Artificial Intelligence and Deep Learning in Wedding Photo and Video Content Creation

The study's relevance is due to the growing need for fast, high-quality, personalized production of wedding photo and video content that combines artistic expression and technological efficiency. In this context, using artificial intelligence algorithms to transform creative processes deserves special attention. The article aims to study the potential of using artificial intelligence and deep learning in creating wedding visual content with a focus on improving the efficiency, quality, and level of individualization of the result. The paper applies methods of comparative analysis of the functional characteristics of modern AI-based tools, structural and semantic generalization of their application areas, and elements of practical modeling of the processes of stylistic adaptation and emotional processing of images and videos. The authors investigate the conceptual foundations of the introduction of artificial intelligence technologies into visual art and describe the use of their capabilities in the wedding segment, in particular in the areas of stylization, editing, semantic structuring and quality optimization. The study found that deep learning contributes to the artistic coherence of a visual product by maintaining compositional logic, preserving the emotional context, and reproducing the author's style. The study identified key problems that complicate the integration of solutions based on artificial intelligence technologies: technical limitations of infrastructure, standardization of visual solutions, and ethical risks regarding the reliability and confidentiality of images. The expediency of using artificial intelligence tools as an auxiliary tool for optimizing the creative process while maintaining control over the artistic result is proven. The practical value of the study lies in the substantiation of mechanisms for the effective implementation of artificial intelligence systems in the professional activities of videographers and photographers. Prospects for further research are related to the creation of specialized visual datasets, hybrid quality control models and adaptive learning platforms for training specialists in the field of wedding media production.