The Influence of Perceived Usefulness of AI within The RACE Framework on Adoption Intention and Digital Marketing Performance: A Comprehensive Literature Review

Abstract

Artificial Intelligence (AI) is changing how businesses run various digital marketing activities. Many studies have explored AI adoption and its benefits. Most of these studies focus on AI perceived usefulness, the influence of AI adoption, marketing results, or RACE as a planning framework. Though there is limited understanding of how perceived AI’s usefulness influences the adoption intention of AI, and hence the expected marketing performance. This is especially true in emerging markets such as Saudi Arabia. Understanding AI’s perceived usefulness in each stage of the RACE (Reach, Act, Convert, and Engage) framework is also important. This paper reviews previous research on AI adoption and adoption intention, the RACE framework, and marketing performance. It identifies a gap in using the technology acceptance model (TAM) model to explain how perceived usefulness of AI influences adoption intention and, in turn, digital marketing performance. It also highlights the lack of studies that apply a full marketing planning framework while analyzing these relationships. The study calls for empirical research that tests the AI adoption through the lens of an extended TAM version at each stage of RACE. Future work should use data to test this relationship. This will help marketers understand how AI adoption improves results. A stage-by-stage view helps show where AI is perceived as more useful, where it is not.