Investigating the Acceptance Factors of Marketing Systems Based on Artificial Intelligence in Small Industrial Companies

Abstract

The adoption of artificial intelligence (AI) based marketing systems by companies is increasing. These systems can help companies improve their marketing performance, increase their market share, and reduce their marketing costs. Few researchers, in this regard, have sought to investigate the causes of the nonacceptance of marketing systems based on AI. This article uses the qualitative research method to identify the effective factors in the adoption of marketing systems based on AI. The current study is practical in aim and qualitative in essence, utilizing an exploratory methodology. The statistical population of the research includes 238 studies including articles on the factors of acceptance of marketing systems based on AI between 2019 and 2024. The data collection tool was selected in the form of a systematic review and library studies of literature and previous researches, and the research method is the meta-synthesis of Sandelowski and Barroso. The sampling method is also selected based on the entry and exit criteria of the PRISMA (preferred reporting items for systematic reviews and meta-analyses) method. PRISMA is a framework for evaluating and enhancing the quality of review articles and scientific studies through systematic review and meta-synthesis. The findings of this research show that the four factors of functional expectations, usage expectations, organizational factors, and user intent have a significant effect on the acceptance of these systems. Companies that promote a culture of learning and embracing innovation are more likely to adopt these systems. These findings can help companies to increase the adoption of AI-based marketing systems in their organization.