Daviyon DanielsAn AI security assessment is a structured review of the systems, data flows, controls, vendors, and governance practices surrounding an organization’s use of AI. The useful output is not simply a score. It is documented evidence showing what was reviewed, what was found, what limitations apply, and what should happen next.
Across industries, that evidence can support customer or vendor due diligence, procurement, internal governance, and decisions about deploying or expanding an AI workflow. Where a specific law, contractual obligation, or framework applies, the assessment can map relevant evidence to those requirements within the agreed scope. It does not certify compliance or guarantee that a customer, auditor, insurer, regulator, or other reviewer will accept the results.
What an AI security assessment covers
The exact scope should be agreed before work begins. Common areas include:
AI system inventory. Identify the AI tools, applications, model providers, integrations, and embedded AI capabilities that belong in scope.
Data-flow mapping. Document what sensitive data reaches those systems, where it is processed or retained, and which third parties are involved.
Security controls. Evaluate access control, data protection, monitoring, incident response, vendor management, AI governance, and other controls relevant to the environment.
Framework mapping. Where relevant to the scope, assessment evidence may be mapped to NIST AI Risk Management Framework concepts, cybersecurity frameworks, and applicable industry or contractual requirements. Framework mapping organizes evidence; it is not an endorsement or certification from the framework publisher.
Risk findings. Document gaps, evidence, severity, assumptions, and limitations so the organization can distinguish urgent issues from longer-term improvements.
Remediation planning. Turn findings into a prioritized roadmap rather than ending with a list of problems.
The assessment process
A well-scoped engagement typically follows five steps.
1. Scope. Identify the AI systems, entities, review requirements, evidence sources, and stakeholders that belong in the engagement.
2. Discover and map. Build the in-scope AI inventory and document relevant data flows, vendor relationships, policies, and technical context.
3. Assess. Review evidence against the agreed control areas and framework references. Where hands-on technical testing is appropriate, it should be explicitly authorized and included in scope.
4. Analyze and document. Rate and document findings using the agreed methodology, record evidence gaps and limitations, and prepare remediation priorities.
5. Sign and brief. A named assessor reviews and signs the final assessment and walks the organization through the findings.
What you receive
An Ayliea engagement can include an executive summary, technical findings, AI system inventory, framework crosswalk, risk register, remediation roadmap, and assessor sign-off. The exact package is defined by the engagement scope. For a practical preparation list, see the AI security assessment evidence checklist.
These are durable deliverables provided directly to the client organization. Ayliea software may support an engagement where available, but a live portal is not required to receive or retain the signed assessment documents.
How organizations use the assessment
A customer or partner may ask how an AI-enabled product handles sensitive data, which models and vendors are involved, who can authorize actions, and how the organization detects or responds to failures. Existing security reports and questionnaires may provide baseline evidence without addressing the particular AI systems or workflows under review.
An independent assessment can give the organization a focused evidence package for that conversation. The receiving party still decides what evidence it accepts and whether further testing, questionnaires, contractual terms, or remediation are needed. A healthcare vendor responding to a hospital review, a financial-services team evaluating an internal AI workflow, and a software company preparing for enterprise procurement may each need different scope and framework references.
What it costs
Ayliea’s current public pricing is available at ayliea.com/pricing:
- AI Security Review: from $3,500
- AI Security Assessment: from $7,500
- Comprehensive AI Security Assessment: from $15,000
- Enterprise / Complex Scope: custom, priced after the scoping call
Final price depends on factors such as the number of AI systems, entities, framework mappings, technical testing requirements, and evidence expectations in scope.
Every engagement starts with a 20-minute scoping call. The goal of that call is to determine whether an assessment fits the problem and, if it does, what should actually be included before either side commits to the work.
When an assessment is worth considering
An assessment is particularly useful when:
- a customer, partner, or internal reviewer is asking AI-specific security questions;
- your organization cannot clearly explain which AI systems touch sensitive data or can take consequential actions;
- AI vendors or model providers have changed faster than your existing security documentation;
- internal security, privacy, or compliance teams need one evidence set rather than disconnected answers;
- leadership wants an independent view of AI risk before expanding an AI deployment.
Start with the decision or review that prompted the request and the evidence the intended reader actually needs. Scope the assessment around that problem rather than a generic checklist. For healthcare-specific obligations, see the healthcare industry page.
Explore assessment services or request a 20-minute scoping call.