Toward a Conceptual Framework for Human-AI Collaboration in Managerial Tasks
Keywords:
Human-AI collaboration, managerial decision-making, artificial intelligence integration, qualitative research, organizational readiness, trust in AI systemsAbstract
This study aimed to identify and conceptualize the key components influencing effective human-AI collaboration in managerial tasks through in-depth exploration of managerial experiences and perceptions. Using a qualitative research design, the study employed semi-structured interviews with 22 middle and senior managers from various industries in Morocco who had experience interacting with AI-enabled systems in their professional roles. Participants were selected through purposive sampling, and data collection continued until theoretical saturation was achieved. Each interview lasted between 45 and 70 minutes and was transcribed verbatim. Thematic analysis was conducted using Braun and Clarke’s method, facilitated by NVivo software to organize codes and extract themes. Data analysis focused on identifying recurrent patterns, participant interpretations, and context-specific insights into the human-AI collaborative process. Five main themes emerged from the analysis: managerial perception of AI, human-AI role dynamics, organizational readiness, conditions for effective collaboration, and future strategic vision. Participants recognized AI as a valuable tool that enhances efficiency and supports decision-making, yet emphasized the need for human oversight and contextual judgment. Trust in AI was conditional and closely linked to system transparency and explainability. Role differentiation was clear, with AI seen as capable in data-driven tasks but limited in ethical and emotional domains. Organizational readiness—including leadership support, infrastructure, and culture—significantly influenced the success of collaboration. Participants also stressed the need for task-appropriate AI deployment, feedback loops, and system customization. Effective human-AI collaboration in managerial tasks depends on a balance of technological capability and human judgment, shaped by trust, ethical clarity, and organizational support. The study proposes a conceptual framework to guide future implementations of AI in management contexts.
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