ARTIFICIAL INTELLIGENCE IN DRAWING AND PAINTING: A REVIEW OF TECHNOLOGIES, ARTISTIC PRACTICES, AND FUTURE DIRECTIONS

Artificial intelligence (AI) has emerged as a transformative force in drawing and painting, redefining artistic practice and expanding contemporary visual language through data-driven creativity (Manovich, 2019; Paul, 2015). This paper reviews major AI techniques—including neural style transfer (Gatys et al., 2015), generative adversarial networks (GANs) (Goodfellow et al., 2014; Elgammal et al., 2017), diffusion models (Rombach et al., 2022), and transformer-based architectures—and examines their role in image-making, aesthetic production, and visual culture. The study analyzes applications such as AI-assisted drawing, algorithmic painting, creative ideation, art restoration, art education, and commercial visual design (Shanken, 2014; Paul, 2015). It also discusses evaluation approaches that combine computational metrics with human aesthetic judgment (McCormack & d’Inverno, 2012), along with ethical and legal concerns related to authorship, originality, cultural representation, and data ethics (Manovich, 2019). By situating AI-generated art within broader discourses of creativity and artistic agency, this paper highlights the emergence of a hybrid human–AI creative paradigm and outlines future directions for artist-centric and ethically grounded AI art practices.