Useful capacity must reach customers.
Desired demand, announced projects, equipment deliveries, and energized capacity are different stages. We follow the path to usable power and avoid counting the same capacity twice.
AI supply chain · Independent research
The infrastructure
behind intelligence.
Understanding the businesses building the AI supply chain—and what their success could mean for investors.
Explore our approach & assumptions ↓
Research by JackAI supply chain & company analysis
The questions
that guide the work
01 / STRATEGY
What could become possible?
Start with a compelling ambition and the problem it solves.
02 / EXECUTION
Who can make it happen?
Examine capability, competitive advantage, and the capital required.
03 / VALUE
What reaches shareholders?
Connect business outcomes to value per share, with assumptions in view.
Our approach & assumptions
A bigger market is the beginning of the investment question.
We look for compelling company strategies, then test the evidence that they can succeed. Our research connects the physical buildout of AI infrastructure to the cash that can reach shareholders.
The starting premise
Rapid AI progress.
Lasting infrastructure demand.
Our research assumes major improvements in AI capabilities during 2027 and 2028, supporting a prolonged expansion in compute and power demand. The possibility of recursive self-improvement—AI improving its own capabilities—and artificial superintelligence motivates that backdrop.
These are explicit scenario assumptions. The company research tests what they could mean for businesses and shareholders; it does not establish when those AI milestones will occur.
Growth can continue well beyond 2031. Successful suppliers may remain growth businesses, investing heavily to meet a much larger market.
Supply can improve too. Better engineering and faster construction may expand capacity, while competition and customer bargaining reshape margins. We test who can retain value as the industry changes.
What must connect demand to value
The assumptions behind every company case.
Growth has to earn its capital.
Factories, working capital, maintenance, and service obligations all cost money. Weak near-term cash flow can reflect productive expansion; the question is what that investment earns over time.
Urgent customers can help fund supply.
Deposits, reservations, long-term contracts, and project participation can accelerate the buildout. We account for the concessions and ownership claims that accompany that support.
The outcome must work per share.
Debt, partners, leases, recurring equity awards, and new financing affect what shareholders retain. We model those claims alongside operating success.
A thesis you can examine.
Company evidence, operating models, financing requirements, and valuation sensitivities sit behind the conclusions. We distinguish reported facts, management objectives, and our own assumptions so readers can see what a thesis depends on.
Our central cases describe successful execution under sustained rapid AI demand. Company disappointment, competition, and financing constraints are tested within that same backdrop.
Inside the library
From the conclusion to the evidence.
Start with the investment conclusions. Go deeper into company strategies, financial models, price targets, and the sources behind them.