Accelerating color theory-based design through artificial intelligence: a conceptual welcome - Khairudin, Khayril Anwar; Yahaya, Mohamad Hafiz; Abdul Jamil, Siti Ermi Syahira; Rosli, Hazrul Marzan; Abu, Muhammad Badrulzzaman; Abd Rahman, Muh Sarip (2025)
Exploration the integration of artificial intelligence (AI) into design processes has reshaped the creative landscape, enabling designers to produce work with increased speed and precision. This conceptual paper explores the role of AI in expediting the design process specifically within the domain of color theory. While traditional color selection relies heavily on human intuition, theoretical knowledge, and iterative experimentation, AI systems offer predictive modeling and data-driven recommendations that align with established color harmony principles (Jain et al., 2022). By leveraging machine learning and generative algorithms, designers can automate tasks such as palette generation, contrast evaluation, and emotional tone mapping, thus significantly reducing the time and cognitive load required in early design stages (Luo & Moroney, 2021). Grounded in theories of computational creativity and cognitive load (Boden, 2004), this paper argues that AI can serve not only as a tool but also as a cognitive partner in design education and professional practice. However, the paper also raises critical questions about over-reliance on automation, potential erosion of creative intuition, and the ethical implications of delegating aesthetic decisions to machines. The discussion positions AI not as a replacement but as an augmentation to human creativity, particularly in contexts where color theory knowledge is foundational but often underutilized due to time constraints. This work contributes to emerging debates in design pedagogy, computational aesthetics, and AI-assisted creativity.