Objective As one of the representative patterns on Shang Dynasty bronzes, the animal face pattern has attracted widespread attention in academia for its fierce and mysterious artistic characteristics. However, the current methods of innovatively transforming traditional patterns still rely on conventional design approaches, lacking exploration of new technologies. With the rapid development of Artificial Intelligence Generated Content (AIGC), which provides a new technical pathway for the redesign of traditional patterns, the human-artificial intelligence collaborative design model has gradually become an important development direction in the field of design. Based on this, this paper takes the Shang Dynasty animal face pattern as the research object, aiming to explore the application pathways of AIGC in traditional pattern design, promote its innovation and transformation in modern women's bag design, and construct a feasible pathway for the digital innovation of traditional patterns under a human-artificial intelligence collaborative design paradigm.

Methods Taking Shang Dynasty animal face patterns as the research object, a design process of 'design factor extraction, quantitative evaluation, AIGC-based design generation, and designer optimization' was constructed. First, image data of Shang Dynasty animal face patterns were systematically collected and classified according to historical periods, and their stylistic characteristics were analyzed to form samples. Second, the Analytic Hierarchy Process was used to construct an evaluation model for the design factors of Shang Dynasty animal face patterns, and experts were invited to evaluate them; the weights of each factor were calculated, and typical design factors were selected. Based on the factor weights, the construction of AIGC prompts was guided, and AIGC tools were used to automatically generate the factors. Finally, designers screened, adjusted, and refined the AIGC-generated results to ensure that the final design met the application requirements in terms of cultural accuracy, aesthetics, and practicality, resulting in the final design scheme.

Results Based on the Analytic Hierarchy Process, the design factors of Shang Dynasty animal face patterns were quantitatively evaluated. Among them, the ornament factor (B1) had the highest weight, while in the scheme layer, the Late Shang factor (C3) and the semantic factor (C8) had higher weights, clarifying the primary and secondary relationships of the design elements and the priority order for transformation. Secondly, the design factor weights were used to guide the construction of AIGC prompts, enabling the collaborative transformation of semantic factors, ornament factors, and color factors, resulting in six modern women's bag design schemes. Finally, experts and users were invited to evaluate the design schemes to select the final design scheme.

Conclusions The collaborative application of the Analytic Hierarchy Process (AHP) and AIGC technology can effectively achieve the screening and visual transformation of Shang Dynasty animal face patterns design factors, and form a systematic pathway from factor extraction to modern women's bag product design. By constructing AIGC prompts based on design factor weights, the collaborative transformation of semantic, ornament, and color factors is facilitated, which not only improves design efficiency but also enhances the diversity and visual expression of design schemes. The human-artificial intelligence collaborative design paradigm established preserves the cultural characteristics of Shang Dynasty animal face patterns while realizing their innovative application in modern women's bag design.