Secure Multi-Tenant AI Architecture Enhances Enterprise AI Adoption Through Tenant Trust Using PLS-SEM in India’s Salesforce Cloud Industry
Keywords:
Secure Multi-Tenant AI Architecture, Enterprise AI Adoption, Tenant Trust, PLS-SEM, Salesforce Cloud Industry, India, AI Security GovernanceAbstract
The emerging difficulty facing organizations is to acquire multi-tenant AI deployment, without losing the confidence in Salesforce cloud platforms. The idea that a secure multi-tenant architecture-oriented AI will enhance the acceptance of enterprise AI in the cloud-based Salesforce business setting in India was investigated in this paper, as it builds trust amongst tenants. The research was anchored on Trust Theory that classified the elements of perceived security assurance and its way of increasing the acceptance of the organizational technology and platform confidence. PLS-SEM was used to test the proposed relationships and 412 Indian-based IT managers, Cloud Administrators, Sales Force Professionals obtained the data, with the help of structured questionnaires. The findings have indicated that secure multi-tenant AI architecture positively affects the trust of tenants and was instrumental in influencing the adoption of AI throughout an enterprise, Salesforce-centered institutions. Also, the indirect influence of secure multi-tenant AI architecture to the adoption of enterprise AI based on tenant trust was high in its turn since all of the structural relationships were found statistically significant at p < 0.01. The study provides current knowledge which fills in the gap between AI security architecture and enterprise uptake through trust, thereby contributing to socio-technical cloud governance studies as well as setting a strategic path of deploying AI in Salesforce without issues over security.
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