Journal of Strategic Marketing

Human Centred AI in Strategic Decision Making

Marketing is undergoing a seismic transformation due to the dramatic advances and adoption of artificial intelligence (AI), cloud-based data ecosystems, and digital channels (Salesforce, 2026). However, the evidence from cross-industry analysis shows that more than 80% of AI initiatives fail to achieve expected financial return (Cooper, 2026). While 90 percent of CMOs are experimenting with AI use cases, less than 10 percent have either scaled it or captured value across marketing workflows (Singla et al., 2025). The extant marketing literature highlights that the opportunity lies not in AI-powered marketing operations but in restructuring marketing processes as a continuous growth engine centring humans/marketers to orchestrate AI, agents, channels, new product development and personalisation (Davenport et al., 2020; Kumar et al., 2023; Huang & Rust, 2021). Thus, the pressure to deliver measurable impact reshapes how marketing deploys AI to engage customers, manage expectations, make decisions, ensure equity, and assure quality of life (Hermann 2022). It is also critical to embrace the principles of responsible AI (e.g., beneficence, autonomy, security, sustainability, justice, and explicability) to address the emerging challenges of the AI revolution in marketing and ensure welfare for all (Floridi 2019; Hermann & Puntoni 2025).  

This special issue is focused on research papers that make new contributions to Human Centred AI in Strategic Decision Making. This special issue welcomes high-quality/high-impact full research papers, state-of-the-art developments building upon marketing or interdisciplinary theories.

The main topics of interest include, but are not limited to:

·       Continuous insights: The average marketing organisation uses at least seven data sources in designing segmentation, campaign execution, and analytics, and marketers can play a central role in this process to predict consumer behaviours in collaboration with AI.

·       Security in Agentic creativity: Agentic AI leverages analytical AI and Gen AI together to plan, decide, and execute tasks across workflows and systems. As agents become more intelligent, there is recent evidence of data breaches, cyberattacks, and security risks due to the alignment problem (Bennhold 2026). Challenges persist with automatic scaling of new campaigns, automatic campaign optimisation, and cross-platform media budget allocation (Stein et al., 2026).

·         Trust and algorithmic biases: There is a need for research to implement rigorous auditing protocols to identify and proactively correct distortions in data and models (Akter et al., 2023).

·       AI governance and ethical principles: There is a wide range of ethical guidelines to establish AI governance for the adoption of socially beneficial AI. Unfortunately, there are no specific guidelines for marketing-specific products.

·       Human-centred marketing skills: There is a massive need for reskilling and upskilling marketing talent, focusing on advanced data analytics, hyper-personalisation, Chatbots, and virtual assistants, in strategic decision-making.

·       AI failures: Building an AI-ready organisation is foremost a people challenge, not just a technology one. AI projects keep failing due to poor data quality, not identifying customer needs, unrealistic expectations and lack of cultural readiness. AI and human collaboration are crucial to develop strategic marketing decisions.

References

Akter, S., Sultana, S., Mariani, M., Wamba, S.F., Spanaki, K. and Dwivedi, Y.K., 2023. Advancing algorithmic bias management capabilities in AI-driven marketing analytics research. Industrial Marketing Management, 114, pp.243-261.

Bennhold, K. (2026, August 4). When AI goes rogue. The New York Times.

Cooper, R.G.  (2026). The AI Perfect Storm: When Five Powerful Forces Converge, Product Development Institute. http://www.bobcooper.ca/articles/artificial-intelligence-in-npd

Davenport, T., Guha, A., Grewal, D. and Bressgott, T., 2020. How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), pp.24-42.

Hermann, E., 2022. Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of business ethics, 179(1), pp.43-61.

Hermann, E. and Puntoni, S., 2025. Generative AI in marketing and principles for ethical design and deployment. Journal of Public Policy & Marketing, 44(3), pp.332-349.

Huang, M.H. and Rust, R.T., 2021. A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), pp.30-50.

Salesforce (2026). Tenth edition state of Marketing. URL: https://www.salesforce.com/au/marketing/resources/state-of-marketing-report/conf/

Singla, A., Sukharevsky, A., Hall, B., Yee, L., & Chui, M. (2025). The state of AI in 2025: Agents, Innovation, and transformation. McKinsey & Company.

Stein, E., Wilkie, J., Boudet, J., Robinson, K., & Bhagia, L. (2026, June 22). From campaigns to continuous growth: AI capabilities shaping marketing. McKinsey & Company.