Towards A Unified Organizational Framework

As technology continues to evolve, organizations face growing and complex challenges and opportunities that affect their ability to govern, manage and harness data as a key source of competitive advantage. Equally, data are considered a powerful and unique source of success for organizations, which in turn, can impact their decision-making capabilities and play a critical role in their success. Hence, this article aims to provide a detailed identification, analysis and discussion over the current data governance context and its existing frameworks, highlighting their commonalities, differences and gaps, including ones related to data governance relationship with Generative Artificial Intelligence (GenAI). This article conducts an extensive methodological and in-depth analysis over a set of sixteen data governance frameworks based on different key data governance attributes, denoting that although there are numerous frameworks, they hold weaknesses, limitations and challenges which prevent them from being capable of incorporating and governing the use and management of AI, particularly the demands originating from GenAI. Our findings provide and propose a new and enhanced data governance framework which integrates the best features and ideas from the existing ones and initiatives derived from the advancements and particularities of AI and GenAI models, systems, and overall usage.

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Publication Details

Journal
Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Published
2026-02-01
Primary Topic
Data Quality and Management
Type
article
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article

Towards A Unified Organizational Framework

João Barroso, Vítor Santos, Mijail Naranjo-Zolotov, Henrique S. Mamede et al.
Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Data Quality and Management
article

Towards A Unified Organizational Framework

João Barroso, Vítor Santos, Mijail Naranjo-Zolotov, Henrique S. Mamede, Bruno Bernardo
article en

Abstract

As technology continues to evolve, organizations face growing and complex challenges and opportunities that affect their ability to govern, manage and harness data as a key source of competitive advantage. Equally, data are considered a powerful and unique source of success for organizations, which in turn, can impact their decision-making capabilities and play a critical role in their success. Hence, this article aims to provide a detailed identification, analysis and discussion over the current data governance context and its existing frameworks, highlighting their commonalities, differences and gaps, including ones related to data governance relationship with Generative Artificial Intelligence (GenAI). This article conducts an extensive methodological and in-depth analysis over a set of sixteen data governance frameworks based on different key data governance attributes, denoting that although there are numerous frameworks, they hold weaknesses, limitations and challenges which prevent them from being capable of incorporating and governing the use and management of AI, particularly the demands originating from GenAI. Our findings provide and propose a new and enhanced data governance framework which integrates the best features and ideas from the existing ones and initiatives derived from the advancements and particularities of AI and GenAI models, systems, and overall usage.

Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)
Peace, Justice and strong institutions
Openalex Percentile: Top 64%
Data Quality and Management
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