Is your business ready for AI agents?

Claude Code, Cursor, Gemini, Codex, and AI-native builders are changing who can create with data. The opportunity is enormous. So is the coordination problem. The benchmark maps whether organizations have the visible data foundation, agentic build layer, governance, and ownership to turn distributed experiments into trusted workflows.

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Organizations leading the shift

#CompanyScoreReadinessGradeArchetype
1
JPMorganChase logo
JPMorganChase
jpmorganchase.com
90
AScaled Agentic Operators
2
NVIDIA logo
NVIDIA
nvidia.com
89
AScaled Agentic Operators
3
PwC logo
PwC
pwc.com
86
AScaled Agentic Operators
4
Salesforce logo
Salesforce
salesforce.com
86
AScaled Agentic Operators
5
Visa logo
Visa
visa.com
86
AFocused AI Builders
6
Capgemini logo
Capgemini
capgemini.com
85
AScaled Agentic Operators
7
BCG X logo
BCG X
bcg.com
84
AFocused AI Builders
8
Deloitte logo
Deloitte
deloitte.com
84
AScaled Agentic Operators
9
S&P Global logo
S&P Global
spglobal.com
84
AScaled Agentic Operators
10
Datasource Consulting, an EXL company logo
Datasource Consulting, an EXL company
exlservice.com
84
AFocused AI Builders
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Methodology

Six pillars of governed agentic scale

The benchmark measures the visible conditions required to turn AI experimentation into durable organizational capability — not just access to a model.

01
Data foundation & retrieval
02
AI-native / agentic build capacity
03
Stack balance / tool mix quality
04
Eval, observability & governance
05
AI hiring investment & momentum
06
Talent & leadership
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See where your organization sits on the agentic data journey