Intake and risk tiers
Capture the business job, affected people, data, vendor, model, tools, actions, stakes, and owner, then route the use case by defined risk criteria.
Move useful AI work forward without losing business control.
A policy alone does not tell a team what to do with a new assistant, vendor feature, model, or production use case. People need a clear intake path, a way to judge risk, named decision rights, and boundaries they can apply during real work.
We help define a usable AI governance operating model: how ideas enter, how risk is classified, which data and capabilities are allowed, who approves or denies use, how exceptions work, and what evidence is reviewed after release.
Turn policy into a working decision system
Decision rights and approvals
Name who proposes, reviews, approves, operates, monitors, pauses, and retires each kind of AI-assisted work.
Data, vendor, and tool boundaries
Define which data may be sent, stored, retrieved, or logged, which vendors are allowed, and which capabilities can read, draft, recommend, or act.
Accountability and exceptions
Give each approved use case an accountable owner, a review date, an escalation path, and a time-bound exception process with recorded reasons.
Governance continues after approval
Approval starts an operating loop. The use case needs stated limits, evaluation evidence, monitoring signals, incident and escalation paths, and a cadence for reviewing changes in the workflow, data, vendor, model, or business stakes.
Lower-risk uses can follow a lighter route while higher-risk work receives deeper review and tighter controls. The model also defines when to deny, pause, narrow, or retire a use case rather than treating adoption as the default outcome.
What the client receives
The deliverables are working tools for the people proposing, reviewing, approving, operating, and overseeing AI use—not a policy document with no operating path.
- A use-case intake form and inventory with required context, accountable owners, current status, and review dates.
- A risk-tier model and decision table that routes routine, elevated, and prohibited uses to the right review path.
- Usage rules for approved data, retrieval sources, vendors, models, tools, retention, logging, human review, and consequential actions.
- A decision-rights and approval map covering proposal, assessment, approval, denial, operation, escalation, pause, and retirement.
- An exception register and process with scope, rationale, compensating controls, approver, expiration, and reassessment.
- Evaluation, monitoring, incident, and review-cadence requirements plus templates and an adoption sequence for putting the model into use.
Related routes
Governance can lead into one bounded AI-assisted workflow, architecture work around an inherited system, or integration controls around the data and tools involved.
When this is the right fit
This is useful when teams are already adopting AI without a shared decision path, leadership needs a practical operating model, or higher-stakes use cases are waiting on clear authority, evidence, and review boundaries.