LUCKNOW, 2nd February 2026: A multi-institutional team, including a researcher from the Indian Institute of Management Lucknow, has examined the ethical implications of Artificial Intelligence (AI) in marketing. The research emphasisesthate ethical AI usage is central to ensuring equity, fairness, and sustainable business performance. For the same, the research team comprehensively examined the existing literature of established ethical theories and critically analysed how AI-driven marketing practices affect key stakeholders.
The researchers analysed several unsuccessful implementations of AI and drew the conclusion that AI should not be viewed as an abstraction.
Microsoft's Tay is a primary example that showed how unregulated machine learning can perpetuate toxic social biases through assimilation. The Facebook–Cambridge Analytica controversy is another example of user privacy violations due to AI-driven data analytics that, without appropriate regulatory frameworks, is liable to violate users’ privacy. Amazon’s AI-based recruitment tool was discontinued since it was biased against women, demonstrating that inequity can be reproduced using historical data. All these examples demonstrate that without proper governance, there is a high risk that utilized data and values in AI can be biased or inequitable, making transparency, ethical AI design, and human governance indispensable.
Published in the prestigious American Business Review (an ABDC A rated journal), the findings of this study have been co-authored by Prof. Priyanka Sharma, Professor, IIM Lucknow, along with Prof. V. Kumar, Brock University, Ontario, Canada, Prof. Ashutosh Dixit, Cleveland State University, Ohio, U.S.A., and Prof. Sudipendra Nath Roy, St. Cloud State University, Minnesota, U.S.A. Based on frameworks including utilitarianism, deontology, virtue ethics, ethics of care, and contractarianism, the paper offers a structured ethical perspective to evaluate the growing influence of AI in contemporary marketing systems.
The research team specified five major ethical issues regarding the use of AI in marketing. These include:
- Monopolisation
- Privacy concerns
- Corporate social responsibility
- Human rights
- Accountability
The research team used real-world situations to guide us through how these issues arise and how they impact consumers, companies, and the general population.
The study proposes a set of theory-based solutions from ethical frameworks to combat these issues. It-
-Advocates data democratisation to curb excessive market concentration and monopolistic power by enabling broader, fairer access to data resources.
-Emphasises contextual and purpose-driven data usage, ensuring that consumer data is collected and deployed strictly within ethically justified and transparently communicated boundaries.
-Underscores the importance of adhering to international human rights protocols, particularly in preventing discrimination, protecting autonomy, and upholding dignity in algorithmic decision-making.
-Calls for the creation of robust AI governance mechanisms, including clear accountability structures, ethical review processes, and institutional safeguards such as independent AI ombudspersons, to promote transparency, responsibility, and trust in AI-enabled marketing practices.
Speaking about the study, Prof. Priyanka Sharma said, “AI has become both indispensable and deeply challenging for firms. Thus, AI practices grounded in theories of Ethics such as Utilitarianism and Deontology, can help businesses address issues of privacy, accountability, and corporate social responsibility in their marketing applications. Frameworks like data democratization and governance through AI ombudsperson are the key for responsible and equitable use of AI-driven marketing practices.”
With this conceptual framework, the research team have made a notable contribution to the discourse on responsible AI in marketing. By providing guidance for academics, practitioners, and policymakers, seeking to balance technological innovation with ethical responsibility and outlines future research directions to further strengthen ethical AI adoption.
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