Technology and AI
A Framework for AI Governance in Marketing
The application of AI to marketing raises not only practical issues about implementation but also ethical and regulatory challenges. Based on a synthesis of existing literature, this Responsible AI Marketing Framework proposes four key pillars to ensure effective AI governance: Transparency by design; Consent architecture; Algorithmic accountability; and Consumer empowerment.
Beyond the Algorithm: Consumer Trust, Transparency, and the Governance of AI-Driven Marketing in Digital Ecosystems
Reviews and synthesizes 35 high-quality qualitative research sources to develop a framework for AI marketing governance.
MSI MMM Committee Discussion: ROI Misuse, MMM Decision-Making, and AI’s Emerging Role
This session focused on two major themes: 1. A new paper arguing that marketers frequently misuse ROI when making allocation decisions from MMMs and 2. A discussion about how AI is beginning to influence MMM workflows and marketing analytics more broadly.
Implementing Marketing AI: A Taxonomy and Scorecard
This taxonomy of marketing functions can guide implementation of artificial intelligence from machine learning to generative AI. Enablement proceeds from Interpretation (research and analytics) to Direction (strategy and tactics) to Optimization. Engagement involves Creation of personalized products and services that drive customer Connection. AI implementation can proceed in either direction.