AI in Influencer Marketing: A Study of Artificial Intelligence in Influencer Selection, Content, Campaign Management and Performance

Influencer marketing has developed from a relationship-driven promotional activity into a data-intensive digital marketing channel. Artificial intelligence (AI) is accelerating this change by helping brands discover relevant creators, evaluate audiences, predict campaign outcomes, personalize content, identify fraudulent engagement, optimize budgets and measure return on investment. Instead of relying only on follower counts or manual research, marketers can use AI to examine large volumes of creator, audience and campaign data and make faster decisions. This assignment examines how AI is applied throughout the influencer marketing lifecycle. It explains influencer discovery and selection, audience analysis, content generation, campaign optimization, sentiment analysis, fraud detection and performance measurement. It also discusses the benefits and limitations of AI, including efficiency, personalization and improved targeting on one side, and privacy, bias, disclosure, authenticity and over-automation on the other. The study concludes that AI is most effective when used as a decision-support system rather than as a replacement for human creativity and relationships.

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Publication Details

Published
2026-10-31
DOI
https://doi.org/10.33774/coe-2026-nn89r
Primary Topic
Digital Marketing and Social Media
Type
preprint
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AI in Influencer Marketing: A Study of Artificial Intelligence in Influencer Selection, Content, Campaign Management and Performance

Piyush Kumar
Digital Marketing and Social Media
preprint

AI in Influencer Marketing: A Study of Artificial Intelligence in Influencer Selection, Content, Campaign Management and Performance

Piyush Kumar
preprint en

Abstract

Influencer marketing has developed from a relationship-driven promotional activity into a data-intensive digital marketing channel. Artificial intelligence (AI) is accelerating this change by helping brands discover relevant creators, evaluate audiences, predict campaign outcomes, personalize content, identify fraudulent engagement, optimize budgets and measure return on investment. Instead of relying only on follower counts or manual research, marketers can use AI to examine large volumes of creator, audience and campaign data and make faster decisions. This assignment examines how AI is applied throughout the influencer marketing lifecycle. It explains influencer discovery and selection, audience analysis, content generation, campaign optimization, sentiment analysis, fraud detection and performance measurement. It also discusses the benefits and limitations of AI, including efficiency, personalization and improved targeting on one side, and privacy, bias, disclosure, authenticity and over-automation on the other. The study concludes that AI is most effective when used as a decision-support system rather than as a replacement for human creativity and relationships.

University of Lucknow (IN)
Digital Marketing and Social Media
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