What authority
have we given AI?
Where is AI operating, what decisions can it make or influence, and what are the defined guardrails?
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As AI systems gain access to sensitive data and greater authority to act, management needs a clear view of where AI is operating across public cloud, private cloud, and on-premises environments, what decisions it can influence, what controls exist, and what evidence is available for oversight.
Our AI Governance & Control Assessment gives leadership a fact-based view of the current environment so you can strengthen oversight, prioritize action, and prepare for Board, audit, and regulatory scrutiny.
A focused, high-impact engagement designed to fit executive timelines.
Clear findings and recommendations built for discussion and decision-making.
Assess policies, controls, data, infrastructure, authority, and decision rights.
Bring business, risk, security, legal, and technology into one management view.
Our assessment helps management answer the critical questions executives and Boards are asking about AI — with facts, not assumptions.
Where is AI operating, what decisions can it make or influence, and what are the defined guardrails?
→What sensitive data, systems, and business processes are in scope, and where are the greatest risks?
→Are policies, technical controls, monitoring, and oversight mechanisms effective and operating as intended?
→Do we have the evidence, documentation, and traceability needed to explain and defend AI-driven outcomes?
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Our AI Governance & Control Assessment gives management a practical, fact-based view of the current state — including how AI is governed, where it operates across public cloud, private cloud, and on-premises environments, what authority it has, what controls exist, and how prepared you are for Board, audit, and regulatory reporting.
A structured and collaborative approach designed to deliver clear insights and actionable recommendations.
Stakeholders, priorities,
and AI scope.
Governance, policy,
and controls.
Authority, exposure,
and evidence.
Target-state
recommendations.
Board-ready findings
and next steps.
Decision rights, ownership, policy, oversight, and escalation.
AI workloads across public cloud, private cloud, and on-prem environments, priority workflows, and exposure.
Sensitive information, access, use, and protection across AI activity.
What AI can recommend, decide, or execute, and under whose authority.
Approvals, human intervention, monitoring, and exception handling.
Traceability, forensic records, and management's ability to explain what occurred.