Assessment Methodology

A rigorous, research-backed framework for evaluating AI readiness across 6 weighted dimensions.

The Scoring Formula

Your overall AI Readiness Score is a weighted average of 6 category scores, each on a 0-100 scale:

Overall Score = (Data Maturity × 25%) + (Team & Skills × 20%) + (Strategy & Budget × 20%) + (Infrastructure × 15%) + (Use Case Clarity × 10%) + (Change Readiness × 10%)

Score Levels

AI Beginner
0-30
AI Explorer
31-50
AI Ready
51-70
AI Advanced
71-85
AI Leader
86-100

The 6 Assessment Dimensions

25%

Data Maturity

How you collect, store, structure, and access data. Data is the raw material for all AI. Poor data = poor AI, no matter how good the algorithms.

Factors evaluated:
  • Data collection and storage systems
  • Overall data quality rating
  • Data structure and labeling completeness
  • Real-time data accessibility
  • Historical data volume
15%

Infrastructure

Your technical foundation — cloud readiness, system integrations, and IT capacity. AI requires scalable compute and well-connected systems.

Factors evaluated:
  • Tech stack composition
  • API/integration maturity
  • IT team capacity
  • Cloud readiness level
20%

Team & Skills

The human side of AI. Technical talent, data literacy across the organization, training programs, and leadership understanding all directly affect outcomes.

Factors evaluated:
  • Data science/ML talent on staff
  • Organization-wide data literacy
  • AI training programs
  • Leadership AI understanding
  • Team openness to AI
20%

Strategy & Budget

AI without strategy burns budget. We evaluate whether AI is part of your formal planning, whether leadership is aligned, and whether budget is allocated.

Factors evaluated:
  • Documented AI strategy
  • Budget allocated for AI (next 12 months)
  • Implementation timeline
  • Executive sponsorship level
10%

Use Case Clarity

Knowing what you want to achieve with AI dramatically increases success rates. We assess goal clarity, use case specificity, and process pain points.

Factors evaluated:
  • Primary goal definition
  • Specific use case identification
  • Manual process documentation
10%

Change Readiness

Organizations that resist change fail at AI. We measure how your culture handles change, risk tolerance, and willingness to invest in training.

Factors evaluated:
  • Organizational change handling
  • Data privacy/compliance posture
  • Risk tolerance for new technology
  • Training investment willingness