Abstract
Artificial intelligence (AI) is increasingly used to support organisational decisions about hiring, work allocation, performance, and resource distribution. Most management research treats AI as a tool that helps leaders make decisions. This paper asks a broader question: how might AI change the basis on which organisational authority is exercised and recognised as legitimate? The paper combines Max Weber’s account of legitimate authority with Martin Heidegger’s concept of Gestell, or Enframing. Weber explains why people accept authority: because it is grounded in tradition, personal leadership, or formal rules and offices. Heidegger helps explain how AI can turn these sources of authority into data that can be measured, ranked, predicted, and optimised. The paper argues that AI does not simply replace human leaders. Instead, it can redistribute authority among managers, employees, algorithms, data infrastructures, and organisational procedures. The analysis shows how AI may reshape traditional authority by treating custom and precedent as historical data; charismatic authority by measuring engagement, influence, and communication; and legal-rational authority by embedding rules and discretion in scores, rankings, and automated workflows. It also develops a Human-centred governance framework built around accountability, transparency, contestability, meaningful human oversight, legitimacy, and institutional design. The paper contributes a Weber-Heidegger framework for studying AI-enabled authority and offers practical guidance for ensuring that AI-supported decisions remain accountable, open to challenge, and connected to human judgment and organisational purpose.
Keywords:
- Keyword: artificial intelligence; organisational authority; algorithmic governance; Weber; Heidegger; human-centred governance; leadership; legitimacy.
How to Cite:
Attia, M. & Siddiqui, R., (2026) “The Dissolution of Human-Exclusive Authority: A Weber-Heidegger Framework for AI-enabled Organisational Governance”, Journal of Intelligent and Sustainable Systems (JISS) 2(3).