All four foundational theories of marketing examined in this review - service-dominant logic, customer-based brand equity, commitment-trust theory, and the satisfaction paradigm - assume human agency at the moment of value co-creation, an assumption that is empirically false for an increasing share of transactions. Yet marketing scholarship has examined AI, data privacy regulation, and platform ecosystems largely in isolation, producing no synthesis of how these three forces jointly disrupt the discipline's theoretical architecture. This article presents a systematic integrative review of 154 sources - 104 peer-reviewed articles and 50 industry reports published between 2015 and 2026 - following the methodology of Palmatier et al. (2018). Our analysis reveals three structural shifts: value co-creation now occurs in hybrid human-AI ecosystems rather than exclusively between human actors; brand equity must be maintained simultaneously in consumer cognition and in algorithmic recommendation systems; and relational trust operates asymmetrically when one partner in the exchange is an artificial agent. We propose the Algorithmic Value Creation Framework (AVCF), which reconceptualizes these four foundational theories for algorithmic contexts and introduces the construct of Algorithmic Brand Equity (ABE) - a brand's visibility, favorability, and retrievability within the recommendation architectures and large language models that increasingly mediate consumer access to products. The framework offers marketing scholars a conceptual vocabulary for a discipline whose core assumptions were forged in an era that has ended.
Kovalenko et al. (Sat,) studied this question.