AI Data Governance and Privacy Training Course

Name: AI Data Governance, Privacy, and Integrity Course
Availability: InStock

Govern AI data across ownership, lineage, quality, privacy, access, retention, third parties, changes, and assurance.

AI Data Governance and Privacy Training Course

At a glance

Duration: 12 days
Format: Classroom
Cities: Doha, Abu Dhabi, Cape town, Dubai, Madrid, Berlin and more
Next session: 11 – 22 October 2026, Doha
Average fee: 9,900 €

Home
Our Categories
AI Data Governance, Privacy, and Integrity Course

Overview

AI Data Governance, Privacy, and Integrity Course is a ten-day practitioner course for governance, privacy, risk, data stewardship, and AI ownership teams, who leave with an AI Data Governance and Privacy Control Pack. Participants map ownership, lineage, quality, purpose, access, retention, third-party data, changes, incidents, and monitoring across the data lifecycle. The course connects data controls with accountability and human review. Agile Leaders Training Center provides training in AI data governance, privacy, and integrity.

Who Should Attend

Data governance teams responsible for policies, ownership, and stewardship
Privacy teams responsible for approved purposes and personal-data controls
Risk and compliance teams responsible for evidence and assurance
AI product teams responsible for data inputs, outputs, and changes
Data stewards responsible for quality, lineage, access, and disposition

The course assumes participants oversee business data or AI use and leaves out legal advice, cybersecurity engineering, model development, and broad enterprise AI strategy.

Departments and Industries

The course supports governed AI data use across assurance, technology, and operational functions.

Data governance, privacy, risk, compliance, and internal audit
Information technology, analytics, AI product, and records management
Finance, procurement, human resources, and shared services
Healthcare, insurance, banking, and professional services
Manufacturing, logistics, retail, and telecommunications

Learning Objectives

By the end of this course, participants will be able to:

Build ownership and stewardship controls for AI data
Analyze lineage, provenance, quality, and integrity evidence
Apply purpose, minimization, privacy, and access controls
Evaluate retention, deletion, and third-party data decisions
Diagnose data changes, incidents, exceptions, and control gaps
Build an AI data governance and privacy control pack

Course Agenda

Day 1: Governance Scope and Accountability

AI Data Lifecycle and Processing Map
Data Owner and Steward Responsibility Matrix
Decision Authority and Human Oversight Record
Policy-to-Control Traceability Grid
Governance Scope and Boundary Statement

Day 2: Inventory and Classification

AI Data Asset Inventory Template
Input, Reference, Output, and Feedback Classification
Sensitive Data Identification Checklist
Business Purpose and Approved Use Register
System and Data Dependency Map

Day 3: Lineage and Provenance

Source-to-System Data Lineage Diagram
Dataset Origin and Provenance Record
Transformation and Derivation Log
Source Authority and Reliability Rating
Traceability Gap Register

Day 4: Quality and Integrity

Data Quality Dimension Scorecard
Accuracy, Completeness, and Consistency Rules
Integrity Check and Reconciliation Method
Duplicate, Conflict, and Outlier Review
Quality Exception and Remediation Record

Day 5: Purpose and Data Minimization

Purpose Necessity and Proportionality Test
Minimum Data Requirement Matrix
Collection and Reuse Boundary Decision
Data Field Reduction Exercise
Purpose Change Approval Record

Day 6: Privacy Impact and Sensitive Data

AI Data Privacy Impact Screening
Individual and Group Impact Map
Sensitive Data Handling Decision Tree
Privacy Risk and Mitigation Register
Human Review and Escalation Gate

Day 7: Access, Retention, and Deletion

Role-Based Data Access Matrix
Access Request and Approval Workflow
Retention Rule and Trigger Schedule
Deletion and Disposition Evidence Log
Access and Retention Exception Review

Day 8: Third-Party and Change Control

Third-Party Data Due Diligence Checklist
Data Sharing and Transfer Control Record
Dataset Version and Change Log
Change Impact and Revalidation Checklist
Supplier Data Responsibility Schedule

Day 9: Incidents, Monitoring, and Assurance

Data Incident and Integrity Event Taxonomy
Control Monitoring Indicator Set
Exception, Waiver, and Corrective Action Register
Governance Evidence Review Calendar
Control Gap and Assurance Report

Day 10: AI Data Control Practice

Suggested Exercise: Map Ownership and Data Flow
Suggested Exercise: Test Quality and Privacy Controls
Suggested Exercise: Review Third-Party Data Changes
Suggested Exercise: Record Incidents and Assurance Evidence
Capstone Exercise: AI Data Governance and Privacy Control Pack

Practical Exercises

The course uses suggested activities to convert governance requirements into reviewable data controls.

Suggested activity: map data assets, purposes, owners, stewards, systems, and lifecycle dependencies
Suggested activity: document lineage, provenance, transformations, quality rules, integrity checks, and exceptions
Suggested activity: assess minimization, privacy impacts, access, retention, deletion, and third-party responsibilities
Suggested activity: monitor changes and incidents, assemble evidence, and prioritize corrective actions

FAQs

Who suits AI data governance, privacy, and integrity training?

AI data governance, privacy, and integrity training suits governance, privacy, risk, data stewardship, assurance, and AI ownership teams. It assumes responsibility for business data or AI use, not software engineering.

How does AI data governance differ from general AI governance?

AI data governance concentrates on data ownership, purpose, lineage, quality, privacy, access, retention, third parties, and integrity evidence. General AI governance also addresses broader system, model, organizational, and use-case decisions.

Why do AI systems need data lineage and provenance?

Lineage and provenance show where data originated, how it changed, which systems handled it, and which outputs depend on it, enabling review of quality, authority, accountability, and corrective action.

How does data minimization apply to AI data governance?

Data minimization requires teams to define the purpose, identify the least data necessary, challenge collection and reuse, document exceptions, and reassess the decision when the purpose or system changes.

How should AI data integrity incidents be managed?

Integrity incidents should be classified, contained, traced to affected data and outputs, assigned to an owner, corrected with evidence, and reviewed for control changes and follow-up monitoring.

Conclusion

Participants take back an AI Data Governance and Privacy Control Pack linking assets, purposes, ownership, lineage, quality, privacy, access, retention, third parties, changes, incidents, and assurance evidence. It makes control responsibilities and decisions visible. It supports repeatable governance reviews and documented corrective action across the AI data lifecycle.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

Download Brochure (PDF) Print PDF

Showing 21-40 of 76 events

Location	Dates	Duration	Mode	Price
Geneva	Week 53, 2027 3 – 14 January 2027	12 Days	Onsite	€11,000
Rome	Week 02, 2027 11 – 22 January 2027	12 Days	Onsite	€10,000
Abu Dhabi	Week 02, 2027 11 – 22 January 2027	12 Days	Onsite	€8,000
Amsterdam	Week 03, 2027 18 – 29 January 2027	12 Days	Onsite	€10,000
London	Week 04, 2027 25 January – 5 February 2027	12 Days	Onsite	€10,000
Prague	Week 05, 2027 1 – 12 February 2027	12 Days	Onsite	€10,000
Muscat	Week 05, 2027 7 – 18 February 2027	12 Days	Onsite	€11,400
Cairo	Week 06, 2027 8 – 19 February 2027	12 Days	Onsite	€7,000
Milan	Week 07, 2027 15 – 26 February 2027	12 Days	Onsite	€10,000
Sharm El-Sheikh	Week 08, 2027 22 February – 5 March 2027	12 Days	Onsite	€7,000
Riyadh	Week 08, 2027 28 February – 11 March 2027	12 Days	Onsite	€11,400
Vienna	Week 09, 2027 1 – 12 March 2027	12 Days	Onsite	€10,000
Phuket	Week 09, 2027 7 – 18 March 2027	12 Days	Onsite	€9,000
Abu Dhabi	Week 10, 2027 8 – 19 March 2027	12 Days	Onsite	€8,000
Johannesburg	Week 10, 2027 14 – 25 March 2027	12 Days	Onsite	€6,400
Langkawi	Week 11, 2027 21 March – 1 April 2027	12 Days	Onsite	€10,000
Dubai	Week 12, 2027 22 March – 2 April 2027	12 Days	Onsite	€8,500
Bangkok	Week 12, 2027 28 March – 8 April 2027	12 Days	Onsite	€9,000
Bali	Week 13, 2027 4 – 15 April 2027	12 Days	Onsite	€10,000
Madrid	Week 15, 2027 12 – 23 April 2027	12 Days	Onsite	€10,000

Frequently asked questions

What does this course cover?

OverviewAI Data Governance, Privacy, and Integrity Course is a ten-day practitioner course for governance, privacy, risk, data stewardship, and AI ownership teams, who leave with an AI Data Governance and Privacy Control Pack. Participants map ownership, lineage, quality, purpose, access, retention, third-party data, changes, incidents, and monitoring acr…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

AI Data Governance and Privacy Training Course