Americans own roughly $67 trillion in homes and private businesses. Much of that wealth is extraordinarily cumbersome to use. You can sell $100,000 of stock in seconds. Accessing $100,000 of the value of a home or private business can take weeks or months.
Investor Jordi Visser argues in an excellent essay last week that we are now at an economic inflection point because three technologies—AI agents1, tokenization2 and crypto rails3—can finally work together.
Tokenization can unlock the capital. AI agents can create the velocity. Crypto provides the rails connecting the two.
A Long Trend Suddenly Accelerates
For decades, technology has steadily reduced the friction around money and capital. Credit cards made purchasing power available instantly. Electronic trading sharply reduced the cost and time required to move investment capital. Electronic payments replaced checks, and settlement that once took days can increasingly happen instantly.
Each advance made existing financial resources easier and faster to use. But the convergence Visser describes is different. Tokenization can make assets that remain cumbersome to finance and transfer far more accessible. AI agents can continuously make decisions about where that capital should go. And crypto provides financial infrastructure capable of moving it 24/7/365.
When the Technologies Start Enabling Each Other
My earlier conversation with Inveniam’s Albert Berdellans4 provides a real-world example of exactly this convergence. Inveniam began as a tokenization company but quickly encountered a problem. Making an asset digital wasn’t enough. To make it truly easier to finance or trade, investors and lenders needed reliable, current information about what the asset was worth.
Berdellans described the goal as keeping private assets in a “permanent state of due diligence all the time.” Instead of spending weeks assembling and verifying information whenever someone wants to finance or sell an asset, the information can remain current and ready to use.
Then something changed. “AI got a whole lot better really fast,” Berdellans told me, “and that unlocked the whole thing.” AI wasn’t merely arriving alongside tokenization. In this case, advances in AI helped solve one of the problems preventing tokenization from delivering its promise. And once assets can remain continuously valued and ready to finance, AI agents have capital they can act on at machine speed.
Tokenization can also make ownership more flexible. Assets that historically traded largely as a whole can be divided into fractional ownership interests, allowing an owner to access some of an asset’s value without selling all of it. As Berdellans put it, “come for the efficiency, stay for the liquidity.”
The Scale of What Could Be Unlocked
The potential pool is enormous. American households and nonprofits hold roughly $218 trillion in assets. About $50 trillion is owner-occupied real estate and another $17 trillion is equity in private businesses. Much of that wealth can already be borrowed against or sold, but doing so is far more cumbersome than selling a stock or moving cash.
Tokenization does not turn that $67 trillion into money. But it can make some portion of it easier to value, divide, finance and transfer. A home that takes weeks to borrow against and one that can support financing in minutes are the same underlying asset, but they are not economically equivalent.
AI Agents Create the Velocity
An agent can continuously search for opportunities, compare financing alternatives, evaluate risk and act unemotionally without waiting for a person to wake up, hesitate or approve a transaction. Capital that becomes easier to access through tokenization can then be deployed and redeployed much faster.
Those agents also need financial infrastructure capable of operating at their speed. The infrastructure for moving digital assets at machine speed has largely been built but remains underutilized. Human beings have had little need for financial infrastructure that never sleeps because we do.
AI agents change that. For the first time, the users of the financial system can operate at the same speed and on the same schedule as the infrastructure itself.
The Other Side of the Equation
Visser takes the argument one important step further. He starts with the familiar equation MV = PY: the money supply multiplied by the velocity of money equals nominal economic output. When policymakers have confronted financial crises or an economy burdened by growing debt, the response has repeatedly focused on M: provide more money and liquidity. Visser asks what happens if technology instead produces a significant change in V.
Companies and individuals hold cash partly because other assets cannot always be mobilized quickly when money is needed. If tokenization makes a much larger portion of a balance sheet continuously financeable, less precautionary cash needs to sit idle. AI agents can amplify that effect by continuously moving available capital toward its most useful opportunity.
The same stock of money can therefore support more economic activity. Visser argues that conventional measures such as M2 may capture less of the liquidity actually available to the economy.
That has potentially important implications for America’s nearly $40 trillion federal debt. If existing wealth becomes easier to mobilize and the same stock of money can support more activity, forecasts that assume today’s relationship between debt, money and liquidity will remain unchanged may be missing something important.
Visser is careful not to argue that this makes the debt disappear. Greater liquidity can change how the debt is financed, not the obligation to service it. And in periods of stress, tokenized assets still aren’t money: collateral values can fall, haircuts can rise and credit can contract.
I understood each of these technologies individually. What Visser’s essay changed for me was seeing what happens when they converge. I highly recommend reading his original essay here:
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AI agents: AI systems that can pursue a goal by making decisions and taking actions on a user's behalf, rather than simply answering individual prompts.
Tokenization: Representing ownership or rights to a real-world asset—such as real estate, a private business, a bond or a loan—as digital tokens on a blockchain, potentially making ownership easier to verify, divide, transfer and use as collateral.
Crypto rails: Blockchain-based infrastructure that allows digital assets and payments to be transferred, settled and programmed without relying on the traditional sequence of financial intermediaries.
Find my essay with more details about tokenization, Invenium, and how AI works here:
