GFAI0: Governance Frameworks for (Meta)data and AI Management Learning Plan
As data and AI initiatives scale, governance must keep pace. Instructed by data management master instructor Irina Steenbeek, the nine-course Governance Frameworks for (Meta)Data and AI Management Learning Plan provides a structured approach to building organizational capabilities across data, metadata, and AI governance, from foundational principles to enterprise-wide implementation. Strategic alignment, framework development, and metadata and data quality management are addressed through practical tools, templates, and exercises that support tailored, enterprise-ready governance strategies aligned with compliance, quality, and organizational goals.

Program Overview
Modern organizations face increasing pressure to manage data, metadata, and AI initiatives with clarity, compliance., and strategic alignment. Without effective oversight, businesses risk wasted resources, regulatory issues, and missed opportunities to drive value. To address these challenges and establish a structured approach to decision-making, data management expert Irina Steenbeek guides learners through designing practical, enterprise-wide governance frameworks in the Governance Frameworks for (Meta)Data and AI Management Learning Plan.
Throughout this nine-course curriculum, participants explore how to define the necessary policies, processes, and roles for success through real-world examples, templates, and hands-on exercises. The program bridges the gap between strategy and operations, covering essential topics ranging from enterprise architecture and data quality to the specific oversight required for AI and risk management.
By the end of this learning plan, attendees will possess the skills to implement integrated strategies that ensure clarity, accountability, and measurable impact, empowering them to transform governance from a theoretical concept into a functional system that improves operational efficiency and decision-making.
Program Highlights
This 9-course learning plan offers:
- Over 20 hours of expert-led video instruction.
- Nine total courses covering the developing of governance frameworks across the enterprise.
- Knowledge checks after each module and a final exam.
- Downloadable templates, exercises, and slides in every class
- Real-world examples and applied frameworks that connect theory to practice.
Pricing and Credits
- Learning Plan Price: $749
- Individual Course Price: $99
- CEUs: 30 hours
How It Works
This learning plan includes nine on-demand, self-paced courses that can be taken individually or as a complete certification pathway. Each course includes:
- A 94- to 207-minute instructional video
- Section-level Check-for-Understanding quizzes
- A 17- to 23-question content-based practice test per course
- Downloadable presentation slides and study materials
- Unlimited access and progress tracking
Courses in the Learning Plan
- Introducing the Key Concepts of Meta(Data) and AI
- Linking Business Objectives to (Meta)Data and AI Initiatives
- Defining the Scope of Governance Frameworks and Developing a Strategy
- Developing an Enterprise-Wide Governance Framework
- Developing the Governance Framework for Enterprise Architecture
- Developing the Governance Framework for Metadata Management
- Developing the Governance Framework for Data Quality Management
- Customizing AI Industry Framework to an Organization’s Needs
- Developing an Integrated Implementation Plan for (Meta)Data Management Capabilities
By the End of the Governance Frameworks for (Meta)Data and AI Management Learning Plan, You’ll Be Able To:
- Define core concepts in data, metadata, information, and AI governance.
- Align business objectives with data, metadata, and AI initiatives for strategic impact.
- Design and implement enterprise-wide governance frameworks across data, metadata, and AI.
- Develop integrated implementation plans connecting data, metadata, AI, and risk capabilities.
- Apply maturity assessments, KPIs, and risk mitigation strategies to operationalize governance initiatives.
Why the Governance Frameworks for (Meta)Data and AI Management Learning Plan Learning Plan?
Benefits:
- Provides a structured methodology to establish organizational data, metadata, and AI governance capabilities.
- Equips professionals to design policies, roles, processes, and frameworks that align with business strategy.
- Offers practical exercises and templates to translate concepts into enterprise-ready plans.
- Supports compliance with industry regulations while enabling responsible AI adoption.
- Strengthens organizational maturity, risk management, operational alignment, and decision-making across initiatives.
Is This Learning Plan Right for You or Your Team?
This program is ideal for:
- Data, AI, and governance professionals leading enterprise initiatives
- Business architects connecting strategy to governance frameworks
- Compliance and risk managers responsible for data, metadata, or AI oversight
- Project managers coordinating complex governance, data, or AI implementations
- Leaders seeking structured approaches to integrate governance, quality, and risk management
No technical experience is required. This learning plan is designed for business- and technical-focused professionals seeking practical tools to establish, govern, and integrate organizational data, metadata, and AI capabilities.
Private Team Training
Bring your team up to speed when you take advantage of our private in-person or virtual courses tailored to your organization’s needs. DATAVERSITY offers custom team training and bulk licensing options to ensure consistency and scalability in your data management initiatives.
We offer several bulk licensing options for corporate and group use.
Contact us for a follow-up discussion!
Email: [email protected]
Backed by Industry Leader
Developed and delivered by DATAVERSITY®, a globally respected leader in data governance education, known for delivering trusted training, influential conferences, and deep industry insights.
Complete All Nine Governance Frameworks for (Meta)data and AI Management Learning Plan Courses
1. GFAI1: Introducing the Key Concepts of Meta(Data) and AI
required
This course establishes a shared foundation for understanding core industry concepts across data, metadata, AI systems, and governance. Led by data management master instructor Irina Steenbeek, it introduces current guidelines, key definitions, and a practical use case that anchors learning throughout the program.
View Details2. GFAI2: Linking Business Objectives to (Meta)Data and AI Initiatives
required
This course focuses on connecting business objectives to data, metadata, and AI initiatives using a structured, value-driven methodology. Led by data management master instructor Irina Steenbeek, it provides practical tools to prioritize initiatives, engage stakeholders, and assess business impact and return on investment.
View Details3. GFAI3: Defining the Scope of Governance Frameworks and Developing a Strategy
required
This course guides the design and strategic planning of governance frameworks for data, metadata, and AI. Data management master instructor Irina Steenbeek provides methods for scoping frameworks, analyzing regulations and industry standards, and developing capability maps and high-level roadmaps. Participants gain the skills to align governance initiatives with organizational strategy.
View Details4. GFAI4: Developing an Enterprise-Wide Governance Framework
required
Building an effective enterprise-wide governance framework is essential for aligning data, metadata, and AI initiatives with organizational strategy and structure. This course, led by data management master instructor Irina Steenbeek, explores operating models, governance roles, policies, processes, and IT tool requirements, while providing participants with practical tools to assess maturity, establish KPIs, and develop a strategic roadmap for governance implementation.
View Details5. GFAI5: Developing the Governance Framework for Enterprise Architecture
required
Enterprise architecture governance must span business, data, application, and technology domains to effectively support modern organizations. This course, led by data management master instructor Irina Steenbeek, provides structured methods for defining capabilities, artifacts, roles, and governance mechanisms that enable integrated data and AI initiatives.
View Details6. GFAI6: Developing the Governance Framework for Metadata Management
required
Effective metadata governance depends on a strong relationship between business strategy, data architecture, and organizational context. In this course, led by data management master instructor Irina Steenbeek, participants explore how metadata capabilities, policies, roles, and tools combine to support effective governance and measurable outcomes.
View Details7. GFAI7: Developing the Governance Framework for Data Quality Management
required
Grounded in real-world governance challenges, this course examines how organizations can design and operate effective data quality frameworks aligned with business priorities and AI requirements. Led by data management master instructor Irina Steenbeek, it focuses on structuring quality dimensions, rules, roles, and supporting tools across the data lifecycle. Emphasis is placed on maturity assessment and performance measurement to enable trusted, scalable data.
View Details8. GFAI8: Customizing AI Industry Framework to an Organization’s Needs
required
Focused on turning complex AI regulations and industry frameworks into practical organizational governance, this course explores how AI initiatives can be structured responsibly and strategically. Led by data management master instructor Irina Steenbeek, it examines AI risks, principles, use cases, and policies to support compliant and value-driven adoption.
View Details9. GFAI9: Developing an Integrated Implementation Plan for (Meta)Data Management Capabilities
required