AI Risk Assessment: A Step-by-Step Guide for Small and Midsize Businesses

You’ve heard that AI creates security risks. But do you know which specific AI tools in your organization pose the biggest risk — and what you should do about them first?

An AI risk assessment answers those questions. It documents what AI tools you’re using, evaluates the risk each one poses to your data and compliance posture, and gives you a prioritized action plan. This guide walks you through the process step by step.

What Is an AI Risk Assessment?

An AI risk assessment is a structured evaluation of the artificial intelligence tools your organization uses — or is considering using — to identify potential security, privacy, compliance, and operational risks. It’s the AI-specific version of a standard IT risk assessment, adapted for the unique characteristics of AI tools: their data handling practices, training data policies, output reliability, and integration with your existing systems.

The output is a documented inventory of AI tools paired with a risk rating and recommended controls for each. It becomes the baseline for your AI security program and the primary document an auditor or compliance assessor would review when evaluating your AI governance posture.

Step 1: Build Your AI Tool Inventory

You cannot assess risk you don’t know about. Start by cataloging every AI tool in use across your organization — officially approved and employee-sourced.

Sources to check: IT-approved software lists, software license records, browser extension inventories, SaaS management platforms, expense reports (employees often expense AI subscriptions), and direct surveys of department heads. Don’t forget AI features embedded in tools you already use — Microsoft 365, Salesforce, HubSpot, Slack, and dozens of other platforms have added AI capabilities in recent product updates.

For each tool, document: the tool name and version, the vendor, the primary use case, which employees or departments use it, whether it’s enterprise or consumer tier, and whether a data processing agreement is in place.

Step 2: Identify the Data Each Tool Touches

For each AI tool in your inventory, determine what types of data employees are inputting into it. This is often more revealing than organizations expect.

Common data categories to evaluate: personally identifiable information (PII), protected health information (PHI), payment card data (PCI), controlled unclassified information (CUI), proprietary business information (source code, financial projections, contracts, strategic plans), and employee data. Document what’s actually being entered, not just what should be entered.

Step 3: Evaluate Risk for Each Tool

With your inventory and data mapping complete, evaluate the risk level for each tool using four dimensions:

• Data handling risk: Does the vendor use input data for model training? Is data stored, and for how long? Where is it processed? Is there a DPA?
• Compliance risk: Does use of this tool create compliance exposure under HIPAA, CMMC, PCI-DSS, SOC 2, or other applicable frameworks?
• Access risk: Is access controlled via SSO? Are credentials shared? Can former employees still access the tool?
• Output risk: Is AI-generated output being used in high-stakes decisions without human review? Could inaccurate AI output create legal or operational risk?

Rate each tool as Low, Medium, High, or Critical risk based on the combination of data sensitivity and control gaps identified.

Step 4: Prioritize and Remediate

Your risk assessment will surface a range of issues. Prioritize remediation based on two factors: the severity of the risk and the ease of remediation. Quick wins — like disabling conversation history in ChatGPT or requiring SSO for an existing enterprise tool — should be addressed immediately. Larger structural issues — like replacing a consumer AI tool with an enterprise alternative, or building out a full data classification framework — go on a prioritized roadmap with owners and deadlines.

Common remediation actions include: upgrading consumer tools to enterprise tiers, implementing SSO and MFA for AI tool access, adding tools to your DLP monitoring scope, publishing and training employees on an AI acceptable use policy, and removing or blocking tools that pose unacceptable risk with no viable path to remediation.

Step 5: Document and Review

The completed risk assessment is a living document. New AI tools are deployed regularly — by your IT team, by your SaaS vendors, and by your employees. Build a review cadence into your program: quarterly for high-risk tools, annually for the full inventory. Any time a new AI tool is adopted, it should go through the assessment process before deployment, not after.

Getting the Assessment Done

If your organization doesn’t have dedicated security staff, conducting an AI risk assessment can feel like a significant undertaking. A vCISO can run the process for you — conducting the tool inventory, facilitating data mapping sessions with department heads, evaluating vendor risk, and producing the completed assessment with a prioritized remediation roadmap.

Cover6 Solutions offers AI risk assessments as a standalone engagement. Schedule a consultation to get started →

See the full AI security picture: AI Security for Business: The Complete Guide →

Tyrone E. Wilson is a U.S. Army veteran, vCISO, and founder of Cover6 Solutions — a veteran-owned cybersecurity firm specializing in vCISO services, penetration testing, and security training.