AI-Native Architecture: The Convergence of Autonomy and Trust in Enterprise Platforms

Authors

  • Rajesh Ediga Osmania University

DOI:

https://doi.org/10.47941/ijce.2947

Keywords:

AI-Native Architecture, Autonomous Agents, Governance Frameworks, Enterprise Integration, Progressive Autonomy

Abstract

This article examines the emergence of AI-native architecture as exemplified by Salesforce's dual innovation—Agentforce and Einstein GPT Trust Layer. As artificial intelligence transitions from supplementary features to foundational architectural elements, enterprises face the challenge of balancing autonomous agency with appropriate governance frameworks. Through analysis of Salesforce's approach, explore how seemingly opposing priorities of autonomy and control can be harmonized within an integrated architectural pattern. The article investigates how the Agentforce framework enables sophisticated autonomous operations across enterprise contexts, while the Einstein GPT Trust Layer provides a comprehensive security and compliance infrastructure specifically designed for AI interactions. By examining this architectural integration, we demonstrate how organizations can simultaneously empower AI capabilities while establishing necessary boundaries, creating systems that maximize operational value while minimizing organizational risk. This convergence of autonomy and accountability represents a significant evolution in enterprise architecture that resolves key tensions between technological advancement and organizational governance

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References

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Published

2025-07-15

How to Cite

Ediga, R. E. (2025). AI-Native Architecture: The Convergence of Autonomy and Trust in Enterprise Platforms. International Journal of Computing and Engineering, 7(9), 47–57. https://doi.org/10.47941/ijce.2947

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Section

Articles