Influencer marketing has become a dominant force in digital advertising by leveraging social media personalities to boost brand visibility and engagement. Although much research focuses on short-term metrics like likes, shares, and views, a significant gap remains in understanding its long-term effects on consumer loyalty and purchasing behavior. As influencer marketing grows increasingly commercialized, concerns about authenticity and audience trust intensify, necessitating an examination of how excessive brand endorsements shape consumer perceptions. Additionally, the role of artificial intelligence (AI) in influencer selection is underexplored. AI-driven algorithms are transforming how brands identify and collaborate with influencers, yet challenges related to selection biases, predictive accuracy, and ethical concerns persist. This study aims to bridge these research gaps by developing a framework to assess the long-term effectiveness of influencer marketing on brand loyalty, investigating the balance between authenticity and commercialization in endorsements, and evaluating the efficiency and fairness of AI-based influencer selection models. By tackling these novel characteristics, the study will offer regulators, businesses, and marketers helpful recommendations on how to improve tactics for continuous engagement, ethical content promotion, and increased customer confidence. In the end, the results will support the changing conversation on influencer marketing, thereby assuring that it stays a reliable, scalable, and real advertising tool.