AI-Driven Governance and Privacy-Preserving Architecture for Healthcare CRM in Multi-Org Cloud Environments: A Human-Centered Big Data Framework for Trustworthy Decision-Making
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I4P128Keywords:
AI Governance, Privacy-Preserving Architecture, Healthcare CRM, Multi-Org Cloud, Big Data, Trustworthy Decision-MakingAbstract
Healthcare and insurance organizations are increasingly expected to modernize digital service operations while protecting privacy, preserving trust, and improving the quality of decisions made across large and complex ecosystems. In multi-organization cloud environments, healthcare customer relationship management platforms support interactions among members, agents, care coordinators, operational teams, and enterprise partners. Artificial intelligence can improve these interactions through guided recommendations, summarization, risk insight, and service orchestration, but it also introduces new concerns about data exposure, accountability, and governance. This paper proposes an AI-driven governance and privacy-preserving architecture for healthcare CRM in multi-org cloud environments. The framework combines human-centered design, big-data intelligence, privacy-preserving controls, and management oversight into a unified operating model for trustworthy decision-making. The paper argues that in healthcare service systems, AI cannot be treated as an isolated automation layer. It must be shaped by privacy boundaries, reviewable controls, explainability, and organizational discipline. The contribution of this study lies in presenting a practical architecture that links advanced computational capabilities with management-level trust, operational resilience, and more humane digital experiences.
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