Organizations increasingly use data analytics and AI to support marketing decisions, but access

to insights does not automatically lead to action. This thesis examines what organizational

factors facilitate or hinder the translation of traditional and AI-generated insights into actionable

marketing strategies. The study is based on seven semi-structured interviews with marketing

practitioners from different sectors. The findings show that the main challenge is not data

availability, but the ability of organizations to interpret, trust, and act on insights. Important

barriers include limited time and resources, weak data interpretation, unclear ownership,

resistance to change, and hesitation toward AI-generated recommendations. Important

facilitators include managerial support, clear routines, collaboration, data literacy, and human

validation. The thesis concludes that turning data and AI insights into marketing action is mainly

an organizational process. Data and AI can support decision-making, but they create value only

when organizations have the culture, leadership, skills, and routines needed to turn insights into

action.