AI Risk Assessment
Identifies broad business, operational, legal, ethical, privacy, and governance risks from AI adoption.
Scope
Reviews AI use cases, business impact, data quality, model risk, bias, explainability, privacy, security, legal exposure, ethics, and human oversight.
The gaps it finds
Unapproved AI use, poor governance, weak human review, biased decisions, unclear accountability, privacy exposure, poor data quality, and model risk.
Value to the board
Enables responsible AI adoption while reducing the risk of poor decisions, data misuse, bias, and reputational harm.
Framework alignment
- NIST AI RMF
- ISO/IEC 42001
Reporting
Like every assessment in the portfolio, this engagement ends with the full deliverable set, from executive summary and maturity scorecard to remediation roadmap and board dashboard. The methodology page describes each deliverable.
Scope this assessment
A scoping conversation confirms objectives, stakeholders, systems, and the document request list before any work begins.