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In recent times, social media has been a major tool where traces of clients’ engagements of a business product or services are kept. The petabytes of daily social media data are utilized to make informed decisions grounded in context. Businesses are tapping into this chunk of data to make intelligent decisions. The use of these Artificial Intelligence (AI) technologies is shown to drive business value. Existing reviews of Social Media Analytics (SMA) use and other digital innovations lack the theorisation of the value created from the use of SMA as a digital transformation of businesses(Matarazzo et al. 2021). Davenport and Ronanki (2018), purports that there are three main business needs that make use AI technology. These are, process automation, cognitive insights and cognitive engagement. Gaining competitive intelligence from social media data has become a market requirement among businesses. Competitive intelligence is “a process that includes collection, analysis, interpretation and dissemination providing strategic information that can be used in a decision making process” (Acharya et al. 2018). Fan and Gordon (2014) indicated that social media analytics produces intelligence that contributes to creating competitive advantages and business value. On this premises, it is interesting to study the competitive intelligence capabilities of SMA and value creation. This study sought to theorise the ways to create business value from the use of SMA. The study seeks to answer the research question: What value is derived from the competitive intelligence capabilities of Social Media analytics. This research will adopt both conceptual analysis and empirical quantitative design to achieve its objectives. A cross-sectional survey research design will be adopted in this study. Managers of the banking and telecommunication companies in Ghana, specifically in Greater Accra region, will be chosen to respond to the survey questionnaire that will be administered. The key informants will be managers of these companies because their experiences, and professional knowledge about SMA use will provide reliable information to this study. The study will use partial least square-based structural equation modelling to evaluate the measurement items. This study is one of the few types of research to investigate the causal relationships between the SMA, competitive intelligence, and value creation. This study contributes to information systems literature by conceptualising the competitive intelligence capabilities of SMA to understand the value that is derived from its use.