Artificial Intelligence and Social Media Marketing: A Conceptual Study

Abstract

Artificial Intelligence, or Ai, is reshaping social media marketing by enabling more precise targeting, faster content production, and improved measurement of consumer responses. This conceptual study examines how AI systems influence marketing strategy, operational practices, and customer engagement across social media platforms. The paper integrates prior scholarship in AI adoption, digital marketing, and algorithmic communication to develop an analytic framework explaining key mechanisms and outcomes. Specifically, it conceptualizes AI-enabled social media marketing through four interrelated constructs: (1) algorithmic decision-making and personalization, (2) content generation and optimization, (3) predictive analytics and performance attribution, and (4) governance, ethics, and sustainability of marketing effectiveness. The study addresses a central problem in the literature: while research frequently documents technological capabilities, it is less explicit about how AI reshapes marketing processes end-to-end and what conditions moderate benefits and risks. The objective is to propose an integrative conceptual model that clarifies the causal pathways through which AI contributes to engagement and conversion, and to identify boundary conditions linked to data quality, platform incentives, user trust, regulatory constraints, and brand–audience alignment. By synthesizing evidence from peer-reviewed research, industry-facing measurement standards, and governance perspectives, this study offers guidance for scholars seeking to operationalize conceptual variables and for practitioners aiming to implement AI responsibly.