Governance & Ownership
Responsibilities, policies, approvals, and decision-making.
AI Governance & Adoption Review
Scale AI adoption without losing control.
Artificial intelligence is entering product, engineering, and operations faster than the processes needed to govern it.
Identify which AI systems your organization is actually using, where risks exist, and what to prioritize to increase adoption in a safe, traceable, and operable way.
The context
AI adoption often moves faster than its governance.
A single organization may have employee tools, AI capabilities built into products, agents with system access, and automations created by different teams.
- ChatGPT, Claude, Gemini, or Copilot used by employees.
- SaaS tools that include AI.
- Models, APIs, RAG, and internal assistants.
- Agents able to query data or take action.
- Vendors processing corporate information.
Without a cross-functional view, leadership and Technology may not know:
- What AI exists, who owns it, and what data it uses.
- Which permissions it has and which vendors are involved.
- What decisions or actions it can execute.
- Which controls exist and which opportunities have the strongest ROI.
The goal is not to slow AI down. It is to use more AI with greater visibility and control.
Who it is for
Designed for organizations already using AI.
- Already use generative AI internally.
- Are rolling out Copilot, ChatGPT, Claude, Gemini, or other tools.
- Are adding AI to products or developing agents.
- Allow AI to access business data.
- Work with confidential information or personal data.
- Are moving from isolated experiments to broad adoption.
- Want to increase adoption without unnecessary bureaucracy.
The assessment
A cross-functional view of how the organization uses AI.
AI Inventory
Tools, models, vendors, integrations, and use cases.
Data & Privacy
Data, confidentiality, privacy, intellectual property, and flows.
Security & Architecture
Identity, permissions, logging, RAG, agents, and system access.
Human Oversight & Quality
Supervision, quality, reliability, transparency, and boundaries.
Vendors & Models
Models, vendors, dependencies, contracts, and third parties.
AI Literacy & Adoption
Training, approved tools, and responsible use.
Monitoring & Operations
Monitoring, incidents, change, and lifecycle.
The process
From the current state to an actionable roadmap.
Discovery
We understand strategy, main use cases, and the technology context.
Interviews
We speak with Technology, Security, Legal/DPO, leadership, and business stakeholders where relevant.
Assessment
We assess the organization using a structured framework.
Findings
We identify risks, gaps, opportunities, and quick wins.
Executive Roadmap
We turn findings into priorities for the next 90 days.
Deliverables
What you get.
AI Inventory
Initial map of AI systems, tools, and use cases.
AI Governance Score
Structured view of maturity by area. It is not a certification.
Critical Risk Assessment
Situations requiring priority attention.
Top Findings
Main risks, gaps, and pending decisions.
Opportunity Map
Opportunities for productivity, automation, and new capabilities.
Quick Wins
Actions that can be implemented quickly.
90-Day Roadmap
Priorities, owners, and recommended sequence.
Executive Review
Session to present conclusions and decide next steps.
The difference
Governance without separating technology from the business.
AI Governance should not be treated only as a legal or documentation exercise. The main risks and opportunities sit at the intersection of architecture, data, product, engineering, security, vendors, and the business.
The Review is approached from a CTO perspective: understanding both how systems are built and operated and the business context in which they need to create value.
Technology + Product + Risk + Business
Risk and adoption
Control risk and find opportunities.
Governance
- Shadow AI and sensitive data.
- Agents, permissions, and traceability.
- Vendors, security, and accountability.
- Human oversight.
Adoption
- Automation and productivity.
- New workflows and better processes.
- AI-enabled products and cost reduction.
- New capabilities and execution speed.
Governance should not become a brake on adoption. It should be the infrastructure that lets it scale.
What comes next
From assessment to execution.
AI Governance & Adoption Review
Understand the current state and set priorities.
Implementation
Implement policies, workflows, architecture, controls, and technical solutions.
Strategic Technology Advisory
Support technology, architecture, product, and AI evolution over time.
Scope
A technology review, not a legal certification.
The assessment can help structure requirements related to governance, privacy, security, or applicable regulation.
The Review is not a legal or regulatory certification. Where needed, specific matters should be validated with the relevant legal or data protection owners.
AI Governance & Adoption Review
Do you really know how your organization is using AI?
An initial conversation helps us understand the context and determine whether an AI Governance & Adoption Review can add value.