This study was conducted with the aim of “developing and validating a model of AI based content marketing in startups” within a macro level framework centered on improving change management and industrial development in the context of digital transformation. The research design followed a sequential exploratory mixed methods approach. In the qualitative phase, data were collected through netnography and analyzed using a thematic network approach organized at three levels: component, dimension, and core concept. The output of this phase was the extraction of five core concepts: content production, use of automation tools, data analysis efficiency, effective content interaction and distribution, and decision making improvement, which formed the basis for developing the quantitative instrument. The content validity of the items was confirmed based on the judgment of 10 experts 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. Confirmatory factor analysis (CFA) was performed. The model fit indices were highly satisfactory. The final output of the research presents an integrated, management oriented framework that is aligned with the needs of digital transformation and industrial development. This framework clarifies how to leverage the technical capabilities of artificial intelligence to improve content quality, deploy automation, optimize distribution, and enhance data driven decision making in startups, and can serve as a basis for guiding policy making and change management in Iran’s startup ecosystem.