THE IMPACT OF AI-BASED AUTOMATION ON INCOME STABILITY OF GIG WORKERS

Ankur Goyal
Research Scholar,
Dr. Shiv Kumar
Research Guide,

Department of Economics, Shri JJT University, Jhunjhunu, Rajasthan, India

Abstract :This study examines how algorithmic management, task automation, and platform-driven decision-making influence earnings consistency, job availability, and financial security among gig workers. While AI enhances efficiency, matching accuracy, and productivity, it also introduces volatility through dynamic pricing, demand fluctuations, and reduced human oversight. The research highlights a dual impact: increased opportunities for high-skilled workers who can adapt to AI tools, and heightened precarity for low-skilled workers facing task displacement and unpredictable income streams. Furthermore, the study explores the role of platform policies, worker adaptability, and regulatory frameworks in mediating these effects. The findings suggest that without adequate safeguards—such as minimum earning guarantees, transparency in algorithms, and access to up skilling—AI-driven automation may exacerbate income instability and inequality within the gig workforce. The paper concludes by recommending policy interventions and platform accountability measures to ensure a more equitable and sustainable gig economy.

Keywords: AI-based automation, gig economy, income stability, algorithmic management, platform work, job precarity, digital labor, income volatility, economic inequality