AI Readiness Assessment

AI Readiness Assessment Skill

Conduct a structured, evidence-based evaluation of a business's readiness for AI adoption across six dimensions, then produce a detailed ai-readiness-report.md covering scores, gap analysis, and prioritized next steps. Aligned with OneWave AI's pragmatic, ROI-driven audit methodology.

Contents

• references/dimensions.md — The six dimensions, full 1-5 scoring rubric, and key questions per dimension.
• references/methodology.md — Information-gathering, scoring math and interpretation table, gap analysis, recommendation priorities, company-size and industry tailoring, and conversation flow.
• references/output-template.md — The complete ai-readiness-report.md structure to fill in.

Workflow

• Gather context. Collect information through conversation, document review, and codebase analysis. See references/methodology.md (Phase 1) for channels and the question set in references/dimensions.md.
• Score the six dimensions. Rate each from 1 to 5 against the rubric in references/dimensions.md. Be honest and conservative, use half-points for nuance, and record the evidence behind every score.
• Calculate the overall score. Apply the weighted formula and map it to a readiness level using the table in references/methodology.md (Phase 2).
• Run the gap analysis. For each dimension below 4.0, document current state, target state, the gap, its impact, and the effort to close it (Phase 3).
• Build recommendations. Produce prioritized actions across the five OneWave priority tiers, tailoring for company size and industry (Phase 4 and tailoring section).
• Generate the report. Write ai-readiness-report.md following references/output-template.md, then highlight the top 3 immediate actions.

The Six Dimensions

| Dimension | Weight |

|-----------|--------|

| Data Maturity | 25% |

| Technology Stack | 20% |

| Team Skills and Capacity | 20% |

| Process Documentation | 15% |

| Budget and Resources | 10% |

| Organizational Culture | 10% |

See references/dimensions.md for the full rubric and questions.

Core Rules

• Never inflate scores. A business that scores 2.0 needs to hear that honestly; false optimism wastes money and time.
• Always provide evidence. Back every score with specific observations, not assumptions.
• Be actionable. Pair every identified gap with a concrete recommendation.
• Respect budget realities. Include cost-appropriate options; not every organization needs enterprise-grade solutions.
• Use no jargon without explanation. The report is read by business leaders, not only technologists.
• Flag deal-breakers. When a dimension scores 1.0, state explicitly that AI initiatives should not begin until it is addressed.
• Consider the full cost. Include ongoing costs (maintenance, retraining, monitoring), not just implementation.
• Recommend the right AI. Match recommendations to actual readiness; do not recommend deep learning to a company that has not consolidated its data.
• Maintain OneWave AI alignment. Frame all recommendations within pragmatic, ROI-driven AI adoption. Avoid hype; focus on business value.

10. Use no emojis. Keep all output professional and text-based.