As artificial intelligence (AI) becomes increasingly embedded in organizational life, it is reshaping how leadership is enacted and recognized. From AI-supported hiring and compensation systems to digitally mediated interaction and evaluation, AI structures the signals through which leaders gain recognition, legitimacy, and influence. At the same time, decades of research show that leadership recognition is shaped by status characteristics such as gender and ethnicity, often disadvantaging members of lower-status groups. This symposium addresses a central question for contemporary organizations: How do technological systems and social signals jointly shape who is recognized, trusted, and followed as a leader? Moving beyond views of leadership as a fixed role, the symposium conceptualizes leadership as a multilevel, socially constructed process that emerges through institutional practices, algorithmic systems, interactional dynamics, and micro-level behavioral cues. Across five papers, the symposium traces leadership recognition from macro-level organizational signaling to moment-to-moment interaction. The contributions examine how leadership expectations are communicated through AI-related job advertisements, how algorithmic management reshapes perceived leader power, how inclusion and status jointly shape emergent leadership in diverse teams, how social comparison biases leadership evaluations, and how nonverbal cues such as gaze recruit engagement and recognition in real-time group interaction. Methodologically, the symposium showcases a diverse set of approaches, including large-scale text analysis, experiments, field and laboratory studies, multimodal behavioral data, and physiological measures. Together, these studies advance theories of leadership emergence and evaluation by revealing how status, power, and AI intersect to shape leadership recognition, while offering insights into how organizational and technological systems can foster more equitable patterns of influence in modern workplaces.
Who Gets Seen as a Leader? Signals, Status, and AI in Modern Organizations
Aizhan Tursunbayeva;Luigi Moschera;
2026-01-01
Abstract
As artificial intelligence (AI) becomes increasingly embedded in organizational life, it is reshaping how leadership is enacted and recognized. From AI-supported hiring and compensation systems to digitally mediated interaction and evaluation, AI structures the signals through which leaders gain recognition, legitimacy, and influence. At the same time, decades of research show that leadership recognition is shaped by status characteristics such as gender and ethnicity, often disadvantaging members of lower-status groups. This symposium addresses a central question for contemporary organizations: How do technological systems and social signals jointly shape who is recognized, trusted, and followed as a leader? Moving beyond views of leadership as a fixed role, the symposium conceptualizes leadership as a multilevel, socially constructed process that emerges through institutional practices, algorithmic systems, interactional dynamics, and micro-level behavioral cues. Across five papers, the symposium traces leadership recognition from macro-level organizational signaling to moment-to-moment interaction. The contributions examine how leadership expectations are communicated through AI-related job advertisements, how algorithmic management reshapes perceived leader power, how inclusion and status jointly shape emergent leadership in diverse teams, how social comparison biases leadership evaluations, and how nonverbal cues such as gaze recruit engagement and recognition in real-time group interaction. Methodologically, the symposium showcases a diverse set of approaches, including large-scale text analysis, experiments, field and laboratory studies, multimodal behavioral data, and physiological measures. Together, these studies advance theories of leadership emergence and evaluation by revealing how status, power, and AI intersect to shape leadership recognition, while offering insights into how organizational and technological systems can foster more equitable patterns of influence in modern workplaces.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
