The rapid development of information technology, artificial intelligence has been widely used in large models, digital media content is exponential growth, people generate and use digital content is increasingly huge, when the user is faced with a huge amount of digital content how to make a choice and how to recommend the digital content that the user needs to the user who needs a specific problem, the traditional recommendation algorithms are unable to solve the contradiction between the massive information and the user’s personalised needs, traditional recommendation algorithms cannot solve this problem. Traditional recommendation algorithms cannot solve the contradiction between massive information and users’ personalised needs, and artificial intelligence technology provides new means and methods to solve this problem. This study uses artificial intelligence recommendation algorithms to construct an intelligent recommendation model for digital media content, and combines cutting-edge technologies such as deep learning, natural language processing, and user behaviour analysis to achieve intelligent recommendation of users’ personalized needs, provide personalized digital content recommendation services for different users, and improve users’ experience and satisfaction with the recommendation results. Verification is carried out through experiments, and the results show that the digital content recommendation model based on artificial intelligence has significant advantages over traditional recommendation algorithms in terms of recommendation accuracy, user satisfaction and system efficiency. The promotion and use of the artificial intelligence grand model will be conducive to promoting the dissemination of digital content and effectively improving the efficiency of people’s work and life.