Methodological Approaches to Using Artificial Intelligence to Develop Creative Skills in Future Designers

Abstract

The article analyzes methodological approaches to leveraging artificial intelligence (AI) technologies to foster the creative abilities of future designers. This study is highly relevant in the context of rapid digital transformation and the pervasive integration of innovative digital technologies across all sectors of society. It underscores the urgent need to revise and update pedagogical approaches that nurture creativity-a fundamental competence for modern designers. The purpose of this study is to develop a methodological framework for the effective integration of artificial intelligence tools into the training process of future designers, aimed at enhancing their creative potential, critical thinking, and adaptability in the context of digital transformation. The authors examine the specific potential of using generative AI models, such as Leonardo.AI and Microsoft Copilot (with DALL-E 3 integration), which enable rapid concept generation, as well as language AI models like ChatGPT and Gemini that automate text processing, information retrieval, and idea generation. A comprehensive examination of both theoretical and practical ramifications of integrating these tools into vocational education (specialty A5) is presented. The integration of these AI tools has the potential to optimize the training process, enhance creative imagination, and develop analytical skills and adaptability required by today's competitive labor market. The research methodology is based on a comprehensive model that integrates elements of competency-based, systemic, and personality-oriented approaches to creativity development. A comparative analysis of traditional teaching methods and innovative AI-based approaches is provided, emphasizing the formation of flexible and non-standard thinking in students. The study's findings highlight the necessity of continuous monitoring of the impact of AI technologies on the educational process to enable timely adjustments in methodological solutions and to manage risks associated with the automation of creative tasks. Based on an extensive review of the literature and open-source data, the study identifies both the advantages and limitations of using AI in design education. The authors note risks such as overreliance on automated content generation and potential loss of traditional design skills. To address these challenges, the article proposes a series of recommendations for the phased introduction of AI technologies through introductory classes, practical projects, brainstorming sessions, and creative competitions. These measures are designed to support the comprehensive development of students' creative potential and to maintain a balance between digital automation and hands-on, traditional design skills. In conclusion, the results demonstrate the feasibility and necessity of integrating AI into design education to develop professional, innovative, and transferable skills among future designers, equipping them to effectively compete in the evolving digital economy.