Fair and Inclusive Customer Segmentation in AI- Driven Marketing

Title

Fair and Inclusive Customer Segmentation in AI- Driven Marketing

Creator

Benny, Jeeva; Kaur, Jasmine

Description

This chapter explains how artificial intelligence has evolved customer segmentation from a marketing tool into a socio- technical decision mechanism with implications for fairness, inclusion, and cultural representation. In the chapter, algorithmic segmentation is analyzed using clustering methods, explainable frameworks such as LIME and SHAP, and fairness metrics to identify or alleviate structural bias in multicultural markets. It discusses accuracy fairness trade- offs, transparency, emotional trust, and organizational capability gaps, especially when segmentation outputs flow into generative AI driven personalization. Through case studies on multicultural targeting, AI sales agents, misinformation flows, and exclusion in finance, employment, and welfare, the authors show how segmentation systems affect society. The chapter concludes with strategic, ethical, and policy recommendations for responsible, inclusive AI marketing grounded in fairness aware segmentation. 2026 by IGI Global Scientific Publishing. All rights reserved.

Source

AI-Driven Decision-Making for Diversity, Equity, and Inclusion in Marketing;pp.261-288

Date

01-01-2026

Publisher

IGI Global

Subject

And Inclusion (DEI); Customer Segmentation; Diversity; Equity; Explainable Artificial Intelligence (XAI); Generative AI (GenAI); LIME (Local Interpretable Model Agnostic Explanations); Proxy Bias; SHAP (SHapley Additive exPlanations)

Coverage

Benny J., Christ University, Bangalore, India; Kaur J., Christ University, India

Rights

All Open Access; Hybrid Gold Open Access

Relation

ISBN: 979-833736733-0; 979-833736731-6;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.4018/979-8-3373-6731-6.ch010

https://www.scopus.com/pages/publications/105033221708?origin=resultslist