Japan Quant Strategy: Finding new candidates after AI supplier correction: Exploratory study of AI adopters based on text analysis

Research evidence excerpt

Japan Quant Strategy: Finding new candidates after AI supplier correction: Exploratory study of AI adopters based on text analysis

Masanari Takada AC Global Markets Strategy

(81-3) 6736-8636 10 July 2026 J P M O R G A N

masanari.takada@jpmorgan.com

Figure 4: Correspondence between analysis identification labels and AI adopter categories

Based on the definition of AI adopters, supplementary groups were established for the screening process in addition to the

identification labels

Classification US Graph Label Japan Graph Label Supplement

Productivity AI ADOPTER COST JP AI ADOPTER COST Improve operational efficiency, reduce

improvement type PRODUCTIVITY PRODUCTIVITY manpower, and reduce costs through AI

Strengthening of AI

AI ADOPTER DEMAND JP AI ADOPTER Implementation of AI in products and

functions for

PRODUCT DEMAND PRODUCT services for customers

customers

Demand-cycle/data- DURABLE AI ADOPTER JP HIGH CONVICTION Relatively strong evidence of demand

cycle type DEMAND II DEMAND II CANDIDATE virtuous cycle structure and AI connection

Core candidates for The US is a proxy, and Japan is a strict

JP CORE TRUE

demand-cycle/data Core / True Flywheel proxy classification. Considered direct

FLYWHEEL CANDIDATE

cycle comparisons

Unique to Japan. Primary screening

Primary candidate JP AI DEMAND II

None population before demand-cycle/data-cycle

population SCREEN POOL

classification

Unique to Japan Evidence of a virtuous

Potential candidates JP DEMAND CREATION

None demand cycle structure has not been

for text TEXTUAL WATCHLIST

verified

AI supply side / Tool AI SUPPLIER OR The side that sells and supports AI, not the

Supplier / provider review

provision TOOLING side that uses AI

Data/base DATA PLATFORM Not an AI adopter, but rather something

Asset / data review