From understanding where you stand to operating a sustainable governance program, we help make responsible AI a working reality.
Evaluate AI usage, policies, risk practices, vendors, data, employee awareness, and organizational readiness. Deliverables can include a readiness assessment, gap analysis, AI system and use-case inventory, risk priorities, and a prioritized 90-day roadmap.
Establish a centralized view of AI systems and use cases, including owners, vendors, purpose, data processed, degree of automation, approval status, and review dates.
Apply stronger oversight where risk is greatest. Evaluate data sensitivity, automation, human involvement, customer or employee impact, privacy, safety, and consequences of failure.
Translate the framework's Govern, Map, Measure, and Manage functions into the policies, roles, controls, and decisions your organization uses every day.
Develop the scope, policies, processes, documentation, reviews, and continual improvement practices of an AI management system. We prepare organizations for independent assessment; we do not issue certification.
Create practical standards for acceptable use, sensitive data, approved tools, AI-assisted decisions, human review, and incident escalation.
Establish a structured way to evaluate use cases by business impact, data sensitivity, privacy, security, reliability, transparency, and third-party dependency.
Understand how vendors use AI, process your data, manage their models, monitor outputs, and report incidents before risks are embedded in your operations.
Turn policy into practical guidance employees, managers, and executives can understand and apply in their day-to-day decisions.
Maintain governance as tools, vendors, and risks evolve with ongoing use-case reviews, risk assessments, committee support, incident review, and executive reporting.
Start with a clear picture of where you are today.
