A data science framework for AI-driven innovation within organizations
Document Type
Article
Publication Date
1-1-2025
Publication Title
Issues in Information Systems
Abstract
Artificial Intelligence (AI) continues to redefine how organizations innovate, grow, and enhance productivity. However, successful AI adoption hinges not only on technology but also on the strategic integration of data within organizational ecosystems. This paper presents a structured data science framework to guide AI-driven organizational transformation. To enable sustainable AI innovation, the framework provides a roadmap by synthesizing best practices, case studies, and emerging research across six foundational pillars: data strategy, infrastructure, AI workflows, culture, talent, and feedback. The model emphasizes the need for strategic alignment, ethical governance, and cross-disciplinary collaboration to maximize AI’s impact on enterprise growth and operational efficiency.
Volume Number
26
Issue Number
1
First Page
110
Last Page
125
DOI
10.48009/1_iis_109
Recommended Citation
Wu, Daniel D., "A data science framework for AI-driven innovation within organizations" (2025). Faculty and Staff Works. 928.
https://kb.gcsu.edu/fac-staff/928