Shahriar Akter, University of Wollongong

Carolyn Strong, Cardiff University

Marketing is experiencing rapid transformation through AI adoption, yet over 80% of AI initiatives fail to deliver expected financial returns. Despite most CMOs experimenting with AI, fewer than 10% have successfully scaled it across marketing workflows. The gap between AI potential and actual value creation highlights the need for marketing processes centered on humans orchestrating AI, channels, and personalization as a continuous growth engine.

This special issue seeks high-quality research examining how human-centered AI can enhance strategic decision-making in marketing. It welcomes papers addressing responsible AI principles such as beneficence, autonomy, security, justice, and explicability, alongside practical challenges in marketing-specific AI governance, security risks in autonomous agents, algorithmic bias mitigation, and the reskilling of marketing teams for effective human-AI collaboration.

Appel publié par Journal of Strategic Marketing. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Continuous insights: Using multiple data sources for segmentation, campaign execution, and analytics with AI collaboration to predict consumer behaviours
• Security in Agentic creativity: Addressing data breaches, cyberattacks, and security risks in agentic AI systems, including automatic campaign scaling and optimization
• Trust and algorithmic biases: Implementing auditing protocols to identify and correct distortions in data and models
• AI governance and ethical principles: Establishing AI governance frameworks and marketing-specific ethical guidelines for socially beneficial AI adoption
• Human-centred marketing skills: Reskilling and upskilling marketing talent in data analytics, hyper-personalisation, chatbots, and virtual assistants for strategic decision-making
• AI failures: Understanding why AI projects fail due to data quality, customer needs identification, expectations management, and cultural readiness in human-AI collaboration

Timeline

• October 30, 2026: Abstract deadline
• March 31, 2027: Manuscript deadline

Muhammad Imran Rasheed, University of Surrey

Barbara Rita Barricelli, Università degli Studi di Brescia

Waseem Ul Hameed, Universiti Utara Malaysia

This special issue examines how artificial intelligence systems are transforming workplace interactions, employee behavior, and organizational dynamics. While prior research has focused on AI adoption and performance outcomes, this collection addresses the human-centered dimensions of AI at work, including how employees develop trust in intelligent systems, experience AI-mediated processes, adapt their behaviors, and navigate issues such as technostress, autonomy, and cognitive load.

The special issue prioritizes behavioral, cognitive, and psychological perspectives on human-AI interaction in organizational settings. It seeks contributions that explore employee experiences with intelligent technologies, design of user-centered AI systems, transparency mechanisms, and the creation of psychologically sustainable digital work environments. The collection welcomes empirical, theoretical, and design-oriented research across quantitative, qualitative, and mixed-method approaches.

Appel publié par Behaviour & Information Technology. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Employee interaction with AI-enabled systems
• Human reliance, overreliance, and resistance toward AI
• Behavioral adaptation to intelligent technologies
• Human-AI collaboration and hybrid decision-making
• Trust formation in intelligent systems
• Algorithmic transparency and explainable AI
• Employee perceptions of AI fairness and accountability
• Behavioral responses to opaque decision systems
• Technostress, digital exhaustion, and AI fatigue
• Cognitive overload and information processing under AI systems
• AI dependency and employee wellbeing
• Digital distraction and attention fragmentation
• AI-supported autonomy and employee empowerment
• Algorithmic management and behavioral control
• Digital surveillance and monitoring technologies
• Behavioral consequences of automated performance systems
• Ethical design of workplace AI systems
• Human-centered intelligent systems
• Responsible AI implementation in organizations
• Designing psychologically sustainable digital work environments
• AI-enabled learning systems and digital upskilling
• Employee agility and adaptability in AI-enabled workplaces
• Behavioral implications of reskilling and task transformation
• Human learning behavior in technology-mediated contexts
• AI-supported teamwork and collaboration
• Virtual collaboration and intelligent communication systems
• Social interaction patterns in AI-mediated environments
• Team trust and coordination under intelligent systems
• AI in healthcare, hospitality, education, finance, and public services
• Gig work, platform labor, and digital employment systems
• Cross-cultural and cross-national comparisons
• Remote and hybrid work environments
• User experience (UX) of workplace AI systems
• Human-centered design of intelligent workplace technologies
• Conversational AI and intelligent assistants at work
• Adaptive and personalized workplace interfaces
• AI usability and user acceptance in organizational settings
• Interaction design for human-AI collaboration
• Human oversight and human-in-the-loop systems
• Trust calibration in intelligent systems
• Employee engagement with AI-enabled technologies
• Interface design for responsible and ethical AI use
• User perceptions of agency, control, and autonomy in AI-mediated work environments

Timeline

• July 31, 2027: Manuscript deadline