--- title: "Generative AI in the Marketing Industry: An Industry Analysis of Content Transformation, Consumer Engagement, and Firm Performance · AI Fault Line" url: https://aifaultline.com/research/p/doi-10-64818-pijmess-3107-4626-0050/ description: "AI Fault Line is a neutral, evidence-cited field guide to why experts looking at the same developments disagree about AI's effect on productivity, jobs, inequality, regulation and the pace of change." --- [Research](https://aifaultline.com/research/) # Generative AI in the Marketing Industry: An Industry Analysis of Content Transformation, Consumer Engagement, and Firm Performance Diya Devadiga, P. S. Aithal · Poornaprajna International Journal of Management Education & Social Science (PIJMESS) · 29 May 2026 [Read original source](https://doi.org/10.64818/pijmess.3107.4626.0050) Where this sits in the debate - [Will AI actually boost productivity and growth?](https://aifaultline.com/debate/productivity/) · its finding supports the claim ([why studies differ](https://aifaultline.com/debate/productivity/#why)) Direction of the finding as read from the abstract by an AI model ([AI-written](https://aifaultline.com/about/)). ## Key takeaway [AI-written](https://aifaultline.com/about/) A qualitative industry analysis (using SWOC/ABCD/PESTEL frameworks over secondary sources) argues generative AI is improving marketing content creation, personalization, and operational efficiency while raising algorithmic-bias, privacy, and cybersecurity concerns. It's a practitioner-oriented synthesis rather than new empirical measurement of firm performance effects. ## Abstract Purpose: This study aims to analyze the impact of Generative Artificial Intelligence (GenAI) on the marketing industry with a focus on content transformation, consumer engagement, and firm performance. The research examines how GenAI is reshaping traditional marketing practices through automation, personalization, and integration with Marketing Technology (MarTech) systems. It also seeks to understand the opportunities, strategic implications, and challenges associated with the adoption of AI-driven marketing technologies. Methodology: The study adopts an exploratory and analytical research approach based on secondary data collected from peer-reviewed journals, academic publications, industry reports, and digital sources. Various analytical frameworks such as SWOC (Strengths, Weaknesses, Opportunities, Challenges), ABCD (Advantages, Benefits, Constraints, Disadvantages), and PESTEL (Political, Economic, Social, Technological, Environmental, Legal) analyses are used to evaluate the internal and external factors influencing the adoption of Generative AI in marketing. The study also incorporates stakeholder perspectives to understand the impact of GenAI on businesses, consumers, policymakers, and investors. Results & Analysis: The findings indicate that Generative AI significantly improves content creation, marketing automation, personalization, customer interaction, and operational efficiency. AI-driven tools enable businesses to generate scalable and data-driven marketing strategies that enhance customer engagement and improve return on marketing investment. The SWOC and ABCD analyses highlight major advantages such as efficiency, innovation, personalization, and competitive advantage, while also identifying challenges including ethical concerns, algorithmic bias, cybersecurity risks, and data privacy issues. The PESTEL analysis further emphasizes the role of political, economic, social, technological, environmental, and legal factors in shaping the future of AI- ## About this publication **Academic journal.** Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth. Published 2026 (5 months ago) Citations 0 (OpenAlex) 0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison. [Chart: published 2026] ## More on this topic Related by theme, not necessarily by method or conclusion. - [Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality](https://aifaultline.com/research/p/doi-10-2139-ssrn-4573321/) SSRN · 2023 - [Generative AI at Work](https://aifaultline.com/research/p/doi-10-1093-qje-qjae044/) The Quarterly Journal of Economics · 2025 - [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot](https://aifaultline.com/research/p/doi-10-48550-arxiv-2302-06590/) arXiv · 2023 - [The Productivity J-Curve: How Intangibles Complement General Purpose Technologies](https://aifaultline.com/research/p/doi-10-1257-mac-20180386/) American Economic Journal Macroeconomics · 2020 Overview assembled automatically from collected metadata. [How this site is built](https://aifaultline.com/about/).