How Organizations Design Portfolio Management to Govern AI: A Taxonomy Approach

Advances in artificial intelligence (AI) create game-changing opportunities and new risks for organizations. Increasing competition and emerging regulation pressure them to govern AI for strategic use. Portfolio management has been identified as a key mechanism. However, AI is different from technologies for which portfolio management has proven effective. How organizations design portfolio management to govern AI is not well understood. Therefore, we conceptualized key design decisions in AI portfolio management (AIPM) by developing a multi-layer taxonomy. We developed our taxonomy based on five exploratory case studies. We evaluated it through expert interviews and a practitioner intervention. Our taxonomy shows that many IT portfolio management characteristics also apply to AIPM. However, AI introduces complexities that require novel design decisions. Our taxonomy captures design knowledge that enables future causal / predictive theorizing on AIPM. Practitioners can use our taxonomy as a tool to establish and improve AIPM practices.

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Publication Details

Journal
Journal of the Association for Information Systems
Published
2025-06-18
Primary Topic
Musicology and Musical Analysis
Type
article
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article

How Organizations Design Portfolio Management to Govern AI: A Taxonomy Approach

Journal of the Association for Information Systems
Musicology and Musical Analysis
article

How Organizations Design Portfolio Management to Govern AI: A Taxonomy Approach

article en

Abstract

Advances in artificial intelligence (AI) create game-changing opportunities and new risks for organizations. Increasing competition and emerging regulation pressure them to govern AI for strategic use. Portfolio management has been identified as a key mechanism. However, AI is different from technologies for which portfolio management has proven effective. How organizations design portfolio management to govern AI is not well understood. Therefore, we conceptualized key design decisions in AI portfolio management (AIPM) by developing a multi-layer taxonomy. We developed our taxonomy based on five exploratory case studies. We evaluated it through expert interviews and a practitioner intervention. Our taxonomy shows that many IT portfolio management characteristics also apply to AIPM. However, AI introduces complexities that require novel design decisions. Our taxonomy captures design knowledge that enables future causal / predictive theorizing on AIPM. Practitioners can use our taxonomy as a tool to establish and improve AIPM practices.

Journal of the Association for Information Systems
Liechtenstein Institute (LI), University of Liechtenstein (LI), University of St.Gallen (CH), University of Applied Sciences St. Gallen (CH)
Openalex Percentile: Top 42%
Musicology and Musical Analysis
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