Governing the Autonomous Enterprise with ServiceNow AI
Keywords:
SAI Governance Frameworks, Cloud-Native AI Systems, Security-Centric Automation, ServiceNow AI Integration, Zero-Trust Architecture, AI Risk Management, Compliance-Driven AI Operations, Identity and Access Control, AI Lifecycle Governance, Secure AI Deployment.Abstract
Enterprises are increasingly embracing Artificial Intelligence (AI) to accelerate business outcomes. However, deploying AI technology responsibly requires a controlled environment with appropriate risk management to ensure the long-term viability of these systems. This calls for an AI governance framework aligned with enterprise service delivery, one capable of detecting and remediating trust, safety, security, and compliance risks across the AI lifecycle — including the data used to train, develop, and operate AI models.
To this end, we present a Cloud-Native, Security-Centric, and Compliant AI-Driven Automation Framework for ServiceNow. The framework enables AI services to be developed, operated, and maintained safely, securely, and in a controlled, responsive manner consistent with AI governance principles throughout their lifecycle. It operates within a cloud-native model, with all constituent applications — spanning SaaS, IaaS, and PaaS — developed and deployed under zero-trust principles and least-privilege identity and access management. Together, these elements establish a foundation for continuously strengthening security-centric and compliance controls.
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Data Availability Statement
The datasets used in this study are described in Table 4 (ServiceNow ITSM logs, IAM audit logs, compliance audit trail, and AI model telemetry). The data are available from the corresponding author upon reasonable request.
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