Pennings, A.J. (2026, Aug 26) A $100 Trillion USD Climate and Energy Program for the AI Era. apennings.com https://apennings.com/global-communications/a-100-trillion-usd-climate-and-energy-program-for-the-ai-era/

Introduction

This post uses a provocative meme/trope of US debt reaching “$100 trillion” over the next decade. As we know, it has already reached $40 trillion and shows no serious signs of stopping. Two other issues require immediate attention. One is the climate change dangers we are facing daily, and other is the impending challenges of employment in an AI age. This post suggests that while extremely difficult, these challenges can be adequately addressed through positive economic policy prescriptions and political mobilization.[1]

The central economic question of the AI era may not be whether governments can create enough money. It may be whether humanity can identify enough productive things to do with it. That distinction matters. A future in which AI dramatically increases computational productivity while reducing demand for large categories of cognitive and administrative labor could produce enormous productive capacity alongside weakened employment and purchasing power.

The conventional response, more consumption, transfers, or financial assets, may support demand, but it does not necessarily create the physical capabilities required by an increasingly digital, but materially dependent civilization.

A large-scale climate and energy investment program offers a different possibility. It would direct monetary capacity toward electricity generation, transmission grids, storage, nuclear power, resilient buildings, transportation, water systems, advanced manufacturing, semiconductor fabrication infrastructure, climate adaptation, and the enormous physical infrastructure required to support an AI-intensive economy.

These are activities in which software can substantially augment human labor but cannot, yet, simply replace the electricians, construction workers, engineers, machinists, technicians, inspectors, operators, and maintenance workers required to build and operate physical systems. The robots are coming, but they will need to be integrated effectively.

The International Energy Agency’s latest employment research confirms this distinction. Applied technical occupations account for more than half of the energy workforce, while AI is currently contributing primarily to administrative efficiency, design, and system performance rather than eliminating demand for construction, operations, and maintenance workers.

This creates an unusual convergence between climate policy, industrial policy, employment policy, and AI policy. The same investment can reduce carbon and disaster risks, expand productive capacity, create skilled employment, strengthen energy security, and provide the electricity required for data centers, telecommunications, manufacturing, transportation, and increasingly automated economies.

MMT Provides the Fiscal Permission

Modern Monetary Theory (MMT) provides one way of thinking about the monetary side of this proposition. The important insight is not that governments possess an unlimited supply of real resources. They do not. Governments can create financial liabilities in their own currency, but they cannot create unlimited electricians, copper, transformers, land, energy, semiconductor capacity, or construction crews simply by issuing money. The relevant constraint is therefore real-resource capacity rather than an arbitrary financial ceiling.

That distinction is particularly important for the idea of a $100 trillion global climate and energy program. The question should not be, “Can the United States afford $100 trillion?” in the household-budget sense. Nor should the answer be that $100 trillion can simply be created without consequences.

The meaningful questions are: Where will the resources come from? What productive capacity will the spending create? How quickly can economies absorb it? Where are the bottlenecks? And when does additional financial demand begin competing for scarce resources rather than mobilizing unused capacity?

In that sense, MMT supplies a permission structure for thinking beyond conventional fiscal scarcity, but it does not eliminate scarcity. A $100 trillion program would have to be designed as a massive exercise in resource allocation, sequencing, capacity expansion, and inflation management.

From Monetary Capacity to Physical Capacity

A Treasury-backed stablecoin is not itself new productive capacity. It is a digital representation of dollar-denominated purchasing power. Under the GENIUS Act, payment stablecoins must be backed 1:1 by permitted reserves, including short-term Treasury securities and other specified liquid assets. The law therefore establishes a regulatory architecture in which growing stablecoin circulation can generate additional demand for short-maturity US government securities.

The Treasury Borrowing Advisory Committee has explicitly identified increased stablecoin issuance as a potential new source of demand for Treasury bills, while also noting that some of that demand could substitute for existing demand for deposits or money-market instruments.

Treasury Secretary Scott Bessent has described the international policy implications even more explicitly when he suggested that stablecoins can expand access to the dollar economy globally while generating additional demand for Treasuries. This is particularly useful for the periphery tiers that have trouble getting good terms for USD liquidity.

This creates a critical distinction. Producing $100 trillion of digital dollar liquidity is not the same thing as producing $100 trillion of new wealth. The stablecoin provides the monetary rail. The real economy must determine what that liquidity mobilizes. This is why the second question, what should humanity spend the money on? is actually more important than the first.

The World Already Has a Dollar Liquidity Problem

The need for additional dollar liquidity is not hypothetical. The international financial system already contains enormous quantities of dollar-denominated obligations outside the United States. The BIS reported that outstanding USD foreign-currency credit reached approximately $14.7 trillion at the end of March 2026, with roughly 30% owed by emerging-market and developing-economy borrowers. Dollar credit to Emerging Markets and Developing Economies (EMDEs) has expanded substantially over the past decade. The BIS has also emphasized that foreign-currency liquidity shortages are a major source of financial stress because institutions can face obligations in dollars while their revenues and assets are denominated in other currencies.

This is the paradox of the contemporary global economy. The world needs dollars to trade, borrow, save, insure itself against shocks, and settle international obligations, but access to dollar liquidity can become highly constrained precisely when it is most needed, especially in periphery countries.

A globally distributed digital-dollar infrastructure could potentially reduce some of this friction. Treasury-backed stablecoins could place dollar-denominated liquidity directly into digital wallets and business accounts, allowing payments to move through Internet-native networks rather than depending entirely on correspondent banking relationships.

But liquidity should not become an end in itself. The objective should be to turn monetary liquidity into productive commerce, disaster resilience, and manufacturing capacity.

Why Climate and Energy?

Energy is particularly powerful because almost every other economic activity depends upon it. AI requires electricity. Manufacturing requires electricity. Desalination requires electricity. Transportation increasingly requires electricity. Data centers require electricity. Telecommunications require electricity. Robotics require electricity. Hospitals require reliable electricity. The energy system is therefore simultaneously a climate problem, an employment system, an industrial system, and an AI infrastructure problem.

The employment evidence is already striking. The IEA estimates that global energy employment reached approximately 76 million workers in 2024, with energy employment growing 2.2%, nearly twice the rate of economy-wide employment growth. Electricity generation, transmission, distribution, and storage have become particularly important sources of new employment.

Energy efficiency provides another illustration. The IEA finds that energy-efficiency investment can generate roughly 4–22 jobs per $1 million invested, depending on the sector and economic structure, while creating employment in installation, repair, manufacturing, supply, and distribution.

This is precisely the kind of economic activity that becomes attractive in an AI economy. AI can design a building, optimize a power grid, identify materials, schedule workers, monitor equipment, predict maintenance, optimize supply chains, and assist engineers. But someone still has to pour the concrete, install the transformer, wire the building, manufacture the turbine, maintain the transmission line, repair the heat pump, operate the nuclear plant, and install the solar panels. AI can therefore become a labor multiplier rather than simply a labor substitute.

The $100 Trillion Allocation Problem

The $100 trillion figure should consequently be understood as a planning horizon rather than a single expenditure authorization. The objective would be to create a decades-long investment architecture and schedule in which dollar liquidity is progressively converted into productive assets.

The first priority should be electricity generation and grids. Renewable generation, advanced nuclear, geothermal, storage, transmission, distribution, microgrids, and grid modernization should expand simultaneously. Producing electricity without the transmission infrastructure to deliver it would simply move the bottleneck downstream.

The second priority should be energy-intensive industrial capacity. The transition requires enormous quantities of steel, aluminum, copper, transformers, batteries, semiconductors, power electronics, industrial machinery, and construction materials. Hydrogen is not a practical replacement for hydrocarbon combustion in transportation, but can be valuable for producing the heat needed for many advanced industrial applications. A funded climate program that does not build manufacturing capacity risks creating demand without sufficient supply.

The third priority should be buildings and cities. Retrofitting buildings for energy efficiency, electrification, cooling, water conservation, and climate resilience could generate highly distributed employment. Unlike many digital industries, this work is geographically tied to physical structures and therefore creates employment where people actually live.

The fourth should be transportation and logistics. Mobility solutions like electrified rail, public transit, EV charging networks, ports, resilient roads, logistics systems, and low-carbon freight infrastructure are the new mix of answers for the post-carbon focus.

The fifth should be water and climate resilience. Flood protection, drought management, desalination, wastewater treatment, coastal protection, wildfire resilience, forest management, and agricultural adaptation represent investments whose value increases as climate risks become more severe.

And the sixth should be the human infrastructure necessary to operate all of this: vocational education, apprenticeships, engineering programs, technical colleges, worker retraining, and portable credentials. The IEA now identifies skilled-worker shortages as one of the principal constraints on energy-system expansion.

The critical insight is that these investments reinforce one another. More electricity enables more manufacturing. More manufacturing lowers infrastructure costs. Better infrastructure makes digital economies more productive. Better technical education increases the capacity to build infrastructure. More productive economies generate additional tax revenue and private investment. The system can therefore produce positive feedback loops rather than merely multiplying consumption.

The Global Dimension

The program should also not be conceived as an exclusively American infrastructure project. The genius of a globally distributed digital-dollar system would be its ability to connect capital and demand across borders. A worker in Kenya, a solar manufacturer in India, a battery producer in Indonesia, an engineer in Brazil, and an American infrastructure company could participate in the same dollar-denominated economic network.

Stablecoins could provide the liquidity layer. Mobile wallets could provide the distribution layer. Blockchain networks could provide the settlement layer. AI could provide the coordination layer. And physical infrastructure would provide the productive layer.

This is where the architecture becomes much more interesting than simply “crypto.” The objective would not be to replace the dollar. It would be to extend USD liquidity into places where traditional banking infrastructure has difficulty delivering it, and then connect that liquidity to productive investment.

Don’t Confuse Dollars With Resources

There is an enormous danger in this vision. A $100 trillion monetary expansion could become inflationary if financial demand grows faster than productive capacity. It could generate asset bubbles, excessive leverage, corruption, speculative land purchases, or politically directed projects with little social return. Stablecoins could also introduce new forms of run risk, concentration, sanctions exposure, privacy problems, and financial instability.

The GENIUS Act itself recognizes that stablecoin issuance requires reserve, redemption, disclosure, and compliance mechanisms. Treasury and FinCEN are also developing implementation rules addressing anti-money-laundering and sanctions requirements. The larger investment system would need an equally serious set of safeguards.

Every major project should therefore be evaluated against real-resource metrics, not simply dollars spent. How much electricity was added? How much transmission capacity? How many homes were retrofitted? How much industrial capacity was created? How many workers were trained? How much carbon or climate exposure was reduced? How much productivity increased? How much private investment was crowded out? How much local manufacturing capacity was established?

In other words, the system needs a new kind of spreadsheet logic for public investment. It would be one that links financial allocations to physical outputs, employment, energy capacity, resilience, and productivity.

From $100 Trillion of Liquidity to a New Social Contract

This ultimately reframes the AI-era employment problem. If AI makes many forms of information work dramatically cheaper, humanity should not respond by desperately trying to preserve every existing information job. Nor should we assume that technological unemployment automatically produces prosperity.

Instead, we can redirect human effort toward the enormous backlog of physical problems that remain unresolved, such as clean energy, resilient cities, affordable housing, water availability, transportation, ecosystem restoration, advanced manufacturing, healthcare infrastructure, and adaptation to climate change. AI can make humans better at solving these problems.

Treasury-backed digital dollars can potentially make it easier to finance and transact around them. And a carefully designed fiscal architecture can provide the demand necessary to mobilize labor and capital toward them. That is the deeper proposition behind a $100 trillion era.

The goal should not be to create $100 trillion of digital dollars. The goal should be to create $100 trillion worth of additional human and physical capability. The dollars are the accounting units. The stablecoins are the distribution mechanism. The Treasury market provides the reserve asset. Digital networks provide synchronization. AI provides increasingly powerful coordination.

But the final measure of success is physical.

Did humanity build more energy?

Did it build more resilience?

Did it create more productive capacity?

Did it give people meaningful work?

Did it make developing economies more capable?

Did it reduce the probability of catastrophic climate outcomes?

And did it create an economic system in which AI’s extraordinary computational productivity complements rather than simply displaces human productive capacity? That is the real $100 trillion question.

So perhaps the most important policy challenge of the AI era is not how much money we can create, but whether we can develop the institutional, computational, and political intelligence to decide what the money should build.

Selected References

Bank for International Settlements. (2026). Foreign currency funding risk and cross-border liquidity. Committee on the Global Financial System.
Bank for International Settlements. (2026). Global liquidity indicators at end-March 2026.
International Energy Agency. (2025). World Energy Employment 2025.
International Energy Agency. (2026). Ensuring a Skilled Renewable Energy and Energy Efficiency Workforce.
International Energy Agency. (2025). Jobs: Multiple Benefits of Energy Efficiency.
U.S. Congress. (2025). GENIUS Act, Pub. L. 119–27.
U.S. Department of the Treasury. (2025). Statement from Secretary Scott Bessent on Enactment of the GENIUS Act.
U.S. Department of the Treasury. (2026). Report to the Secretary of the Treasury from the Treasury Borrowing Advisory Committee.

Notes

[1] See Pennings, A.J. (2026, Apr 13) MMT as Permission, SACT as Engine. apennings.com https://apennings.com/digital-geography/the-100-trillion-debt-era-mmt-as-permission-sact-as-engine/ It makes a stronger argument that spreadsheet logic and the SACT stack provide the operational engine. SACT converts the chaotic, messy physical universe into a organized matrix of purchasable products. Without the SACT translation layer, MMT’s sovereign dollars are useless signifiers; with it, sovereign money becomes an operative tool capable of re-engineering the physical world.
[2] One important qualification: GENIUS does not authorize the US government to issue $100 trillion of stablecoins, nor does it itself create $100 trillion of new Treasury demand. The $100 trillion figure is a proposed long-run scenario. The GENIUS Act creates a regulatory framework in which private payment-stablecoin issuance can expand against specified reserves, including short-term Treasuries. The macroeconomic question is therefore how such a system could be integrated with fiscal and development policy without confusing financial liquidity with real-resource creation.

AI Prompt(s) Let’s make a plan for the next decade’s $100 trillion federal debt with UST-backed stablecoin funding and MMT permission that means the money isn’t the constraint, but you can’t just pump it into the economy without expecting repercussions. You have to think big and invest and spend wisely on issues like climate change, military resets, univeral healthcare, space exploration, and cheap education. Argue that climate change is the best target because it is simultaneously invokes a risk-mitigation program, an energy-security program, an industrial-capacity program, as well as a technology platform with positive spillovers into infrastructure resilience, advanced manufacturing, and enabling systems for space and other frontiers. It will also employ/include more people in more ways, an important consideration as we move into an AI environment. So turn this into the beginnings of a policy framework for spending in the next decade.

© ALL RIGHTS RESERVED

Not to be considered financial advice. AI is often used, and results are thoroughly interrogated. Links are used for some citations.

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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, blockchain, cryptocurrencies, democratic political economies, global communications, smart new deal
Tags: Modern Monetary Theory (MMT) > US dollar (USD) > US dollar stablecoins > US Treasuries

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