Human-AI Leadership for Sustainable Strategic Decision-Making in Iranian Public Organizations

This research develops a comprehensive framework for embedding artificial intelligence (AI) into sustainable strategic decision-making processes within Iranian governmental organizations. Employing a sequential exploratory mixed-methods design, the study first conducted thematic analysis of ۲۲ semi-structured interviews with senior public managers and academics to identify key constructs. These insights informed a subsequent quantitative phase involving a survey of ۲۴۸ validated responses from public-sector executives, analyzed through partial least squares structural equation modeling (PLS-SEM). The central construct-symbiotic human-AI leadership-emerges as the pivotal mechanism enabling sustainable governance outcomes. Antecedent barriers include technical skill deficiencies, organizational resistance, ethical and bias-related concerns, fragmented high-quality data ecosystems, elevated implementation expenditures (including environmental compliance costs), and regulatory ambiguities. Enabling contextual elements encompass supportive digital-green policies, robust data infrastructures, specialized talent reservoirs, dedicated fiscal allocations for sustainable technologies, international technology partnerships, and resilient advanced infrastructures. Moderating conditions-such as executive commitment, adaptive organizational cultures, targeted capacity-building programs, cross-sector academic collaborations, and multi-stakeholder ethical governance protocols-strengthen the pathway to effective integration. Proposed intervention mechanisms involve co-designing localized responsible-AI standards, investing in energy-efficient AI platforms, deploying real-time governance dashboards, fostering public-private-academic consortia, and integrating advanced optimization algorithms that explicitly account for inflationary pressures and carbon-emission constraints. Anticipated results include superior decision precision, heightened citizen trust and satisfaction, substantial operational efficiencies with reduced environmental footprints, enhanced accountability and transparency, accelerated crisis responsiveness, and optimized sustainable resource allocation. By bridging AI capabilities with sustainability imperatives, this framework offers policymakers a practical roadmap for resilient digital transformation in resource-constrained public bureaucracies.

کلیدواژه ها:

Artificial intelligence ، sustainable strategic decision-making ، human-AI symbiosis ، public-sector governance ، mixed-methods ، PLS-SEM