Data and Methodology
AIDE's methodology measures AI-Driven Enterprise progress using publicly available evidence, consistently applied.
Evidence-Based, Not Self-Reported
We rely on hard data, eliminating the strategic bias of traditional surveys.
Massive Scale
Analyzing a broad set of public data points across the S & P 500 cohort.
Hybrid Intelligence
Combining deterministic rule-based algorithms with nuanced LLM-augmented context analysis.
Where We Pull From
Our intelligence sources span the entire public digital footprint of global enterprises.
AIDE Index
Literacy
Dimension
Board Members and Top Management Experiences, skills, formation related to AI
Data Sources
AIDE Index
Advocacy
Dimension
Board Members and Top Management message on AI
Data Sources
AIDE Index
Orientation
Dimension
Company Strategy, Partnerships & Acquisitions, Workforce, Organization Structure
Data Sources
AIDE Index
Implementation
Dimension
AI product features, AI in operations, and AI deployment evidences
Data Sources
AIDE Index
Literacy
AIDE Index
Advocacy
AIDE Index
Orientation
AIDE Index
Implementation
Dimension
Board Members and Top Management Experiences, skills, formation related to AI
Board Members and Top Management message on AI
Company Strategy, Partnerships & Acquisitions, Workforce, Organization Structure
AI product features, AI in operations, and AI deployment evidences
Data Sources
Public evidence, consistently applied.
The public AIDE Index is built from publicly available evidence using consistent collection and scoring procedures across the S&P 500 cohort. Company-provided information is not used to influence public AIDE Index scores.
"The question for senior leaders isn't whether to invest in AI, it's where and how fast. Research like this, grounded in observable data across rather than self-reported surveys, gives executives a credible starting point for those decisions."
Ned Calder, Managing Director, Strategy and Innovation, Innosight