1.1 Background and Significance of the Study
The rapid evolution of digital marketing practices and the transformative impact of artificial intelligence technologies has raised the problem of integration of AI algorithms on Social media platforms (Corrigan, Craciun,& Powell, 2014). This is further an implication of the transitioning of traditional advertising methods into highly personalized and data-driven strategies. While AI-driven algorithms offer unparalleled opportunities for advertisers to optimize targeting precision and content personalization, they also raise significant challenges and concerns. The extensive collection and utilization of user data by these algorithms has sparked debates over privacy infringement and ethical considerations(Stalidis, Karapistolis & Vafeiadis, 2015). As AI technologies become more sophisticated, the potential for algorithmic bias, lack of transparency, and unintended consequences in social media advertising has become a pressing concern, necessitating a comprehensive examination of the prospects and challenges associated with the utilization of AI in this domain. The problem is also rooted in the need for a delicate balance between advertising effectiveness and user trust. While AI-driven algorithms have the capacity to enhance key performance indicators and deliver more relevant content to users, there is a growing recognition that ethical standards and user consent are paramount. Instances of data breaches, concerns about the misuse of personal information, and the opacity of algorithmic decision-making processes have led to a more critical scrutiny of AI-driven social media advertising. Jha & Jha (2022) in their study “Data Encryption Dispute Resolutions under Intermediary Guidelines of Information Technology Act” provide a detailed account of Challenges and Future Framework. Advertisers, social media platforms, and regulatory bodies are grappling with the challenge of fostering an environment where AI technologies can maximize advertising potential while ensuring users' rights.
Understanding how AI-driven algorithms contribute to the optimization of social media advertising is crucial for marketers (Davenport & Ronanki 2018). Insights into targeting precision, content personalization, and overall campaign effectiveness can guide advertisers in leveraging AI technologies to enhance the impact of their campaigns. This knowledge is essential for staying competitive in an increasingly digital and data-driven advertising landscape. This study also aims to shed light on the ethical considerations associated with the implementation of AI in social media advertising. As concerns about user privacy, transparency, and algorithmic bias grow, the study's findings provide a foundation for developing ethical frameworks and best practices. This is vital for ensuring responsible and user-centric advertising practices that align with evolving societal expectations.
The study's exploration of how AI-driven algorithms impact key performance indicators (KPIs) in social media advertising provides valuable benchmarks for assessing campaign success. This knowledge empowers advertisers to make data-driven decisions, allocate resources effectively, and refine strategies for better results. Understanding the comparative advantages over traditional methods is particularly relevant in optimizing advertising budgets. Industry professionals, including marketers, advertisers, and technology developers, can benefit from the study's insights. It equips them with a deeper understanding of the strengths and limitations of AI-driven algorithms, enabling informed decision-making in strategy development, technology adoption, and compliance with ethical standards.