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R0007/2026-03-20/C009 — Assessment

BLUF

The core observation is confirmed: no major enterprise survey identifies capability-based stratification in AI deployment. However, the McKinsey sample size is incorrect: their surveys used n=1,363 (early 2024), n=1,491 (mid-2024), or n=1,993 (2025) — none match n=1,933. BCG n=10,600 and Deloitte n=3,235 are confirmed.

Probability

Rating: Likely (55-80%) Confidence in assessment: Medium Confidence rationale: Based on web-accessible evidence.

Reasoning Chain

  1. McKinsey AI surveys: n=1,363 (Feb-Mar 2024), n=1,491 (Jul 2024), n=1,993 (Jun-Jul 2025). None match n=1,933. BCG AI at Work 2025: n=10,635 confirmed. Deloitte State of AI 2025: n=3,235 confirmed. None of these surveys stratify by individual capability level. [SRC01-E01, High reliability, High relevance]

Evidence Base Summary

Source Description Reliability Relevance Key Finding
SRC01 McKinsey State of AI Survey High High See BLUF

Collection Synthesis

Dimension Assessment
Evidence quality Medium to Robust
Source agreement High
Source independence Assessed per claim
Outliers None

Detail

McKinsey AI surveys: n=1,363 (Feb-Mar 2024), n=1,491 (Jul 2024), n=1,993 (Jun-Jul 2025). None match n=1,933. BCG AI at Work 2025: n=10,635 confirmed. Deloitte State of AI 2025: n=3,235 confirmed. None of these surveys stratify by individual capability level.

Gaps

Missing Evidence Impact on Assessment
Full-text access Low to Moderate

Researcher Bias Check

Declared biases: None. Influence assessment: Standard verification.

Cross-References

Entity ID File
Hypotheses H1, H2, H3 hypotheses/
Sources SRC01 sources/
ACH Matrix ach-matrix.md
Self-Audit self-audit.md