Pennings, A.J. (2026, Sep 22) The New ICT4D: AI, Stablecoins, and the Infrastructure of Global E-Commerce. apennings.com https://apennings.com/global-e-commerce/the-new-ict4d-ai-stablecoins-and-the-infrastructure-of-global-e-commerce-and-financial-liquidity/

Introduction

The emergence of US Treasury-backed stablecoins potentially connects dollar liquidity, e-commerce, cloud computing, artificial intelligence, and telecommunications into a common infrastructure. They could create an important new layer in the digital economies of developing countries and become a central focus of ICT4D. Their significance is not simply that they provide another form of digital money, but that USD liquidity infrastructure expands into Tier 3 and 4 economies that have traditionally experienced volatile liquidity and restricted access to global USD.[1]

The GENIUS Act, signed into law in July 2025, established a US regulatory framework for payment stablecoins backed one-to-one by permitted reserve assets, especially short-term Treasury securities. The US Treasury has explicitly described stablecoins as an “Internet-native payment rail” that can expand access to the dollar economy worldwide and increase demand for Treasuries.

For developing economies, this creates a potentially important connection between financial inclusion and participation in the AI economy. A software developer, small business, freelancer, or digital entrepreneur may increasingly be able to receive international payments, purchase cloud services, pay for AI APIs, and participate in global e-commerce through digital dollar infrastructure without relying entirely on traditional correspondent-banking arrangements.

The implications become clearer when you consider financial and computational infrastructure together. AI requires data, broadband, storage, cloud computing, electricity, models, APIs, and technical expertise. Stablecoins cannot provide those resources directly, but they can potentially make it easier to pay for them across borders. The emerging architecture therefore looks increasingly like broadband -> data -> cloud -> AI -> stablecoin -> e-commerce -> economic activity.

This could be particularly important for countries with limited domestic AI infrastructure. Rather than attempting to reproduce the entire frontier AI stack, local firms combine local knowledge, data, labor, and entrepreneurship with externally supplied computation and globally accessible dollar liquidity. A local agricultural enterprise, for example, might develop an AI service using domestic data, purchase cloud and model services internationally, and sell its products to customers at home or abroad.

Such an arrangement could extend the traditional ICT4D idea of technological leapfrogging. Mobile money demonstrated that countries could develop new financial capabilities without reproducing the entire banking infrastructure of wealthy economies. Stablecoins potentially add an international dollar layer to that process, connecting local businesses more directly to global digital markets.

But the same infrastructure that expands access can also create new dependencies. If a country’s models, cloud providers, payment rails, stablecoin issuers, and data infrastructure are primarily controlled abroad, digital participation may increase without a corresponding increase in local technological sovereignty. Treasury’s own analysis notes that the expansion of dollar-backed stablecoins could draw some liquidity currently held in non-dollar forms toward the dollar. Stablecoins could therefore simultaneously promote financial inclusion, expand e-commerce, and deepen dollarization.

This tension makes ICT4D education more important, not less. The TSM graduate with this specialization needs to understand the complete computational and financial system through which digital economic activity increasingly occurs. That means learning how data is captured and represented, where it is stored, how networks move it, how AI retrieves and processes it, how APIs and tools connect AI models to organizations, how agents coordinate computational tasks, and how outputs become economic actions. At the same time, students need to understand how digital transactions are financed, settled, and connected to global markets.

This creates a new conception of digital literacy. It is no longer sufficient to teach students how to use AI applications. Students need to understand the infrastructure surrounding AI and the economic systems that make that infrastructure accessible.

This matters because the AI divide is not simply a divide in access to models. It is a divide in data, compute, connectivity, skills, institutional capacity, and financial resources. Research on AI for development increasingly emphasizes that AI4D is contested precisely because technological access can reproduce existing economic and geopolitical inequalities rather than automatically overcoming them. Toupin and Siad identify developmentalist, economic, international-policy, colonial/extractivist, and decolonial perspectives within the AI4D literature, emphasizing the importance of autonomy and local control. And not just in Africa, all areas of the globe are pursuing sustainable and smart development.

ICT4D therefore has a new educational mission. Students need to learn how to use global infrastructure without becoming merely consumers of foreign computational services. They need to determine what to develop locally, what to share regionally, and what to obtain efficiently from global providers. They need to understand the tradeoffs between access, cost, sovereignty, resilience, security, and development.[2]

The TSM graduate with a specialization in ICT4D becomes a manager of networked computational and financial systems. Their task is not necessarily to build the frontier model or the blockchain. It is to understand how data, telecommunications, AI, digital finance, people, and organizational resources can be assembled into productive systems.

The central ICT4D question consequently changes. It is no longer how do we give developing countries access to AI? It asks, “How do we build the human and institutional capacity to turn global computational and financial connectivity into local productive capacity?”

That distinction may determine whether Treasury-backed stablecoins and AI become another channel for extracting value from developing economies or a new monetary infrastructure through which local firms, workers, governments, and entrepreneurs can participate more effectively in the global digital economy.

ICT4D is therefore moving toward a new intersection of AI infrastructure, telecommunications, digital finance, and e-commerce. Training people to understand that intersection may be as important as providing them with access to the technologies themselves.

References

International Telecommunication Union. (2026). AI for Good Impact Report. ITU.
Toupin, S., & Siad, R. (2025). Artificial intelligence for development (AI4D): A Contested Notion. Big Data & Society, 12(2). https://doi.org/10.1177/20539517241304678.
U.S. Department of the Treasury. (2025, July 18). Statement from U.S. Secretary of the Treasury Scott Bessent on enactment of the GENIUS Act.
U.S. Department of the Treasury. (2025). Report to the Secretary of the Treasury from the Treasury Borrowing Advisory Committee.
U.S. Department of the Treasury. (2026). Stablecoin footprint increasing. Treasury Borrowing Advisory Committee.
World Bank. (2023). Digital Economy for Africa (DE4A). World Bank.

Notes

[1] I’ve been developing a framework for understanding the current global system in terms of USD liquidity. Different countries have different relationships to the USD. The US creates US dollars but other countries lend out USD as eurodollars. Tier 3 countries, mainly BRICS, collect a lot of USD through their export prowess. Tier 4 and 5 have more difficulties obtaining USD cheaply.
[2] As the undergraduate program director for a degree in Technological Systems Management with an option to specialize in ICT4D we are looking closely at the transition to AI.

© ALL RIGHTS RESERVED

Not to be considered financial advice. AI is often used, and results are thoroughly interrogated. Links are used for some citations. Views are my own and do not express the stances of my employers, past or present.

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Anthony J. Pennings, PhD is a Professor at the Department of Technology and Society, State University of New York, Korea and a Research Professor for Stony Brook University. He teaches AI and broadband policy. From 2002-2012 he taught digital economics and information systems management at New York University. He also taught in the Digital Media MBA at St. Edwards University in Austin, Texas, where he lives when not in Korea.

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Category: artificial intelligence, global e-commerce, mobile technologies, space systems, sustainable development

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