Leading hybrid intelligence systems: a general systems theory approach to organizational leadership in hybrid intelligence knowledge ecosystems

Martin Sposato, Zayed University

Document Type

Article

Source of Publication

Vine Journal Of Information And Knowledge Management Systems

Publication Date

2-5-2026

Abstract

Purpose - This study aims to develop a meta-leadership framework based on the general systems theory to guide leaders in hybrid intelligence systems where human and artificial agents cooperate. Design/methodology/approach - Using Torraco's (2016) conceptual synthesis framework, this integrative review synthesizes leadership, systems theory and artificial intelligence (AI) governance literature to construct a novel meta-leadership model addressing AI-human cooperation challenges. Findings - The framework comprises five functions (system architecture, boundary regulation, feedback stewardship, adaptation facilitation, ethics governance) operating through three dynamics (alignment, viability, emergence). Emerging empirical studies support the framework's underlying assumptions and suggest potential improvements in organizational performance when structured meta-leadership approaches are applied. Originality/value - This research extends leadership theory beyond anthropocentric models, offering practical guidance for governing distributed agency across human and AI components in knowledge ecosystems.

ISSN

2059-5891

Publisher

Emerald

Disciplines

Business

Keywords

Hybrid intelligence systems, Meta-leadership, Systems thinking, AI governance, Knowledge ecosystems

Indexed in Scopus

no

Open Access

no

Link to Full Text

Share

COinS