Objective

Upon completing this lab, you will be able to:

• Synthesize key concepts from the playbook (strategy, data, culture, risk, infrastructure) into a practical diagnostic tool.
• Develop a custom AI Readiness Assessment scorecard with clear criteria and a logical scoring mechanism.
• Critically evaluate an organization's readiness for an AI initiative using your self-created scorecard.
• Map assessment scores to a set of strategic recommendations, demonstrating the link between diagnosis and action.

Tools/Resources Needed

• A document editor or spreadsheet tool (Google Docs/Sheets, Word/Excel).
• The Ready, Go! Get Set? The AI Strategy Success Playbook as the primary source for developing your assessment criteria.
• Any other resources or references you find from searching online

Description of Assignment

Background

A brilliant AI model can fail spectacularly if the organization isn't ready to adopt it. As we explored in Chapter 10: Now That We Found (Tool), What Are We Gonna Do?, true readiness is not just about having the right technology. It's a holistic measure of a company's strategy, data maturity, culture, skills, and governance. An organization that ignores these foundational pillars before launching an AI initiative is setting itself up for failure.

Instead of providing a generic checklist, this lab challenges you to build your own AI Readiness Assessment based on everything you've learned. You will act as the strategist, deciding what questions are most important to ask to determine if a business is truly prepared to succeed with AI.

Part 1: Design Your AI Readiness Assessment Scorecard

Your first task is to create a scorecard to evaluate a company's readiness for a major AI initiative. This scorecard should consist of the criteria you believe are most critical for success.

1. Establish Assessment Categories: To structure your scorecard, you must include categories that cover the key themes of this book. Your scorecard should contain criteria related to at least five of the following six areas:
   • Strategy & Vision (ref. Chapter 2)
   • Data Maturity (ref. Chapter 7)
   • Technical Infrastructure (ref. Chapter 7)
   • Process & Workflow Integration (ref. Chapter 3)
   • People & Culture (ref. Chapter 10)
   • Risk & Governance (ref. Chapters 5 & 6)
2. Define Criteria & Scoring: Under each category, create 2-3 specific criteria in the form of questions. For each question, define a clear scoring system (e.g., a 1-5 scale where 1 is low readiness and 5 is high readiness). Your scorecard should be able to produce a total "Readiness Score."
   • Example Criterion (for the 'Data Maturity' category):
     • Criterion: "Does the organization have centralized, clean, and accessible data sources for the proposed AI initiative?"
     • Scoring: 1 = No, data is siloed and messy. 3 = Data is available but requires significant cleaning. 5 = Yes, a well-governed and accessible data source is in place.