Human Centred AI in Strategic Decision Making

Editors

  • Shahriar Akter, University of Wollongong
  • Carolyn Strong, Cardiff University

Description

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.

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