The Data Capital Alliance A Founding Invitation

The Data Capital Alliance

Build the economy that can afford the AI future.

Neutral infrastructure for the value of data, participation, and economic growth.

Three forces
shape the future

The Data Capital Alliance
Government Technology Finance
Scenario

Big Gov, Big Tech and Big Finance are competing for 100% of your data to create the AI economy.

Hyperscaler + NVIDIA debt issuance

Incl. SPVs, as a percent of Treasury bond issuance · Source: Bloomberg, JPMAM, Aug 31, 2026
“Big Tech is now emerging as a serious competitor to the US government in the long-term debt market, increasingly competing for the same pool of buyers just as investors are demanding more compensation to hold this debt.”

The Fed’s balance sheet turns back up

Fed total assets, millions of US dollars · Source: Federal Reserve via FRED
“Money is the only thing that moves inflation, so forget the tariff and energy noise. The Fed just restarted the one lever that does, and that liquidity floods back into stocks, gold, and hard assets while the dollar loses ground.”
The AI capex challenge

A trillion dollar buildout needs a larger economic engine.

2026 / Global AI investment
~$1.0T

AI-related investment across public and private companies around the world.Goldman Sachs Research estimate

By 2027 / Hyperscaler capex
$1.3T+

Combined capital expenditure across major hyperscalers.S&P Global Ratings projection

Sources: Goldman Sachs, 7 August 2026; S&P Global Ratings, 27 August 2026. Separate estimates with different coverage.

The economic pressure

The financing burden is growing.

Capex / Operating cash flow
93%

Estimated hyperscaler AI capex share of operating cash flow in 2026.Compared with 33% in 2023.

Tech bond issuance
$320B

2026 forecast reported by Kobeissi, including related special-purpose vehicles.An estimated 60% increase over the prior year.

Debt service and reinvestment need durable cash generation.

Sources: J.P. Morgan Asset Management, 15 June 2026; Kobeissi, September 2026.

Why now?

AI can borrow to build the future. It needs data to pay for it.

The IPOs finance the buildout. The buildout creates the capacity. By Q3/2027, that capacity has to start to produce economic value at scale. It will require a new business model.

$1.3T+ in hyperscaler capex by 2027. Capital markets can finance the infrastructure. They cannot manufacture the economic activity required to justify it. S&P Global’s projection also says debt, leases, guarantees, and other financing structures are becoming increasingly important. Reuters reports that by 2027 major tech companies’ capex could exceed their free cash flow, increasing pressure to demonstrate tangible returns.

The problem

The data problem is economic.

Compute without economically accessible data and economically empowered users hits a demand constraint.

Rights
Who can authorize data usage?
Incentives
Who benefits when data creates value?
Cooperation
Why participate on a competitor’s terms?

Capital builds capacity. Economic activity pays for it.

The economic task

Turn the value of data into working capital,

to expand the market that makes AI investment productive.

01

People
need a stake.

Control authorized uses and participate in the value their data helps create.

02

Companies
need control.

Put data to work while preserving customer relationships and strategic assets.

03

Governments
need sovereignty.

Enable economic participation within accountable local rules.

04

Competitors
need neutrality.

Participate under common terms that no single rival can change alone.

This is the shift from monetizing applications to monetizing data.

From data to
capital

The benchmark

Credit card networks solved a similar problem.

Competitors can build a market together, but only when none of them owns the market.

1958

One bank

Bank of America launches BankAmericard in Fresno, CA.

1976

Neutral rules

Bank of America gave up control of its card network so competing banks could participate on equal terms.

BankAmericard program officially rebranded and became known as Visa.

Network effects

Neutrality wasn’t a nice-to-have. It was the precondition for cooperation at scale.

Visa

Global market

The breakthrough wasn’t the credit card. It was neutral infrastructure competitors could trust.

Because the network belonged to no one, it could belong to everyone. Participation stops being a risk and becomes an advantage.

The case for neutrality

Neutrality changes the AI economics of competition.

Credit cards turned future income into present purchasing power. The AI flywheel needs a mechanism that turns data value into purchasing power for companies and consumers.

01

More
participation

Reduce the strategic cost of joining, so more organizations and people can take part.

02

Lower
transaction costs

Use common terms and standards to reduce repeated negotiation and integration work.

03

More useful
services

Enable authorized relationships across data sources that were previously disconnected.

04

Broader
economic returns

Give contributors and operators defined ways to benefit from productive uses.

Align power,
accelerate innovation.

Shape what comes next.