Identify "blind spots" in how Artificial Intelligence (AI) is currently being used within your organization.
As employees across departments increasingly rely on generative AI tools and embedded software features without formal IT oversight, organizations face critical blind spots regarding proprietary data and intellectual property. This targeted assessment establishes a clear baseline of your AI adoption to ensure your business innovates securely without compromising control.
Key Benefit:
Identify invisible “blind spots” and risks—specifically unmanaged “Shadow AI” usage and SaaS AI footprints—enabling organizations to protect proprietary data, ensure regulatory compliance, and secure their business operations against unvetted AI adoption.
What We Provide:
- Comprehensive Shadow AI Discovery: A structured inventory to map out unmanaged generative AI tool access, departmental power users, and tracking mechanisms across the organization.
- Data Privacy and Leakage Evaluation: An analysis of organizational policies and practices regarding sensitive data (such as customer PII, financial reports, and source code) uploaded to AI models.
- SaaS and Compliance Audit: A review of third-party vendor AI settings, customer-facing chatbot stop-loss protections, and others.
Risks Addressed:
- AI Governance Gaps
- Shadow AI Adoption
- Data Privacy & Leakage
- SaaS & Third-Party Exposures
Applicable Cybersecurity Framework Requirements (non-exhaustive list):
- ISO 27001:2002 6.1.2 – Information security risk assessment
- ISO 27001:2022 6.1.3 – Information security risk treatment
- CIS 1: Inventory and Control of Enterprise Assets
- CIS 2: Inventory and Control of Software Assets
- CIS 15: Service Provider Management