PMI – Data Landscape of GenAI for Project Managers

PMI – Data Landscape of GenAI for Project Managers focuses on one of the most important foundations of Generative AI: data.

The course helps project professionals understand how data characteristics, data quality, governance, security, ethical considerations, and organizational practices influence the effectiveness and responsible use of Generative AI.

PMI describes this learning path as covering data characteristics, governance, ethical considerations, risks, and implementation of GenAI within organizations.

Project managers increasingly work with AI-enabled tools that depend on large volumes of organizational and project data. Understanding how this data is collected, structured, governed, protected, and used is therefore essential for making informed decisions.

Key areas covered
Fundamentals of Generative AI and Large Language Models
Understanding data in GenAI environments
Data characteristics and quality
Structured and unstructured data
Data governance
Data security and protection
Data-related risks and limitations
Ethical considerations
Responsible use of AI
Project manager responsibilities related to data
Organizational readiness for GenAI
Data-driven AI implementation
Data Landscape Canvas
Practical considerations for implementing GenAI

The training is particularly relevant for project managers, PMO professionals, business leaders, transformation professionals, data-focused project teams, and professionals adopting GenAI within organizations.

PMI’s own learning material positions the Data Landscape course as part of its broader PMIxAI learning journey and emphasizes data fundamentals, LLMs, project-manager responsibilities, risks, limitations, and the Data Landscape Canvas.