Empowering Firms With AI-Generated Content: Strategic Approaches to R&D and Advertising in the Era of Generative AI

Abstract

Commercial utilization of generative artificial intelligence (GAI) is expanding rapidly. However, few studies have investigated the transformative impact of GAI on business operations, with a specific focus on research and development (R&D) and advertising facilitated by AI-generated content (AIGC) empowerment; particularly, there is a lack of analysis on the impact of AIGC iteration on firms’ decision-making. The study uses the optimal control and learning-by-doing method to examine two types of AIGC strategies, the single AIGC (enhancing R&D exclusively) and the dual AIGC (simultaneously boosting R&D and advertising), to delve into their dynamic iteration effects on firms’ performance. Our findings reveal that, under the single AIGC strategy, focusing on investments in the AI training R&D sector alone can enhance the GAI smartness level more effectively than adopting the dual AIGC strategy. Conversely, under the dual AIGC strategy, firms initially tend to select GAI empowerment toward the downstream advertising sector more than the upstream R&D sector. Both strategies demonstrate enhanced profits and increased demand with higher rates of AIGC self-learning. Notably, considering the limited budget, firms prioritize allocating AI training resources to the R&D sector under the dual AIGC strategy, guaranteeing their long-term success.