AI Risk Assessment for New Jersey SMBs

The 4-domain assessment framework

Our assessment covers four interconnected domains that determine your AI risk posture. Discovery identifies sanctioned and shadow AI use across the organization. Data Exposure maps what data classes (PII, PHI, IP, customer records) are flowing into which AI systems. Access and Identity documents who can use which AI tools and what guardrails exist. Policy and Training reviews your current AI governance documents and what training staff have received.

Most SMBs find they have 2-3x more AI tools in active use than their IT team realizes. Employees are often integrating ChatGPT, Gemini, Claude, or internal RAG systems into workflows without formal approval or visibility. This domain-based approach ensures nothing is missed.

What we examine during discovery

We conduct a forensic inventory of AI use across your technology stack. This includes Microsoft 365 Copilot enablement and tenant-level DLP policies, ChatGPT Enterprise or Team deployments, Google Gemini for Workspace integration, Slack and Teams native AI features, browser extensions and add-ons in use, custom RAG endpoints or internal AI agents, and personal accounts (Gmail, personal Copilot subscriptions) that employees are logging into from work devices.

We combine automated tenant telemetry, identity provider audit logs, and structured interviews with 4-6 key stakeholders (IT, compliance, ops, finance) to build a complete picture. Shadow AI is where most risk lives, and we surface it without blame.

How we collect evidence

Our three-phase evidence collection minimizes disruption to your team. Phase 1 uses read-only queries against your Microsoft 365 environment, identity provider logs, and DLP systems to identify AI services and data flows. Phase 2 sends a confidential, anonymous survey to a stratified sample of your staff asking what AI tools they use daily and what data they input. Phase 3 includes light-touch interviews with business leaders to understand your compliance requirements and risk appetite.

We operate under mutual NDA and produce no alarms or security events in your environment. All evidence gathering respects your data sensitivity and operates within your existing retention and access policies.

Compliance frameworks we map to

Your assessment is scored and reported against multiple frameworks so you can speak your industry's language. We map findings to NIST AI Risk Management Framework (NIST AI RMF), ISO 42001 (AI Management Systems), New York Department of Financial Services Cybersecurity Requirements for Financial Services Companies, HIPAA Security Rule (if healthcare), FINRA and SEC guidance on algorithmic accountability, and EU AI Act requirements (if you have European operations or customers).

This framework-agnostic approach means your report is immediately useful whether you're defending to an auditor, a cyber insurer, a regulator, or your board.

Engagement structure and timeline

The full engagement runs 3 weeks from kickoff to final report delivery. Week 1 is scoping and discovery: you join a kickoff call, we review your technology stack and compliance drivers, and we prepare our audit queries. Week 2 is evidence collection: we run automated telemetry pulls, distribute the employee survey, and conduct stakeholder interviews. Week 3 is analysis and reporting: we synthesize findings, assign risk scores, develop the remediation roadmap, and prepare your executive summary.

Deliverables include the full AI Risk Assessment Report (typically 30-50 pages), a slide deck for your board or leadership team, a 60-minute readout session where we walk through findings, and scoping for any recommended follow-on Remediation engagement.

What you receive from this assessment

The core deliverable is your AI Risk Assessment Report, a leadership-ready document that covers an executive summary with top 5 risks and residual-risk rating, a complete AI inventory broken down by department and risk tier, a data exposure matrix showing which data classes flow through which systems, a policy gap analysis comparing your current controls to framework requirements, and a prioritized 90-day / 6-month / 12-month remediation roadmap with effort and cost estimates.

We also provide a redacted sample report so you can see the format and depth before you engage. You own all findings and recommendations; the report is yours to share with your cyber insurance carrier, compliance counsel, or regulatory contacts as needed.

AI guardrails for New Jersey businesses

New Jersey is home to major healthcare networks, financial services firms, professional services practices, and manufacturing operations that all face heightened AI governance expectations from regulators, investors, and insurers. Healthcare providers like those in the Atlantic Health system are managing HIPAA-regulated data flowing through Copilot and ChatGPT. Financial advisory and accounting firms operating under FINRA / SEC oversight need documented controls over how client data is handled by AI systems. Legal practices are grappling with confidentiality and privilege risks when staff use external LLMs.

Our assessment is built for this mix. We understand NJ's regulatory landscape and the specific compliance drivers that matter to your vertical. We've completed assessments for healthcare networks in North Jersey, financial services practices across the state, and manufacturing operations in central NJ, and we know what your insurer and auditors are going to ask about.

Frequently asked