Convergence of AI and Content Marketing in the Digital Transformation of Businesses

Abstract

This study was conducted with the purpose of “developing and validating a model of the convergence of artificial intelligence and content marketing in the digital transformation of businesses.” The research design followed a sequential exploratory mixed-method approach. In the qualitative phase, semi structured interviews were conducted with experts in communication, digital marketing, and artificial intelligence. The data were analyzed using the thematic network approach at three levels—components, dimensions, and core concepts. The output of this phase yielded five principal concepts: “content creation,” “use of automation tools,” “efficiency of data analysis,” “effective interaction and content distribution,” and “enhancement of decision making,” which formed the basis for developing the quantitative instrument. The content validity of the items was confirmed through expert judgment and the Content Validity Ratio (CVR) with a threshold of 0.62. In the quantitative phase, the final questionnaire was distributed online, and 489 valid responses were collected. A confirmatory factor analysis (CFA) was performed; nine items with low factor loadings, as well as the “search engine optimization” factor, were removed to improve model fit. The measurement model fit indices and chi square ratio were found to be satisfactory. The final outcome presents a coherent and reliable framework that clarifies the linkage between the technical capacities of artificial intelligence and the content strategic needs of startups, offering a practical roadmap for designing and assessing content quality, implementing automation, optimizing distribution, and strengthening data driven decision making.