Our Methodology
Prism evaluates AI readiness using a rigorous, research-backed framework built on analyst data from Gartner, McKinsey, and Forrester. Every question and benchmark is grounded in empirical evidence about what distinguishes AI-mature organizations from those still in early stages.
7 Assessment Dimensions
Each dimension targets a distinct capability domain that research consistently identifies as a predictor of successful AI adoption.
Strategy
Executive mandate, dedicated budget, and business-outcome-driven AI investments.
Data
Centralized, governed, accessible data foundation ready to power AI at scale.
Talent & Culture
Dedicated AI talent, executive AI literacy, and organizational change readiness.
Governance & Risk
Responsible AI policies, regulatory compliance, and model validation processes.
Infrastructure & Operations
Cloud-ready infrastructure, MLOps maturity, and measurable technology ROI.
Scoring Methodology
1–5
Likert Scale
Every question uses a calibrated 1–5 response scale anchored to observable organizational behaviors, not subjective opinion.
21
Questions
Three questions per dimension, each selected to maximize signal while minimizing respondent burden. Completes in about 8 minutes.
7
Dimensions
Scores are weighted and normalized per dimension, then aggregated into an overall readiness percentage with benchmark comparison.
How scores are calculated
Raw responses (1–5) are normalized to a 0–100 percentage scale per question. Category scores are the mean of their three question scores. The overall score is the equally-weighted average of all 7 category scores. Scores are then contextualized against industry benchmarks to produce tier classifications:
75% and above
50%–74%
Below 50%
Industry Benchmarks
All benchmark figures are derived from published research by Gartner, McKinsey Global Institute, and Forrester Research, reflecting data collected from thousands of enterprise organizations across industries.
| Category | Industry Avg | Top Quartile |
|---|---|---|
| Strategy | 45% | 78% |
| Data | 40% | 72% |
| Talent & Culture | 35% | 68% |
| Governance & Risk | 32% | 65% |
| Infrastructure & Operations | 42% | 75% |