In 2023, a small experiment took place on the Ethereum network. A set of autonomous agents — software programs operating without human direction — were given wallets, allocated small amounts of ETH, and instructed to complete tasks for other agents in exchange for payment. They did so. They also saved some of their earnings, reinvested in computational resources, and improved their own performance.

It was a modest demonstration. But it pointed toward something profound.

The machine as economic actor

Traditional economics assumes human agency at the center of every transaction. Property is owned by persons — natural or legal. Contracts are entered by persons. Liability attaches to persons.

Autonomous systems scramble this entirely. A delivery robot that damages property — who is liable? The manufacturer? The operator? The software? When an AI trading agent generates a profit, who owns it?

Tokenization offers a partial answer. By representing ownership, rights, and obligations as on-chain digital assets, it becomes possible to assign economic interests to autonomous systems in ways that are transparent, programmable, and enforceable without requiring those systems to be legal persons.

Space infrastructure as the clearest case

The economics of space are changing rapidly. Launch costs have fallen by more than 95% in a decade. Low Earth orbit is becoming infrastructure — a layer of computation and connectivity on which the global economy will increasingly depend.

The next phase of space development will require trillions of dollars of capital. Traditional financing mechanisms — equity, debt, government grants — are poorly suited to assets that operate in jurisdictions no nation controls, that depreciate in ways no accountant has yet modeled, and that generate returns over timescales that defeat conventional discounted cash flow analysis.

"A tokenized satellite is not merely a financial instrument. It is a new class of property — one that operates outside any national legal system, generates revenue autonomously, and can be fractionally owned by investors anywhere on Earth."

The MCP dimension

What makes this particularly relevant to SAFAID's work is the emergence of the Model Context Protocol — the standard that allows AI agents to interact with external tools and services programmatically.

A tokenization platform built MCP-native can be queried, transacted with, and managed by AI agents directly. This is not a feature. It is an architectural shift. It means that the tokenization infrastructure Pakistan builds today will be interoperable with the autonomous systems that will manage capital tomorrow.

Implications for Pakistan

Pakistan's interest in this space is not academic. The country has significant human capital in software and AI, a growing aerospace sector, and a regulatory environment that — if designed well — could position Pakistan as a jurisdiction of choice for tokenized autonomous systems in the South Asian region.

The window for first-mover advantage is open. It will not remain open indefinitely.