Assessment of the strategic integration of artificial intelligence in enterprise decision-making frameworks

This review examines the strategic integration of artificial intelligence within enterprise decision-making frameworks. The research synthesizes findings from recent empirical studies, industry reports, and organizational case studies to identify implementation patterns and success factors. Analysis reveals that effective AI integration requires alignment across technological infrastructure, organizational structure, and governance mechanisms. Common implementation barriers include inadequate data quality, skill deficits, cultural resistance, and governance challenges. Organizations achieving optimal outcomes typically develop comprehensive AI strategies, establish robust data management practices, deploy cross-functional implementation teams, and implement multi-level governance frameworks. The review identifies distinct integration approaches across operational, tactical, and strategic decision contexts, each requiring tailored implementation methodologies. Findings indicate that while technical sophistication remains important, organizational readiness factors more strongly predict implementation success. This review contributes to both theoretical understanding of AI-augmented decision making and provides practical guidance for practitioners navigating the organizational complexities of AI integration. The research concludes by identifying emerging trends and future research directions in this rapidly evolving domain.