The Impact of Adopting Artificial Intelligence Technologies Across Digital Marketing Stages on Marketing Performance in Saudi Companies: An Analytical Study of Marketing Innovation as a Mediating Variable

Abstract

The study examined the impact of adopting artificial intelligence across different stages of digital marketing based on the RACE model (Plan, Reach, Act, Convert, and Engage) on marketing performance. Marketing performance was measured through market share, profitability, and sales growth. The study also investigated marketing innovation as a mediating variable. A descriptive–analytical approach was adopted using a field survey method. A structured questionnaire with multiple sections was developed to measure the study variables. It was distributed to marketing managers and specialists in Saudi companies. The final sample consisted of 300 respondents selected randomly. Data analysis and hypothesis testing were conducted using SmartPLS. Structural Equation Modeling (SEM) was applied. The results showed that AI adoption in the Plan, Act, Convert, and Engage stages had a positive and significant effect on marketing performance.
However, the Reach stage did not show a significant effect. The findings also indicated that marketing innovation had no direct effect on marketing performance.  Its mediating role between AI adoption and marketing performance was not supported. This study contributes to the literature by proposing a new applied framework that integrates artificial intelligence with the RACE model in the Saudi context. It helps address a knowledge gap on how intelligent technologies can enhance marketing performance. Practically, the study guides Saudi companies to focus their investments on the most impactful stages: planning, interaction, conversion, and retention. At the policy level, the study highlights the importance of national strategies that support AI adoption in marketing and direct firms toward the most effective applications.