Beyond Automation Part 2: How ServiceNow AI and AWS Transform Enterprise Security

In Part 1 of this series, we discussed how the complexity of aligning cloud infrastructures of different cloud solution providers (CSPs) leads to unscalable solutions that continually require sizable resource investments. In this blog post, we propose two use cases to integrate Amazon Web Services (AWS) with ServiceNow’s powerful Artificial Intelligence (AI)-driven, enterprise platform to scale Governance, Risk, and Compliance (GRC) functions. By implementing these native features, organizations can achieve stronger GRC outcomes while reducing the long-term resource investments needed to support the integration of these environments. 

As with the prior post, we provide lessons learned we recommend readers consider when attempting to implement the respective use cases below. 

1. Reduce evidence collection efforts: Implement “continuous compliance” with Frameworks such as NIST, CIS, and ISO 27001. 

ServiceNow’s Integrated Risk Management (IRM) module can be implemented to automatically map AWS findings to control objectives and compliance frameworks. It uses Natural Language Understanding (NLU) and Optical Character Recognition (OCR) to ingest evidence (e.g., screenshots or logs from AWS services like CloudTrail or GuardDuty). For example, if suspicious activity is flagged in AWS, the finding is then mapped to control objectives in ServiceNow along with linked issues to track gaps. This supports customers that must maintain compliance for workloads hosted on AWS. 

Value Impact

• Reduce audit preparation time by months
• Early issue identification will support faster onboarding to regulated AWS workloads (e.g., FedRAMP, Health Insurance Portability and Accountability Act (HIPAA))
• As gaps are identified, this use case will promote intelligent adoption of AWS-native security services like CloudTrail, Macie, GuardDuty

Challenges

• Mapping Complexity: Translating AWS control findings into ServiceNow control objectives may require custom logic or manual mapping depending on current configurations.
• Data Format Incompatibilities: AWS audit artifacts (JSON, CSV, screenshots) may not be consistently parsable by ServiceNow Document Intelligence or optical character recognition (OCR).
• Framework Drift: If AWS services change or ServiceNow IRM isn’t updated to reflect new framework versions, compliance coverage will degrade.

• Human Bottlenecks: Even with automation, control owners may ignore or delay reviews, breaking the loop of continuous compliance.

   

2. Reduce AWS configuration drift: Provision Secure AWS Environments/Services using ServiceNow Service Catalog

ServiceNow’s Service Catalog, enhanced with Virtual Agent and AI-driven workflows, allows teams to request secure AWS environments pre-configured with compliant architectures. These environments/services are spun up using AWS CloudFormation templates and governed by ServiceNow Service Catalog offering a no-code UI for business teams to request provisioning with enforced governance requirements across user profiles and environmental complexity. For example, when an application developer requests “more data store” via the ServiceNow catalog, the catalog deploys a CloudFormation template for S3 buckets. This ensures the new service meets security compliance requirements without needing the application developer to understand the technical architecture and configurations of AWS resources[JM4] .

Value Impact

• Reduce provisioning time
• Reduce operator toil through consistent scalable deployments.  All new AWS environments/services will inherit organizational guardrails and tagging standards with scalable deployments
• Reduced drift of environments/services as AWS consumption scales resulting in secure and compliant deployments

Challenges

• Template Drift or Misalignment: AWS CloudFormation templates or Control Tower blueprints may become outdated or non-compliant if not regularly audited.
• User Misuse or Bypass: Users may still spin up resources directly in AWS, bypassing the ServiceNow catalog and breaking governance.
• Virtual Agent Gaps: Poor natural language understanding or incomplete dialog trees in Virtual Agent can frustrate users or lead to wrong provisioning.
• Approval Bottlenecks: Predictive routing for approvals may fail due to incorrect training or org changes, slowing down or misrouting requests

Mitigation Considerations to Implementation Challenges

Specific mitigations and dependency considerations for implementation of each use case is customer dependent. However, the following broad mitigations are good ways to strategically consider architecting the proposed use cases. 

• Establish strong CI/CD pipelines for updates to templates, workflows, and AI models.
• Use sandbox environments to test integrations before deployment.
• Regularly audit permissions, mappings, and compliance frameworks in both AWS and ServiceNow.
• Ensure stakeholders are aligned through interlock meetings across infrastructure, security, and GRC teams.

Final Thoughts

Many enterprises are consuming both AWS and ServiceNow but are lacking a clear integration strategy between these two CSPs. This can lead to increased cost in consumption of AWS or ServiceNow, and lead to a potentially unscalable level of customization.

By avoiding a siloed approach, ServiceNow helps your organization manage AWS consumption more intentionally while scaling mandatory GRC activities. Understand both existing features, and desired end state, then map features to end state. Where gaps remain, submit feature requests to AWS and ServiceNow or consider limited customization that is maintainable over time.