Take the AI Readiness Diagnostic to identify where your AI product, platform, or organization may face governance, security, vendor risk, compliance, or audit-readiness gaps.
This is the simplest way to understand whether your AI systems are ready for enterprise scrutiny — before buyers, auditors, legal teams, or regulators start asking harder questions.
The diagnostic evaluates the areas most likely to create friction during enterprise review, procurement, audit, compliance, legal review, or executive scrutiny.
Whether your team can clearly explain what AI systems exist, what they do, who owns them, and what business impact they create.
Whether AI systems process personal data, sensitive data, PHI, financial data, customer information, or regulated data types.
Whether responsibility for AI risk, oversight, approvals, escalation, and controls is clearly assigned.
Whether AI systems have defined boundaries, review points, escalation paths, human oversight, and documented control expectations.
Whether third-party AI tools, model providers, APIs, copilots, and embedded vendors are identified and reviewed.
Whether your team has the artifacts buyers, auditors, security teams, procurement, and legal reviewers are likely to request.
Whether your governance approach aligns to recognized expectations such as NIST AI RMF, ISO/IEC 42001, SOC 2, HIPAA, or emerging mandates.
Whether enterprise buyers, legal teams, investors, auditors, or procurement teams have already started asking AI governance questions.
The report gives you a practical snapshot of where your AI governance posture stands and where attention may be needed before scrutiny increases.
It is designed to help you move from uncertainty to a clearer next step — whether that is a readiness review, vendor risk assessment, control layer blueprint, or deeper governance engagement.
The AI Readiness Diagnostic is the entry point for teams that need to understand their AI governance posture without starting with a large engagement.
For founders preparing to sell AI-enabled products into enterprise buyers, procurement teams, and security review processes.
For teams using AI around PHI, clinical documentation, patient workflows, medical data, or decision support.
For leaders responsible for AI governance, privacy, security, compliance, audit readiness, or risk management.
For teams building, deploying, integrating, or managing AI features that may create enterprise risk questions.
For organizations using AI internally and trying to understand governance, oversight, control, and evidence readiness.
For vendors selling into healthcare, finance, government, insurance, education, or other high-scrutiny environments.
For teams already receiving AI governance, security, vendor risk, or data handling questions from prospects or customers.
For teams that know AI governance matters but do not yet know what gaps matter most or what to fix first.
The diagnostic uses your responses to identify risk indicators, governance maturity signals, evidence gaps, and review pressure. The score is not meant to be a certification. It is meant to give your team direction.
The diagnostic looks at data sensitivity, regulated use, customer impact, third-party AI reliance, and whether AI outputs affect real business decisions.
It evaluates whether ownership, oversight, controls, policies, escalation paths, human review, and evidence are clearly defined.
It considers whether enterprise buyers, investors, auditors, legal teams, procurement, or regulators have already started asking AI governance questions.
A higher-risk result does not mean the AI system is bad. It means the governance, control, or evidence requirements may be more urgent before enterprise scrutiny increases.
Based on the result, the next step may be a 15-minute review, vendor risk assessment, control layer blueprint, or structured governance implementation.
Complete the diagnostic to identify where your AI governance, security, vendor risk, compliance, and evidence posture may need attention before enterprise scrutiny increases.
This diagnostic is designed as a starting point. It does not replace a full legal, compliance, audit, or security assessment, but it helps identify where AI governance gaps may exist and what to prioritize next.
