Track 1: Artificial Intelligence in Management and Mass Communications
Track Organizers
Chair: Dr. Hesham Dinana – The American University in Cairo
Email: hdinana@aucegypt.edu
Abstract
Artificial intelligence is reshaping how organizations are managed and how messages reach mass audiences. This track explores the strategic, operational, and societal implications of AI adoption across management and mass communication domains. It brings together researchers and practitioners examining how generative AI, machine learning, and algorithmic systems are transforming organizational decision-making, leadership, human resource practices, marketing, public relations, journalism, and media production. Submissions are invited on AI-driven strategic management, algorithmic management and human–AI collaboration, AI-enabled marketing and consumer analytics, computational methods for communication research, AI in journalism and digital newsrooms, and the governance, ethics, and trust challenges raised by AI-mediated content and decisions. The track welcomes empirical, conceptual, and case-based contributions that advance theory and practice at the intersection of AI, organizational behavior, and mass communication. Particular attention is given to how AI reshapes organizational resilience, audience engagement, misinformation risk, and accountability frameworks. By connecting management scholarship with communication and media research, this track aims to foster interdisciplinary dialogue on responsible, effective, and human-centered AI adoption, offering actionable insights for managers, communicators, policymakers, and scholars navigating the rapidly evolving AI-driven organizational and media landscape.
Call for Papers: Suggested Topics
- • AI-driven strategic decision-making and organizational management
- • Generative AI and large language models in management and marketing practices
- • Algorithmic management and human–AI collaboration
- • Big Data and AI in marketing decisions and consumer analytics
- • AI-driven personalization, automation and real-time consumer insights
- • Computational and machine-learning methods for communication research
- • AI and algorithmic communication on digital/social media platforms
- • AI in journalism, automated news production and digital newsrooms
- • AI, misinformation, and trust in mass communication and journalism
- • Algorithm auditing, transparency and accountability in AI-mediated content
- • AI-enabled public relations, advertising and brand communication
- • Ethical, social and policy implications of AI in management and media
- • AI in crisis communication, risk management and corporate reputation
- • Human–AI interaction, trust and acceptance in organizational and media contexts