AI Strategy · INTELLIGENCE
Enable responsible adoption without making governance a dead end.
COSII builds practical policy, decision rights, risk classification, review, and oversight around how the organization uses AI.
Establish AI Governance →The business problem
When the work has real consequences, clarity comes first.
Best for
Organizations already using generative or predictive AI without consistent rules, ownership, or executive visibility.
Signals it is time to act
- 01Employees are using public tools with sensitive information.
- 02AI procurement has no consistent risk review.
- 03Legal, security, data, and business leaders are working separately.
- 04The organization has a policy but no operating process.
What you receive
An engagement built around decisions and action.
How we work
Operational from the start.
- 01Orient
Clarify the business context, constraints, stakeholders, and decisions that need to be made.
- 02Assess
Build an evidence-based view of the current state, material risks, and practical opportunities.
- 03Prioritize
Sequence the work by business consequence, dependency, effort, and available capacity.
- 04Operationalize
Put ownership, measures, and an executable rhythm around the roadmap.
Designed outcomes
Progress leaders can see and teams can sustain.
Clear boundaries for safe adoption
Faster, consistent review of use cases
Named accountability
Governance aligned with NIST AI RMF concepts
Questions leaders ask
Frequently asked questions.
Will governance slow down experimentation?
Good governance makes low-risk work easier to approve while focusing scrutiny where consequences are higher.
Can this align with existing risk processes?
Yes. AI governance should connect to existing security, privacy, legal, procurement, and enterprise-risk practices.
A practical next step
Bring us the problem behind the project.
A 30-minute conversation is enough to clarify the situation, the decision in front of you, and what should happen next.
Establish AI Governance