AI Integration for Bridging Advanced Analytics and Business Value in a Regulated World

Abstract: The integration of Artificial Intelligence (AI) and advanced analytics into enterprise strategypromises substantial business value, from improved decision-making to new product innovation.However, realizing this potential is challenging, especially in highly regulated industries wherecompliance, data governance, and ethical constraints are paramount. This paper examines howorganizations can effectively bridge advanced analytics and tangible business value in a worldincreasingly defined by strict regulations. We present a comprehensive review of literature on AIadoption, value creation, and governance, identifying key enablers and barriers to successful AIintegration. A qualitative methodology is employed, synthesizing insights from academicresearch and industry case examples to outline best practices for aligning AI initiatives withbusiness objectives while upholding regulatory compliance. The results and discussion highlightcritical success factors, including strategic alignment of AI use-cases, robust data management,cross-functional governance frameworks, and a culture of responsible innovation. We find thatbalancing agility and compliance is essential: companies must innovate with AI under carefuloversight to avoid legal pitfalls and maintain stakeholder trust. This study contributes anintegrated perspective on deploying AI for business gain in regulated environments and proposesa roadmap to guide organizations. Conclusions emphasize the need for ongoing adaptation, asevolving regulations (such as the EU AI Act) and emerging technologies (like generative AI) willshape future integration efforts. Future work should explore longitudinal case studies to quantifyvalue realization and refine governance models for the next generation of AI solutions.

Keywords: Artificial Intelligence, Advanced Analytics, Business Value, Regulatory Compliance, AI Governance, Enterprise Integration, Responsible AI, Regulated Industries

DOI: 10.54941/ahfe1006924

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