AI Readiness Index Methodology
Building the global benchmark of AI progress
The study draws insights from senior business and technology leaders around the world who are driving Al for their organizations and industries.
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senior leaders surveyed
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markets represented
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industries included
To help ensure unbiased responses, an independent research partner conducted the survey double-blind: respondents didn't know Cisco commissioned it, and we don't know who participated.
How we measure AI readiness
We assess organizations using six pillars, measured across 49 distinct indicators. We weight each pillar based on its relative importance to achieving overall AI readiness.
The math behind the score
From individual indicators to the final readiness score, here's how we translate data into a benchmark of AI readiness.
Step 1:
Indicator scoring
We measured organizations against 49 indicators, calculating a score for each
indicator based on their level of deployment:
Full Deployment:
100%
Partial Deployment:
25-50%
No Deployment:
0%
Step 2:
Pillar scoring
We combined indicator scores to create a readiness score for each pillar, and
overall:
- Strategy
- Infrastructure
- Data
- Governance
- Talent
- Culture
Step 3:
Final readiness score
We segmented each organization’s AI readiness score into one of four levels at the
pillar level, and overall stages:
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Pacesetters (Score ≥ 86):Fully Prepared
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Chasers (Score 61-85):Moderately Prepared
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Followers (Score 31-60):Limited Preparedness
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Laggards (Score 0-30):Unprepared
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