Rethinking Compensation Systems: The Case for AI-based Design

Traditional compensation systems often struggle to adapt to dynamic market conditions and evolving regulatory requirements with the necessary agility. This research article advocates for the adoption of artificial intelligence (AI)-based compensation systems as a transformative solution, enabling organisations to transition to fair, equitable and responsive frameworks. These systems leverage real-time data to support decision-making during periods of change and uncertainty. AI-powered compensation models foster structured, unbiased decision-making while enabling hyper-customisation of compensation packages to promote diversity and inclusion. The article highlights practical use cases for AI adoption, illustrating how these systems can drive fairness and efficiency. However, it also addresses potential hurdles, including ethical considerations, algorithmic bias, substantial investments and data privacy challenges. Ultimately, adopting AI-based compensation systems is not merely a technological upgrade but a continuous learning journey that empowers organisations to create equitable, innovative and future-ready compensation practices.

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Publication Details

Journal
NHRD Network Journal
Published
2025-04-01
DOI
https://doi.org/10.1177/26314541251375290
Primary Topic
Ethics and Social Impacts of AI
Type
article
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article

Rethinking Compensation Systems: The Case for AI-based Design

Harini Muralidharan
NHRD Network Journal
Ethics and Social Impacts of AI
article

Rethinking Compensation Systems: The Case for AI-based Design

Harini Muralidharan
article en

Abstract

Traditional compensation systems often struggle to adapt to dynamic market conditions and evolving regulatory requirements with the necessary agility. This research article advocates for the adoption of artificial intelligence (AI)-based compensation systems as a transformative solution, enabling organisations to transition to fair, equitable and responsive frameworks. These systems leverage real-time data to support decision-making during periods of change and uncertainty. AI-powered compensation models foster structured, unbiased decision-making while enabling hyper-customisation of compensation packages to promote diversity and inclusion. The article highlights practical use cases for AI adoption, illustrating how these systems can drive fairness and efficiency. However, it also addresses potential hurdles, including ethical considerations, algorithmic bias, substantial investments and data privacy challenges. Ultimately, adopting AI-based compensation systems is not merely a technological upgrade but a continuous learning journey that empowers organisations to create equitable, innovative and future-ready compensation practices.

NHRD Network JournalVol. 18(2)
Xavier School of Management (IN)
Openalex Percentile: Top 65%
Ethics and Social Impacts of AI
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