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Abstract: As artificial intelligence advances toward increasingly general and autonomous capabilities, the governance discourse has centered on technical alignment, regulation, and capital structures. Yet a critical dimension remains underexplored: how people management practices and leadership approaches within frontier AI organizations fundamentally shape safety cultures, research priorities, and the responsible development of potentially transformative technologies. This article examines how organizational leadership influences superintelligence trajectories through talent strategies, psychological safety frameworks, governance structures, and distributed decision-making models. Drawing on organizational behavior research, case evidence from leading AI labs, and insights from safety-critical industries, we demonstrate that people management is not peripheral to AI governance—it is foundational. Effective leadership creates the conditions for researchers to voice concerns, resist commercial pressures, maintain epistemic humility, and balance capability development with safety imperatives. We outline evidence-based approaches including transparent communication systems, procedural justice in research prioritization, capability-building investments, and long-term resilience frameworks that enable organizations to navigate the profound ethical and operational challenges of developing potentially superintelligent systems. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell....