AI-Augmented Agentforce Architectures for Predictive Healthcare Claims Adjudication in Salesforce Data Cloud

Author(s)	Mr. Susil Sahu
Country	United States
Abstract	Healthcare payer organizations are under increasing pressure to improve claims turnaround time, reduce administrative burden, and maintain strong compliance controls. This paper presents a practitioner-oriented architecture for predictive healthcare claims adjudication using Salesforce Data Cloud and Agentforce in a governed, human-in-the-loop operating model. The proposed approach unifies claims, member, provider, and service data to improve contextual visibility, identify likely exception-prone claims earlier, and support adjudicators with workflow-aware recommendations. Rather than replacing adjudication authority, the model uses AI to strengthen triage, prioritization, and case understanding while preserving auditability and human review. The paper outlines the architectural components, workflow design, and governance measures needed to operationalize this model in a healthcare payer environment.
Keywords	Salesforce Data Cloud, Agentforce, Healthcare Claims Adjudication, Human-in-the-Loop AI, Enterprise Architecture, Healthcare Payer Modernization
Field	Computer
Published In	Volume 17, Issue 2, April-June 2026
Published On	2026-05-13
DOI	https://doi.org/10.71097/IJSAT.v17.i2.11028

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International Journal on Science and Technology