Driving value in digital marketing: Navigating from applied machine learning to applied artificial intelligence

Vidya Subramanian
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Vidya Subramanian: Data Science, Google, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2025, vol. 11, issue 2, 109-122

Abstract: Today’s digital marketing analysts must navigate evolving regulations, stringent privacy policies, an assortment of tools, a fragmented technical landscape and the rapidly evolving fields of machine learning (ML) and artificial intelligence (AI). This paper addresses these challenges by proposing a comprehensive framework that splits the digital marketer’s role into three areas: marketing strategy, marketing operations and marketing technology. Within this context, the paper reviews how digital marketing analysts currently leverage ML and analytics. It then explores recent advancements in AI that are hoped will address the shortcomings associated with current ML solutions, before turning its attention to the shortcomings associated with AI. The paper underscores how digital marketing analysts need to weave AI strategically into all aspects of their role if they are to remain competitive and relevant in the Web3 era. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

Keywords: artificial intelligence; machine learning; digital marketing; marketing strategy; marketing operations; marketing technology; personalisation; data privacy; AI ethics; algorithmic bias; marketing ROI (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2025
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