Paper Number

ECIS2025-1554

Paper Type

SP

Abstract

Our study investigates the opportunities and challenges of increasing workplace datafication from an employee perspective. It focuses on how AI-driven data collection and analysis shape employee perceptions and influence their engagement levels. As AI becomes part of workplace operations, it introduces a complex balance between productivity gains and employee privacy, thereby influencing organizational outcomes. Using a quantitative survey, we will test the relationships between AI-driven datafication, privacy concerns, work-life conflict, productivity, and employee engagement. We specifically examine employee engagement as a key outcome, recognizing it as essential for organizational performance, retention, and job satisfaction. Overall, our study contributes to datafication research by examining the nuanced effects of increasing employee transparency on employee perceptions and attitudes. Our anticipated insights will support organizations as they navigate the complexities of datafication at work, helping them create balanced, employee-centred approaches to AI integration that promote employee engagement.

Author Connect URL

https://authorconnect.aisnet.org/conferences/ECIS2025/papers/ECIS2025-1554

Author Connect Link

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Jun 18th, 12:00 AM

DATAFICATION AT WORK: NAVIGATING AI, PRIVACY CONCERNS, AND EMPLOYEE ENGAGEMENT

Our study investigates the opportunities and challenges of increasing workplace datafication from an employee perspective. It focuses on how AI-driven data collection and analysis shape employee perceptions and influence their engagement levels. As AI becomes part of workplace operations, it introduces a complex balance between productivity gains and employee privacy, thereby influencing organizational outcomes. Using a quantitative survey, we will test the relationships between AI-driven datafication, privacy concerns, work-life conflict, productivity, and employee engagement. We specifically examine employee engagement as a key outcome, recognizing it as essential for organizational performance, retention, and job satisfaction. Overall, our study contributes to datafication research by examining the nuanced effects of increasing employee transparency on employee perceptions and attitudes. Our anticipated insights will support organizations as they navigate the complexities of datafication at work, helping them create balanced, employee-centred approaches to AI integration that promote employee engagement.

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