AI & Data Security & Compliance

Understand your AI risk before it becomes a breach.

AI is accelerating faster than governance, security, and compliance can keep up. AI & Data Security & Compliance services help you identify where AI is being used, what data it touches, and how to safely scale adoption without introducing unmanaged risk.

AI risk and exposure visibility

Data-first security controls

Governance aligned to frameworks

Continuous AI risk oversight

What We Deliver

Blue Mantis helps organizations assess AI risk, establish governance, secure data, and maintain ongoing oversight as AI adoption grows.





AI Risk and Readiness Assessment

Blue Mantis evaluates how AI is being used across your organization and identifies risk across identity, data, access, and model behavior. We provide a clear starting point for safe AI adoption.

What we cover:


AI use case discovery process: Identifies Copilot, private GPTs, and embedded AI usage.

Risk exposure analysis across domains: Evaluates identity, data, and access vulnerabilities.

Governance and policy readiness review: Assesses existing controls and oversight gaps.

Prioritized remediation roadmap: Defines next steps to reduce risk and improve readiness.

AI Governance Framework Development

Blue Mantis helps organizations establish an AI Governance Office — the structure, charter, and operating model that ensures AI adoption happens within defined, enforceable boundaries instead of unmanaged risk.

What we cover:


AI Governance Office establishment: Builds the team, charter, and decision rights needed to oversee AI adoption.

AI acceptable use policy: Defines clear rules for how AI tools can and cannot be used across the organization.

NIST AI RMF alignment: Aligns AI risk management to the NIST AI Risk Management Framework.

Legal and cross-functional engagement: Brings legal and business stakeholders into a cadence-driven governance operating model.

Data Security for AI and Copilot

Blue Mantis focuses on protecting the data that powers AI systems, extending data loss prevention to prompts, agent outputs, and browser-based LLM usage — not just traditional file and email channels.

What we cover:


Sensitive data discovery and classification: Identifies PII, PHI, financial data, and intellectual property.

DLP for AI channels: Extends Microsoft Purview data loss prevention to AI prompts, agent outputs, and browser-based LLM usage.

Access control and data governance enforcement: Applies role-based access and least privilege principles.

Guardrails for AI data usage: Prevents unintended sharing or misuse of critical data through AI tools.

AI Compliance and Regulatory Alignment

Blue Mantis ensures AI usage aligns with regulatory requirements and emerging standards. We reduce compliance risk while enabling responsible AI adoption.

What we cover:


Regulatory mapping for AI systems: Aligns usage to frameworks such as NIST AI RMF, SOC 2, HIPAA, and EU AI Act.

Compliance gap identification: Highlights areas where AI usage introduces risk or non-alignment.

Audit readiness and documentation: Prepares supporting evidence for regulatory review.

Alignment with existing GRC programs: Integrates AI compliance into broader governance operations.

AI Monitoring and Risk Oversight

Blue Mantis provides continuous oversight of AI systems, ensuring risk is detected early and controls remain effective as AI usage grows.

What we cover:


AI usage and behavior monitoring: Tracks access patterns and anomalies across AI workflows.

Data exposure tracking and analysis: Identifies potential misuse or leakage scenarios.

Model and output risk monitoring: Detects drift and unexpected behavior in AI systems.

Continuous risk reporting and visibility: Provides executive oversight as AI environments scale.

What happens at each step

How AI & Data Security and Governance Works

Step 1

Discover AI Usage Across the Organization

We uncover how AI is being used across your organization, including Copilot, private GPTs, and embedded AI tools. This establishes a clear baseline of where risk exists.

Step 2

Data and Governance Gaps

AI systems are evaluated across identity, data, access, and model behavior. This identifies gaps in data protection, governance structure, and oversight that increase exposure.

Step 3

Implement Design Controls Frameworks

Governance frameworks, data security controls, and access policies are designed and implemented to align AI usage with business risk and compliance requirements. This ensures AI adoption is structured, not ad hoc.

Step 4

Monitor, Report, and Continuously Improve

Ongoing monitoring tracks AI behavior, data exposure, and compliance alignment. This keeps controls effective as AI usage grows and requirements evolve.

Frequently Asked Questions

Why is AI risk different from traditional security risk?

AI introduces new attack surfaces tied to data access, model behavior, and automation. Risks include unintended data exposure, misuse, and decision-making impacts that traditional controls are not designed to address.

Where do most organizations have blind spots with AI?

Most gaps are in visibility and governance. Organizations often do not know where AI is being used, what data is being accessed, or how decisions are being made within AI systems.

How does AI governance differ from traditional governance?

AI governance extends beyond policy into model behavior, data interaction, and continuous monitoring. It requires oversight across technical teams, legal, and business stakeholders.

Why focus on data security for AI?

AI systems rely on data to function, making data the primary risk vector. Without proper controls, sensitive information can be exposed or misused through AI interactions.

How often should AI risk be reassessed?

AI risk should be continuously monitored and periodically reassessed as new use cases, models, and integrations are introduced. AI environments evolve quickly, and controls must keep pace.

Understand where AI creates risk in your organization.

We will identify where AI is being used, what data it touches, and where governance and controls may be missing. You leave with a clear roadmap to reduce risk and move forward with confidence.

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