The rapid integration of artificial intelligence (AI) into workplaces is fundamentally reshaping the nature of work, giving rise to AI-augmented labour systems in which human workers and intelligent technologies collaboratively perform tasks. This paper examines the future of work through the lens of AI-augmented labour, with a dual focus on productivity enhancement and the ethical challenges emerging from this transformation. It explores how AI tools as machine learning algorithms, intelligent automation, decision-support systems, and generative AI are redefining job roles, skill requirements, and organizational structures across sectors. From a productivity perspective, the study analyses how AI augmentation improves efficiency, accuracy, and speed in both routine and complex tasks. AI-enabled systems can reduce human error, optimize workflows, and enable data-driven decision-making, thereby enhancing individual and organizational performance. Rather than fully replacing human labour, AI increasingly complements human capabilities by automating repetitive functions while allowing workers to focus on higher-order cognitive, creative, and interpersonal activities. However, these gains are unevenly distributed across occupations and skill levels, raising concerns about job polarization and the marginalization of low-skilled and routine-based roles. Alongside productivity gains, the paper critically evaluates the ethical implications of AI-augmented labour. Key issues include workplace surveillance and monitoring, privacy infringement, algorithmic bias, erosion of worker autonomy, psychological stress, and the shifting balance of power between employers and employees. The use of AI in performance evaluation, hiring, and task allocation can introduce opacity and bias, potentially undermining trust and fairness in employment relationships. Moreover, continuous monitoring enabled by AI systems may intensify work pressure and blur boundaries between professional and personal life. The study emphasizes the importance of ethical governance, inclusive policy frameworks, and responsible AI design to ensure that AI augmentation leads to sustainable and equitable outcomes. It argues for reskilling and upskilling initiatives, human cantered AI approaches, transparency in algorithmic decisionmaking, and regulatory oversight to protect worker rights. By integrating productivity and ethical considerations, this paper contributes to a balanced understanding of AI-augmented labour and offers insights into how organizations and policymakers can shape a future of work that is both efficient and humane.
Sharma et al. (Tue,) studied this question.