Why the Storage Layer Shapes the ROI
Every AI use case comes down to two questions: What does it cost to run, and how good is the answer? The price of a single token — the basic unit of AI cost — keeps falling, yet the number of tokens an enterprise generates is climbing far faster as models reason more and agents multiply the work. So the bill keeps growing even as the unit price drops. This paradox is the tokenomics challenge driving today’s ROI pressure.
Most teams look for the fix in silicon and power. However, storage is the quieter variable as it shapes both sides of the bill: the fixed cost of training a model and the variable cost of serving every token. Just as the chip became a headline design decision, the drive that houses the data deserves the same standing. In effect, AI has elevated storage from infrastructure to architecture.
This brief traces the economics from the token down to the drive, and shows why high-capacity, high-performance NVMe SSDs are the variable the whole equation turns on. It also examines Solidigm’s enterprise SSD portfolio and how it aligns with these requirements.
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TABLE OF CONTENTS
Summary
The Question Every IT Leader is Now Being Asked
The Tokenomics Paradox: Cheaper Tokens, Bigger Bills
Why Activating AI Is Hard: Performance, Cost, and Power
The Overlooked Layer: Storage in the AI Equation
From Box to Design Point: Media as an Architecture Decision
Where Solidigm Fits
Call to Action
COMPANIES CITED
Solidigm
Google
McKinsey & Company
Moor Insights & Strategy
ORGANIZATIONS & PROJECTS MENTIONED
MIT / Project NANDA
Stanford University / Stanford AI Index
PJM Interconnection
LMCache project
