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AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues

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  • Manis, K.T.
  • Madhavaram, Sreedhar

Abstract

All marketing capabilities can be enabled by technology. One such technology – artificial intelligence (AI) – holds significant potential for enabling marketing capabilities. While technology-enablement and AI-enablement are frequently discussed in the literature, how technology enables is poorly understood. Therefore, on the foundations of resource-advantage theory’s notion of basic and higher-order capabilities, we clarify enablement in general and AI-enablement in particular for marketing capabilities. Specifically, we (i) integrate literature from the marketing and information systems disciplines to develop conceptualizations of AI, AI-enablement, and AI-enabled marketing capabilities, (ii) integrate literature from marketing, engineering, and computer science to develop a hierarchy of automation framework and conceptualize and delineate how automation undergirds AI’s operations, (iii) develop an integrative framework of AI-enabled marketing capabilities using AI operations, the hierarchy of automation, and the hierarchy of capabilities, and (iv) identify and apply AI’s operations to 30 exemplar marketing and marketing-related capabilities to develop propositions based on commonalities across the exemplar capabilities. In turn, we show how technology in general, and AI in particular, can help firms progress up the hierarchy of capabilities. We conclude with a discussion of the contributions of this research, implications for theory and practice, and future research avenues with exemplar research questions.

Suggested Citation

  • Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:jbrese:v:157:y:2023:i:c:s014829632200950x
    DOI: 10.1016/j.jbusres.2022.113485
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