine Learning for Sustainable Development, 5(2), 1-15. Retrieved from https://ijsdcs.com/index.php/IJMLSD/article/view/670/258
Chavva, M., & Veera, S. (2022). Leveraging Large Language Models (LLMs) for Automated Cloud Solution Design and Architecture: A New Paradigm in Cloud Computing. International Journal of Sustainable Development in Computing Science, 4(4), 1-20. Retrieved from https://ijsdcs.com/index.php/ijsdcs/article/view/664