Level 2 · Fundamentals · 3 days

Data & AI
Governance

From strategic framework to operational deployment of AI agents

5 modules that build comprehensive mastery of data and AI governance — from roles and responsibilities to agentic architecture, through field deployment and hybrid process management.

G1 · Corporate Governance G2 · Data Governance G2+ · Deployment G3 · Agentic AI G4 · Processes & Workflows
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This learning path at a glance
5
Modules
3 d.
Total Duration
C-Level/CDO
Target Audience
Lvl.2
Level
G1 · Corporate Governance½d
G2 · Data Governance½d
G2+ · Data Deployment½d
G3 · Agentic AI Governance½d
G4 · Processes & Workflows½d
Learning Sequence · 5 steps

From strategy to deployment

G1 sets the corporate framework, G2 structures roles and tools, G2+ deploys in the field, G3 governs AI agents, G4 adapts processes. Each module builds on the previous one.

G1
Step 1 · Strategic frameworkCDO · CEO · Board
Corporate & Data Governance
Three levels of governance, the CDO's role, and how to treat data as a strategic asset.
½ day▾
Program
Chain of Responsibility
  • 3 governance levels — Board, Executive Committee, operational
  • The CDO — architect of corporate-level data governance
  • Data & AI Vector — 5 best practices, 5 maturity levels
  • Treating data as an asset — what the Board needs to see
Deliverables
  • 🏗️
    3-Level Governance Framework
    Board · Executive Committee · Operational — responsibilities and regulatory obligations by level
  • 📊
    Data & AI Maturity Grid
    5 levels — organizational self-assessment positioning
  • 💼
    CDO Job Description — Executive Committee version
    Responsibilities, decision-making scope, expected KPIs
📖
Self-Learning Module Available
Self Learning — Corporate & Data Governance
→
↓
framework → operational roles & tools
G2
Step 2 · Data frameworkCDO · DPO · Data Stewards
Data Governance
6 fundamental roles, RACI matrix, committee structure and organizational governance models.
½ day▾
Program
  • The 6 fundamental roles of data governance
  • RACI Matrix — who does what in the data framework
  • Data committee structure — the 4 essential governance bodies
  • Centralized, federated or domain-based — which model to choose?
  • Integrated data quality framework — from measurement to remediation
Deliverables
  • 👥
    Complete Data RACI
    Responsibility matrix — ready to adapt to your organization
  • 🏛️
    Committee Structure Diagram
    4 governance bodies — Data Council, Data Committee, Stewardship, Operational
  • ⚖️
    Org. Model Decision Grid
    Centralized vs federated vs domain — decision criteria and trade-offs
📖
Self-Learning Module Available
Self Learning — Data Governance
→
↓
roles → field deployment
G2+
Step 3 · Operational deploymentCDO · Architects · Project Managers
Data Governance — Deployment
7 root causes of failure, success conditions, field assessment and phased deployment roadmap.
½ day▾
Program
  • The 7 real root causes of data governance program failures
  • The 4 non-negotiable conditions — if one is missing, postpone
  • Map before you govern — the 5 assessment deliverables
  • Turning the assessment into a decision — the Executive Committee Case for Change
  • Phase 1 · Building the foundations — D+0 to D+180
  • Data dictionary and first quality controls
Deliverables
  • 🔍
    5-Deliverable Data Assessment
    Inventory, flows, quality, roles, regulation — complete template
  • 📋
    Executive Committee Case for Change
    Narrative structure to convince the Executive Committee to launch the program
  • 🗓️
    D+0 to D+180 Roadmap
    Phase 1 deployment plan with milestones, owners and success criteria
📖
Self-Learning Module Available
Self Learning — Data Governance — Deployment
→
↓
data governance → agentic AI governance
G3
Step 4 · Agentic governanceCDO · CIO · AI ArchitectsEU AI Act
Agentic AI Governance
5 autonomy levels, 3 governance patterns, EU AI Act and operational framework in 6 pillars.
½ day▾
Program
  • From AI assistant to autonomous agent — 5 levels of action
  • The 3 governance patterns — based on risk level
  • EU AI Act · What concretely changes for autonomous agents
  • The agentic governance framework — 6 operational pillars
  • Who decides what in agentic AI — governance matrix
Deliverables
  • 🤖
    5 Autonomy Levels Grid
    From assistant to autonomous system — governance requirements by level
  • ⚖️
    EU AI Act Agent Checklist
    What changes for high-risk agents — operational obligations
  • 🏗️
    6-Pillar Governance Framework
    Agent Policy, auditability, HITL, guardrails, monitoring, escalation
📖
Self-Learning Module Available
Self Learning — Agentic AI Governance
→
↓
agents → processes & target organization
G4
Step 5 · Target organizationCDO · CIO · Process Owners
Process & Workflow Governance
Process Mining, AI-augmented BPMN, new human-agent RACI and AI-native Operating Model.
½ day▾
Program
  • The process as a strategic asset — before, during and after AI
  • Process Mining — mapping real-world processes
  • The 4 agentic patterns — implications for governance
  • AI-augmented BPMN — notation for hybrid processes
  • New human-agent RACI — who is Accountable when the agent decides?
  • Target Operating Model — from project-based to AI-native organization
Deliverables
  • 🔬
    Process Mining Protocol
    Method to map a real-world process before automating it
  • 📐
    AI-Augmented BPMN Template
    Annotated notation for checkpoints, guardrails and HITL
  • 🏢
    AI-Native Operating Model Blueprint
    Target organizational structure for managing human-agent processes
📖
Self-Learning Module Available
Self Learning — Process & Workflow Governance
→
G1Corporate Governance
→
G2Data Governance
→
G2+Deployment
→
G3Agentic AI Governance
→
G4Processes & Workflows
3 days
Total Duration
Recommended prerequisite · Level 1 or equivalent experience
Master end-to-end Data & AI Governance
This learning path is the foundational building block for any CDO, DPO or data architect looking to build robust governance — from strategy to agent deployment.
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