Algorithmic Stress and Leadership Repertoires: An Interpretive Study of India’s Tech Industry

This chapter navigates the central contradiction between the rhetoric of reconciling leading effectively through human-machine integration and optimizing organizational performance, on the one hand, and the realities of employee stress, fear, insecurity, and worsening work-life balance, on the other. The need for a more comprehensive understanding of the prevailing literature on transformative effects of AI, AI and leadership, and algorithmic control, informed by India’s social context, is underscored by the notable absence of indigenous Indian grammatology, the top-down ethnocentric approach to AI literature, and the lack of a bottom-up perspective from developers. The existing literature on AI and leadership fails to account for the interplay between AI and human meaning-making in the collectivist-individualistic Indian social milieu from the perspective of those who develop AI-related algorithms. Notwithstanding terms such as DevOps the human condition and micro subjective dynamics of AI development are surprisingly underexplored. This chapter therefore seeks to contextualize AI within the Indian setting, focusing on the perspectives of Big-Tech and medium-sized companies from the perspective of algorithm development and automation. It explores the relationship between the algorithmic development process, leadership, repertoires, and mental and emotional insecurities.