AI Governance and Security
Put clear boundaries around AI access and action.
Help your people use AI productively while establishing appropriate permissions, data controls, approvals, and oversight.
Turn expectations into control requirements
We help connect AI policy and business needs to practical control decisions across employee tools, internally developed applications, and agents.
- Approved tools and managed access
- Data-handling and permission requirements
- Owners, approvals, and exceptions
Evaluate the architecture behind the controls
Model access, identity, application permissions, APIs, and logs need to support the intended operating model. We help define the requirements and compare approaches with relevant specialists.
- Existing platform capabilities and gaps
- Gateways and other model-access approaches
- Agent authority and connected-system controls
Preserve momentum as use expands
A useful governance approach supports innovation with an understood path for reviewing new uses, connections, and changes.
- Review and release expectations
- Operational monitoring responsibilities
- Evidence and escalation requirements
A focused engagement
AI Visibility and Governance Review
The scope and resources are shaped around your priority. Use this as a starting point for that conversation.
Who it is for
CIO, CISO, and IT or data leaders who need an operating baseline for AI use.
Triggering events
New acceptable-use policy; unapproved tools or personal accounts; Copilot or another enterprise AI rollout; audit questions; acquisition.
Scope
Agreed business units, AI channels, evidence sources, and data classes. Help develop or refine an AI acceptable-use policy where needed. Review approved tools and models, known shadow AI, personal accounts, permissions, control gaps, and operating ownership.
Customer inputs
Existing policies; approved-app lists; available identity, endpoint, browser, network, SaaS, and expense records; relevant contracts; stakeholder interviews. Use authorized exports and least-privilege access.
Deliverables
Developed or revised AI AUP when in scope; evidence-tagged usage baseline with discovery limitations; prioritized risk and gap register; ownership and exception requirements; control roadmap; executive readout.
Expected next step
Agree on immediate policy and ownership decisions, then scope discovery tooling, approved-access options, or a gateway evaluation.
Boundaries
Point-in-time advisory review within agreed access and coverage. No guarantee of complete shadow AI discovery. Legal and regulatory approval stays with the customer. Tool deployment and continuous monitoring require separate scope.
Control coverage depends on the platforms, configurations, and access paths in scope. Technical validation and implementation are assigned to agreed qualified resources.
A practical next step
Start with your AI priority.
Tell us what you are trying to accomplish and where the decision needs more clarity.