Inclusive AI in the Intelligent Economy: An Intersectional Framework for Equality, Diversity, and Ethical Innovation

Abstract

Artificial intelligence (AI) increasingly informs consequential workplace decisions, including recruitment, task allocation, performance monitoring, promotion, and dismissal. Although AI systems may improve efficiency and support organisational innovation, they can also reproduce structural inequalities when data, design assumptions, and governance arrangements fail to account for intersecting social positions. This article develops an intersectional framework for governing workplace AI in the intelligent economy. Using an integrative literature-review and conceptual framework-development approach, the study synthesises scholarship on algorithmic fairness, workplace AI, algorithmic management, explainability, accountability, auditing, and participatory governance. The analysis identifies four interdependent requirements for inclusive AI governance: equitable distributive outcomes, meaningful procedural safeguards, continuous technical accountability, and clearly assigned institutional responsibility. The article argues that bias mitigation and nominal human review are insufficient when workers cannot understand, contest, or influence consequential automated decisions. Inclusive governance instead requires lifecycle-based risk management, accessible explanation and redress, substantive human oversight, and meaningful participation by affected workers and communities. The proposed framework offers practical guidance for organisations and policymakers seeking to embed equality, dignity, accountability, and ethical innovation in AI-enabled workplace decision-making.