Strategic Differentiator / 03
AI Governance &
Risk Management
Navigate AI adoption with confidence. We help organizations deploy AI responsibly through governance frameworks, risk assessments, and ethical policy development aligned with ISO 42001 and NIST AI RMF.
Why This Can't Wait
AI is moving faster
than your risk framework.
Most organizations have deployed AI tools before governance policies existed. ChatGPT in marketing. Copilot in engineering. AI-assisted customer service. Each one a potential data leakage vector, compliance exposure, or regulatory liability and most security frameworks weren't built to assess them.
We're security and privacy practitioners who understand AI at a technical level. Not policy consultants who've read the frameworks. We've worked with AI systems, understand model architectures, and assess real technical risks, not hypotheticals dressed up as governance.
Shadow AI Adoption
Employees are using AI tools your IT and security teams haven't reviewed pasting sensitive data into public models, using unapproved SaaS platforms with AI features, and bypassing procurement processes entirely.
Regulatory Pressure
The EU AI Act is in force. State AI laws are proliferating. Regulators are asking about your AI risk management practices. Customers and enterprise procurement teams are including AI governance questions in their security reviews.
Investor & Board Scrutiny
Boards and investors are asking how AI risk is being governed. ISO 42001 certification is becoming a signal of AI program maturity the same way SOC 2 became a signal of security program maturity.
No Framework for New Risks
Prompt injection, model poisoning, training data leakage, and automated decision-making bias don't appear in your existing security framework. Your risk register doesn't capture them. Your incident response plan doesn't address them.
What Makes This Different
Technical depth.
Not just policy consulting.
01
Security Engineering Behind Every Assessment
We assess AI risk the way we assess any security risk - technically. Prompt injection attack surfaces, model architecture vulnerabilities, training data exposure pathways, supply chain risk in foundation models. Not a checklist. An actual assessment.
02
Privacy Law Intersection Understood
GDPR's right to explanation conflicts with black-box model outputs. CCPA data minimization requirements conflict with training data needs. Biometric data laws apply to facial recognition AI. We understand both sides of that tension because we work in both disciplines.
03
Frameworks That Hold Up to Scrutiny
ISO 42001 and NIST AI RMF alignment isn't decorative. When a regulator, auditor, or enterprise customer asks about your AI governance program, you need documentation that reflects how your AI systems actually operate not a template with your name on it.
AI-Specific Risk Domains
The risks your existing framework doesn't cover.
AI introduces new attack vectors and compliance challenges that traditional security frameworks don't fully address. We help you identify and mitigate these emerging risks.
Data Exposure
Data Leakage
Employees pasting sensitive data into public AI tools. Customer data exposure through poorly scoped model training. Inadvertent disclosure of trade secrets, PII, or confidential business information to third-party model providers.
Model Security
Adversarial Attacks
Prompt injection attacks and jailbreaking attempts. Model theft and adversarial inputs designed to manipulate outputs. Supply chain risk in foundation models and third-party AI integrations your organization depends on.
Regulatory
Compliance Gaps
GDPR right to explanation requirements conflicting with black-box model outputs. Data minimization obligations conflicting with training data needs. Biometric data laws applying to AI systems your legal team hasn't reviewed.
Fairness
Bias & Discrimination
Discriminatory outputs in hiring, lending, healthcare, or customer service AI. Amplification of training data bias at scale. Lack of explainability for adverse automated decisions that affect individuals' rights and opportunities.
Intellectual Property
IP & Copyright Risk
Copyright infringement in generative AI outputs. Ownership disputes over AI-created content. Inadvertent recreation of proprietary algorithms. Contractual obligations around AI-generated work product your agreements don't address.
Third-Party
Vendor & Shadow AI
Third-party AI tools with opaque data handling practices. SaaS platforms adding AI features without security review or customer notification. Unsanctioned AI adoption across departments that your procurement process never evaluated.
Not sure how exposed your organization actually is?
The free consultation starts with an honest inventory of your current AI adoption and where the governance gaps are most likely to be.
What the Engagement Delivers
Assessments, policies, and programs that hold up.
Our AI governance engagements provide risk assessments, policy frameworks, and roadmaps that enable responsible AI adoption while protecting your organization from emerging threats.
ISO 42001 Gap Analysis Report
Comprehensive gap analysis against ISO 42001 Artificial Intelligence Management System requirements with control maturity scoring, gap identification, and prioritized remediation roadmap.
AI Risk Register
Model-specific risk register covering data leakage pathways, adversarial attack surfaces, bias and fairness risks, IP exposure, and vendor risk, with likelihood and impact ratings and treatment recommendations.
Shadow AI Discovery & Inventory
Structured process for identifying AI tools in use across your organization; including unsanctioned tools, SaaS platforms with embedded AI features, and department-level adoption that hasn't gone through security review.
Generative AI Acceptable Use Policy
Practical, enforceable acceptable use policy covering permitted and prohibited AI tool usage, data handling requirements, output review obligations, and accountability structures — written for employees, not lawyers.
NIST AI RMF Alignment Assessment
Assessment against the four core NIST AI RMF functions: Govern, Map, Measure, Manage with maturity scoring and specific recommendations for each function mapped to your AI deployment context.
AI Vendor Security Review
Security and privacy assessment of AI tools and vendors your organization uses or is evaluating covering data handling practices, model training data policies, contractual protections, and incident response obligations.
AI Governance Program Roadmap
Phased implementation roadmap for building a sustainable AI governance program, from immediate policy gaps through framework certification readiness, with resource estimates and milestone sequencing.
AI Incident Response Playbook
Incident response procedures specific to AI-related events; data leakage through AI tools, model output failures, adversarial attack detection, and regulatory notification obligations for AI-related incidents.
Framework Alignment
Standards that provide structure and regulatory defensibility.
Certification Available
ISO 42001 — AIMS
The first comprehensive international standard for AI governance. The Artificial Intelligence Management System framework covers AI lifecycle governance, risk management, and organizational controls. ISO 42001 certification is becoming the AI governance equivalent of ISO 27001 for security a signal of genuine program maturity that customers and regulators recognize.
U.S. Government Standard
NIST AI Risk Management Framework
The U.S. government-backed framework for managing AI risks across four core functions: Govern, Map, Measure, and Manage. Widely adopted across industries and increasingly referenced in federal procurement requirements, financial services guidance, and healthcare AI regulations.
Regulatory Preparation
EU AI Act Readiness
The EU AI Act is in force and its requirements are phasing in through 2027. Risk-based classification of AI systems, prohibited AI practices, transparency and explainability requirements, conformity assessments for high-risk AI, and general-purpose AI model obligations, we prepare you for what applies to your systems.
Industry-Specific Compliance
Three ways to engage,
depending on where you are.
AI governance engagements aren't priced as tiers of the same product - they're genuinely different types of work depending on what your organization needs. The free consultation is where we determine which one fits.
Point-In-Time
AI Readiness Assessment
2–4 weeks · Project-based
For organizations starting their AI governance journey or responding to a specific regulatory or customer requirement. Establishes your current-state baseline, identifies gaps, and produces the roadmap for what comes next.
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- ISO 42001 and NIST AI RMF gap analysis
- AI risk register and shadow AI inventory
- Acceptable use policy framework
- Governance program roadmap with prioritized milestones
Program Implementation
AI Governance Program
3–6 months · Project-based
For organizations ready to build a full AI governance program, from assessment through framework implementation, policy development, and certification preparation. The full engagement that takes you from where you are to where you need to be.
-
- Full ISO 42001 or NIST AI RMF implementation
- Policy suite development and governance structure
- AI model security review and vendor assessment
- Certification body preparation and audit readiness
Ongoing Advisory
AI Advisory Retainer
Monthly · Retainer-based
For organizations that need continuous AI governance support as the regulatory landscape evolves and their AI adoption grows. Available as a standalone retainer or integrated into the vCISO or DPO advisory engagement which is often the most efficient model.
-
- Regulatory monitoring and impact assessment
- New AI tool and vendor security review
- Policy updates as the regulatory landscape changes
- Board and executive reporting on AI risk posture
Already a Retainer Client?
AI governance integrates
naturally into your
existing engagement.
If you're already engaged with Neon Clarity for vCISO or DPO advisory, AI governance oversight is the most efficient addition rather than a separate product. Your advisor already understands your security and privacy program. Adding AI governance doesn't require starting over.
Retainer Services / 01
Fractional CISO Services
AI governance as part of your security program leadership; risk register, policy governance, board reporting, and model security reviews integrated into the retainer.
Retainer Services / 02
DPO & Data Privacy Advisory
AI governance through the privacy lens. Automated decision-making, training data obligations, right to explanation, and the intersection of privacy law with AI deployment.
Ideal For
Who This Engagement Serves
Choose the engagement model that matches your AI maturity and governance needs.
AI-First Companies
Organizations building AI products or whose business model relies on AI and machine learning. You need governance before investors, customers, or regulators demand it and the time between those two moments is shorter than most companies expect.
AI Governance Program
Companies deploying ChatGPT, Claude, Copilot, or other large language models across teams who need policies to prevent data leakage, compliance violations, and IP exposure and who need them before an incident makes the need obvious.
Regulated Industry AI Users
Healthcare, financial services, and government contractors using AI in high-risk contexts: diagnostics, underwriting, defense applications where regulatory scrutiny is active and the cost of governance failure is measured in more than just fines.
Start with a free consultation.
We'll talk through your current AI adoption, your governance gaps, and which engagement model makes sense for where your organization is right now.