Organisation
Roles, ownership, decision rights, escalation paths, and organisational accountability
AAM-004
AI Governance &
Operating Model
Is your organisation prepared to operate AI responsibly over the long term?
AI changes more than technology. It also changes responsibilities. New models, agents, and automated processes require clear roles, traceable decision paths, and a shared understanding of how AI is developed, approved, operated, and monitored.
The AI Governance & Operating Model creates transparency across existing structures and shows where responsibilities, processes, and controls are clearly defined – and where organisational gaps remain.
Discuss AI Governance →01
Why
A capable model and a secure platform are not enough. Organisations need to know who makes decisions, who accepts risks, how AI systems are approved, and how responsibility is exercised throughout the lifecycle.
Weak governance often becomes visible through unclear responsibilities, inconsistent processes, Shadow AI, missing risk assessments, or regulatory uncertainty. A sustainable operating model therefore connects organisation, responsibility, and continuous oversight.
Trust requires responsibility.
02
What
Governance is more than policy. We examine how the organisation works as a whole.
Governance
Policies, approvals, risk acceptance, Human Oversight, and binding controls
Operating Model
How responsibility is actually exercised across development, approval, operation, change, and retirement
Risk & Compliance
Regulatory requirements, AI Risk Management, documentation, traceability, and controls
People
Awareness, training, capability development, collaboration, and organisational acceptance
03
How
We analyse existing organisational structures, AI initiatives, and strategic objectives, combining interviews, workshops, and document analysis to build a robust picture of how governance actually works.
Understand
Understand the organisation, AI initiatives, objectives, and existing governance
Assess
Assess roles, responsibilities, policies, and decision-making processes
Review
Review the operating model across the AI lifecycle
Identify
Identify organisational gaps, risks, and opportunities for improvement
Prioritise
Prioritise findings and translate them into concrete actions
04
Knowledge
After the review, you have a much clearer understanding of the organisational foundation for operating AI:
Which roles and responsibilities are clearly defined – and where ownership is missing
How clearly approvals, risk acceptance, escalations, and Human Oversight are organised and traceable
Where governance and operating-model gaps make sustainable AI use more difficult
Which organisational and regulatory issues require management attention
Which actions should be prioritised to embed responsibility over the long term
Typical deliverablesGovernance Assessment ReportGap AnalysisRoles & Responsibilities ModelGovernance RecommendationsPrioritised ActionsExecutive Summary
05
scip AG
Governance must work in reality – not just on paper.
scip combines long-standing experience in cybersecurity and governance with our own research into Trustworthy AI. This means we do not examine organisational governance in isolation from the systems, risks, and decisions it is intended to control.
Our approach does not reduce AI Governance to compliance or the creation of additional policies. We examine whether responsibility can actually be exercised, decision paths work in practice, and the operating model supports the secure and traceable use of AI over time.
20+
Practical
Holistic
06
Perspective
AAM is not a linear process. Depending on the context, other questions may become relevant and different capabilities can be applied where they add value.
07
Insights
Our governance work is part of a broader understanding of Trustworthy AI: responsibility, controls, and traceable decisions are prerequisites for justified trust.
Trust and AI – Three Wrong Questions →ISO/IEC 38507:2022 — Governance Implications of the Use of AI by Organizations →On Trust in AI – A Systemic Approach →ISO/IEC 42001:2023 — AI Management Systems →AI Assurance & Trustworthy AI →08
Governance is not paperwork.
It is responsibility made operational.
Clear responsibility does not emerge from a policy alone. Let us examine whether your organisation can operate AI in a traceable, controlled, and responsible way over the long term.
Discuss with scip →