Algorithmic stewardship: reconceptualizing strategic leadership through indigenous and holistic cultural wisdom in a multipolar generative AI era
TL;DR
This paper proposes a conceptual framework integrating holistic cultural wisdom to navigate the opacity and contextual challenges of modern algorithmic governance, and introduces the concept of “Algorithmic Stewardship,” redefining executives not merely as resource orchestrators, but as cultural translators who harmonize machine computation with human relational ethics.
Abstract
This paper addresses the strategic tensions arising from the convergence of Generative AI (GenAI) and global multipolarity. It proposes a conceptual framework integrating holistic cultural wisdom to navigate the opacity and contextual challenges of modern algorithmic governance. Adopting a conceptual approach, this study synthesizes literature on strategic leadership, explainable AI (XAI) and cross-cultural cognition. It juxtaposes the efficiency-driven, linear logic of algorithmic decision-making with high-context, holistic epistemologies to construct a “Symbiotic Stewardship” model. Traditional Western-centric leadership models are insufficient for managing the “black box” of GenAI in a culturally fragmented global landscape. The proposed framework argues that indigenous and holistic cultural wisdom serves as a critical ethical governor. It enables leaders to balance human–AI augmentation, mitigate technological opacity and achieve contextual resonance across diverse institutional environments. Responding to the call for phenomenon-based research, this paper bridges high-tech algorithmic strategy with high-touch cognitive sociology. It introduces the concept of “Algorithmic Stewardship,” redefining executives not merely as resource orchestrators, but as cultural translators who harmonize machine computation with human relational ethics.