Accelerated Innovation

Ensure You Have the Capabilities to Win with GenAI

Making Your Solution Data "GenAI Ready"

Workshop
Is your data actually ready to support reliable, compliant GenAI use cases?

Many AI initiatives stall not because of models, but because the underlying data lacks the structure, context, and governance GenAI systems depend on to perform safely and effectively. 

To win, your GenAI initiatives need data that is intentionally designed, assessed, and aligned to real GenAI use cases. 

The Challenge

Teams preparing for GenAI often face hidden data readiness issues: 

  • Unclear readiness standards: Teams lack a shared definition of what “GenAI-ready” data actually requires. 
  • Hidden gaps and risks: Existing data assets contain quality, coverage, or compliance issues that surface too late. 
  • Misaligned data strategy: Data preparation efforts drift from the specific needs of priority GenAI use cases. 

Poor data readiness will limit GenAI effectiveness, introduce risk, and slow delivery of AI-powered solutions. 

Our Solution

In this hands-on workshop, your team defines, assesses, and aligns data readiness requirements to ensure your data can safely and effectively support targeted GenAI use cases. 

  • Define concrete criteria for what “GenAI-ready” means in your context. 
  • Assess existing data sources for gaps, risks, and limitations. 
  • Identify how context and formatting affect GenAI performance. 
  • Surface ethical and legal considerations tied to data usage. 
  • Align data preparation priorities directly to GenAI use cases. 
Area of Focus
  • Defining 'GenAI Ready' Data Requirements 
  • Assessing Existing Data Gaps and Risks 
  • Understanding the Role of Context and Format 
  • Preparing for Ethical and Legal Compliance 
  • Aligning Data Strategy to GenAI Use Cases 
Participants Will
  • Establish a shared definition of GenAI-ready data for their organization. 
  • Identify gaps and risks in current data assets. 
  • Understand how context and structure influence GenAI outcomes. 
  • Anticipate ethical and legal data considerations early. 
  • Align data strategy decisions to concrete GenAI use cases. 

Who Should Attend:

Data EngineersData ArchitectML EngineersGenAI Engineers

Solution Essentials

Format

Virtual or in-person

Duration

2 hours 

Skill Level

Intermediate technical teams working with data and AI initiatives 

Tools

Data inventories, documentation templates, and guided assessment frameworks 

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