Strategic Convergence of Business Intelligence and Artificial Intelligence: Navigating Ethical Value Creation in Cloud-Based Ecosystems

Abstract

Background: The digital economy is witnessing a paradigm shift where traditional Business Intelligence (BI) is merging with Artificial Intelligence (AI) within cloud-computing environments. While this convergence offers unprecedented opportunities for value creation, it presents significant challenges regarding data privacy, cloud cost optimization, and ethical algorithmic governance.

Objective: This study aims to investigate the synergistic relationship between BI, AI, and cloud infrastructure, specifically focusing on how organizations can balance the "Big Data" imperative with "Data Minimalism" to ensure ethical, secure, and efficient decision-making.

Methods: Utilizing a multi-dimensional theoretical framework, this research synthesizes economic theories of information value with contemporary analyses of cloud security, blockchain applications in healthcare, and ethical AI deployment in retail. The study employs a comparative analysis of high-agility technology firms and regulated healthcare entities to identify universal success factors.

Results: Findings indicate that BI success is increasingly dependent on the "decision environment" rather than mere technical capability. Furthermore, the integration of AI-driven real-time threat detection in cloud environments significantly reduces operational risk. Notably, the application of "Data Minimalism" strategies correlates with higher consumer trust and reduced computational overhead, challenging the prevailing volume-centric data dogmas.

Conclusions: The future of BI lies in "Cognitive BI"—systems that not only report but predict and prescribe actions within an ethically bound framework. Organizations must transition from passive data accumulation to active, value-centric data governance, leveraging cloud scalability while adhering to strict privacy standards.