Human-AI Co-Design and Co-Creation: A Review of Emerging Approaches, Challenges, and Future Directions

Abstract

The integration of Artificial Intelligence (AI) into creative and design processes has shifted from automation towards co-creation, positioning AI as a collaborative partner rather than a replacement. As AI-driven tools become more embedded in human-centred design, understanding their impact on interaction dynamics, ethics, and usability is critical. This review examines key advancements in human-AI co-design and co-creation fields, focusing on interaction frameworks, ethical considerations, non-linear collaboration models, domain-specific applications, and user experience (UX) design. Recent research emphasizes the need for structured frameworks that facilitate effective communication and partnership between humans and AI in creative tasks. Mixed-initiative and explainable AI (XAI) approaches play a crucial role in enhancing transparency and interpretability, allowing designers to co-create with greater trust and autonomy. Ethical concerns, such as AI’s influence on user perception and decision-making, are also gaining prominence, calling for responsible AI deployment in co-creative settings. Additionally, non-linear collaboration models redefine AI’s role as an adaptive assistant throughout iterative design stages, aligning with the dynamic nature of creative processes. Domain-specific applications, ranging from game and product design to choreography and smart manufacturing, illustrate the versatility of AI in augmenting human creativity. AI-assisted UX design further extends this impact by personalizing user experiences and streamlining workflows, ultimately improving efficiency and engagement. Despite these advancements, challenges remain in balancing AI autonomy with human control, evaluating its impact on creative workflows, and developing inclusive methodologies that cater to diverse design disciplines. This review synthesizes current research trends and identifies future directions for designing AI systems that empower, rather than replace, human expertise in creative industries.