Economics
These economists say AI can improve the fiscal health of the U.S.
Published
2 years agoon
Can artificial intelligence be so transformative as to solve one of the U.S. economy’s biggest problems: its skyrocketing fiscal deficit? According to three economists at the Brookings Institution, the answer is yes — AI could prove a positive “critical shock” for the country’s fiscal health.
A working paper released last month by the Center on Regulation and Markets at Brookings projects that under the most optimistic scenario, AI could reduce the annual U.S. budget deficit by as much as 1.5% of gross domestic product by 2044, or about $900 billion in nominal terms, lowering annual budget deficits by roughly one fifth at the end of the 20-year span.
“The use of AI presents the rare — possibly unique — opportunity to expand access to health care information and services while simultaneously reducing the burden on the conventional health care system,” the paper’s authors, Ben Harris, Neil Mehotra and Eric So, wrote.
While the authors name various channels through which AI can increase productivity, they highlight AI’s potential to dramatically improve health care services and public health.
Not only could AI make American health care more efficient, it might also “democratize” access to the system by giving people more options for preventative medical care — “changing the ‘who’ and ‘where’ of health care,” the economists wrote.
AI could ease deficit pressure
The economic impacts of a more efficient health care system, and giving individuals more paths to manage their own health, could ease pressure on the government’s yawning fiscal deficit, which topped $1.8 trillion in the fiscal year ended Sept. 30. The national debt stands at $36 trillion.
But adopting AI in health care services isn’t a sure thing. Plenty of impediments stand in the way of widely implementing AI, largely tied to regulation and incentives.
Economists’ outlook on AI and health care is “a mix of enthusiasm and despair,” said Ajay Agrawal, a professor at the University of Toronto’s Rotman School of Management ,where he researches the economics of artificial intelligence.
“Enthusiasm because there’s probably no sector that stands to benefit more from AI than health care. … But there’s friction due to regulation, due to incentives — because of the way things are structured and how people are paid for things — and friction due to the associated risks and liabilities,” Agrawal said.
“So yes, there’s lots of implementation challenges, and at the same time, the prize for succeeding at this is very big,” Agrawal said.
Health care and the deficit
The federal government spent an estimated $1.8 trillion on health insurance in 2023, or around 7% of GDP, according to the Congressional Budget Office. From 2024 to 2033, the CBO forecasts federal subsidies for health care will total $25 trillion, or 8.3% of GDP.
The problem is that so much health care spending in the U.S. isn’t tied to treatment or patient outcomes. Instead, about a quarter of all spending, public and private, is estimated to go toward administrative functions.
“Nearly every industry in the U.S. has experienced substantial improvements in productivity over the last 50 years, with 1 major exception: health care,” according to a report by McKinsey analysts.
This is one area where AI could improve operations, according to the Brookings Institution economists. Basic tasks such as appointment scheduling can be automated, while tasks such as patient flow management and preliminary data analysis can also be done by AI programs.
While the three economists acknowledge that the impact of AI on federal spending is still “highly uncertain,” the coauthors believe it could ultimately be more transformative for the economy than past technological leaps, such as the use of personal computers in the 1990s. The current AI shock “feels different. This isn’t your typical technological shock,” Harris told CNBC.
AI is affecting “how people receive health care,” how the drug industry discovers new products and how researchers make medicine more precise, Harris said.
Disease and death rates
In particular, Harris underscored AI’s impact not just on productivity, but also its potential to transform the cost of care and the rates of illness, disease and death.
“Such changes could have profound impacts on Social Security and public health program outlays,” he and his coauthors wrote.
To be sure, there is also the potential that AI advancements could counterintuitively increase federal spending if the average lifespan increases as a result of the technology. Not only could improved technology lead people to seek more medical care, longer lifespans might also result in a larger retired population.
But the Brookings paper takes a more optimistic tack, predicting one of AI’s largest benefits will result from accelerating the efficacy of preventative care and disease detection. This will create a healthier population that will need less medical intervention, the authors wrote — and might also increase labor force participation rates if a healthier workforce stays employed for more years.
“AI’s ability to improve diagnostic accuracy can not only improve patient outcomes but also reduce wasteful spending on inappropriate treatments,” the economists said. “From a more optimistic perspective, existing AI systems may lower expenditures on all health spending, including Medicare, with cost reductions occurring through several channels—with personalized medicine being a prominent example.”
Evaluating whether AI can ultimately translate into a positive or negative shock on fiscal policy will depend on what stage of the age distribution it affects, Agrawal said. Whether AI is “having its bigger impact on retired people, or around working people,” will answer how the numbers play out, Agrawal said.
AI proliferating already
So far, diagnostics has shown the most advances and greatest potential in applying AI in health care. Agrawal cited AI’s influence throughout almost all the steps of diagnostic care, from receiving input data, medical imagery such as X-rays and MRIs, as well as doctor notes, charts.
“In almost every area of diagnosis, AI has, in some cases, already demonstrated what they call ‘superhuman performance’ — better than than most docs,” Agrawal said.
AI has also shown “significant promise” in better optimizing treatment plans for patients through data analysis. Machine intelligence can develop more effective and less costly plans for individual patients, according to the authors of the paper.
Agrawal believes it’s too early to say whether public or private health systems will take better advantage of AI. In the U.S., private insurers have generally been more keen on AI technology associated with preventative treatment, he said. There’s been less interest in using AI in diagnostic applications, possibly that might lead to a rise in cases and more treatment, he said.
“There aren’t clear economic incentives for the private sector to [implement] that,” said Agrawal. “In the public sector, even though there are incentives, there are a lot of frictions associated with privacy on the data side.”
He believes public-private partnerships will be key in driving the rollout of AI across health care.
The public health care sector “will need very strong incentives in order to drive change, because otherwise, everybody is in their routine. There’s a lot of resistance to change,” Agrawal said.
“So to get over that resistance, you need a very strong motivator, and the private sector generally provides a much stronger motivator, either because the users are trying to reduce cost, or the creators of the technology are trying to generate profit,” he continued.
Large tech companies have already pushed forward in developing large language models specifically for health care services. Google’s AI system, Articulate Medical Intelligence Explore (AMIE), mimics diagnostic dialogue. Its Med-Gemini platform uses AI to aid in diagnosis, treatment planning and clinical decision support. Amazon and Microsoft have their own projects underway to expand the application of AI programs in health services.
Outlook under Trump
President-elect Donald Trump’s second term could alter the rollout of AI in health care, and ultimately, its economic impact. Trump has vowed to reduce government spending and formed an outside panel called the Department of Government Efficiency designed to “dismantle Government Bureaucracy, slash excess regulations, cut wasteful expenditures, and restructure Federal Agencies.” Public health funding is one area that could reduced funding, frustrating the ability to roll out AI applications.
“Now, it is possible that if you do see a retreat in the federal government’s role in providing health care to people, that more efficient AI could help compensate for the cost of that retreat,” said Harris. “If AI means that each dollar goes farther, then I think we’ve timed everything in a sort of lucky way.”
There’s also the chance that rolling back regulations under a second Trump administration could expedite the implementation of AI across health care.
“Many people are fearful of reducing regulation because they don’t want technologies that are immature to be brought into the health care system and harm people,” Agrawal said. “And that’s a very legitimate concern. But very often what they fail to also put into their equation is the harm we’re causing people by not bringing” in new technologies, he added.
“Some areas need a lot more technical development, but there are some domains in diagnosis that are already ready to go, and it’s just regulation that’s preventing them from being used,” Agrawal said.
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Economics
U.S.- Canada Trade Talks Collapse; Carney Says Retaliatory Tariffs Begin September 8
Published
2 days agoon
September 1, 2026
Trade negotiations between the United States and Canada collapsed this week, with Canadian Prime Minister Mark Carney announcing that retaliatory tariffs on U.S. goods will take effect September 8, 2026. The breakdown follows the Trump administration’s imposition of 50% tariffs on certain Canadian goods, according to reporting from CNBC and the Washington Post.
What Happened
CNBC reported the collapse of talks as part of its ongoing business news coverage on August 22, 2026, noting the story as one of the week’s most significant developments for cross-border trade. The Washington Post’s business desk, in coverage also published August 22-23, quoted Carney characterizing President Trump’s 50% tariffs as “a miscalculation,” and confirmed the September 8 date for Canada’s retaliatory measures.
As of this writing, specific details on which categories of U.S. goods will be subject to Canadian retaliatory tariffs have not been fully reported. This article will be updated with additional specifics as they become available from primary government sources.
Why This Matters for Markets and Consumers
Trade disputes between the U.S. and its largest trading partners tend to have ripple effects across supply chains, consumer prices, and specific industry sectors with cross-border exposure. A Washington Post analysis accompanying the coverage noted that other countries unhappy with existing U.S. trade arrangements are likely watching the U.S.-Canada breakdown closely, suggesting the dispute could have implications beyond the immediate bilateral relationship.
Broader Context: A Volatile Week for Cross-Border and Fiscal News
The trade breakdown arrived during an already turbulent week for U.S. economic news. The same week saw the national debt cross $40 trillion for the first time, a sharp rise in Treasury bond market volatility, and the Treasury Department doubling the size of its debt buyback program. Whether the trade dispute has any direct connection to these fiscal and monetary developments has not been established in current reporting, but the concentration of major economic stories in the same week has drawn attention from market commentators tracking overall macroeconomic risk.
How This Fits the Broader Trade Policy Pattern
The U.S.-Canada breakdown is not occurring in isolation. Trade policy has been an active area of U.S. economic policymaking throughout 2026, with tariff actions and negotiations affecting multiple trading partners over the course of the year. Canada has historically been among the United States’ largest trading partners by total trade volume, meaning a prolonged dispute carries more direct economic exposure for both economies than a similar breakdown with a smaller trading partner would.
Industries with integrated North American supply chains — including automotive manufacturing, agriculture, and energy — have historically been among the most exposed to U.S.-Canada trade friction, given the degree to which components and raw materials cross the border multiple times during production. Businesses in these sectors should treat the September 8 deadline as a planning point regardless of whether it ultimately takes effect as announced.
What We Don’t Yet Know
Several material details remain unconfirmed or unreported as of this writing:
– The specific list of U.S. product categories subject to Canadian retaliatory tariffs
– Whether any further negotiations are scheduled between the September 8 deadline and the present
– Potential exemptions for critical supply chains, such as energy or auto parts, which have historically received special treatment in prior U.S.-Canada trade disputes
What to Watch Next
Businesses with cross-border exposure to Canadian suppliers or customers should monitor official statements from the U.S. Trade Representative’s office and Canada’s Department of Global Affairs for detailed tariff schedules ahead of the September 8 implementation date. Given the fluid nature of trade negotiations, a resumption of talks or a modified agreement before that date remains possible and would supersede current retaliatory tariff plans.
Economics
U.S. National Debt Surpasses $40 Trillion for the First Time: What It Means for the Economy
Published
2 weeks agoon
August 23, 2026
The U.S. gross national debt crossed $40 trillion for the first time this week, according to Treasury Department data reported by NPR on August 20, 2026. The milestone caps a period of rapid fiscal expansion: the debt has doubled since 2017, and the federal government now spends more than $1 trillion a year just servicing interest on what it owes.
Why the Debt Load Is Accelerating
The debt has not grown at a steady pace. Instead, a combination of pandemic-era spending, tax policy changes, and elevated interest rates has compounded the federal government’s borrowing costs. As older Treasury bonds issued at lower rates mature, they are being refinanced at today’s higher prevailing rates, which pushes up the government’s annual interest bill even without any new borrowing.
That interest bill is no longer a minor line item. At more than $1 trillion annually, debt servicing now competes directly with discretionary spending on defense, infrastructure, and social programs. Economists watching the trend note that this dynamic can become self-reinforcing: higher interest costs widen the deficit, which requires more borrowing, which in turn raises future interest costs.
Bond Market Reaction
The debt milestone arrived during a volatile week for Treasury bonds. Bond prices fell even as equity markets touched record highs, a divergence that market analysts describe as bond investors signaling concern about the sustainability of federal borrowing, even as stock investors remain focused on corporate earnings and AI-driven growth.
U.S. Treasury Secretary Scott Bessent responded to the bond market pressure by expanding the Treasury’s debt buyback program, telling CNBC the size of buyback operations had been doubled to at least $4 billion per operation, with room to increase further. Buybacks are intended to support demand for existing Treasury securities and help stabilize yields during periods of market stress.
What Rising Debt Means for Ordinary Households
For everyday consumers, the national debt level itself is abstract, but its downstream effects are not. Elevated Treasury yields tend to push up borrowing costs across the economy, including mortgage rates, auto loans, and business credit. The same week the $40 trillion milestone was confirmed, average 30-year mortgage rates moved sharply, illustrating how bond market volatility connects directly to household borrowing costs.
Rising federal interest costs also narrow the government’s fiscal flexibility. As a larger share of the federal budget goes toward servicing debt rather than funding programs, policymakers face growing pressure to either cut spending, raise revenue, or both — choices that carry direct economic consequences for households and businesses alike.
What to Watch Next
The debt trajectory is expected to remain a central topic at the Federal Reserve’s Jackson Hole Economic Symposium, scheduled for August 27–29, 2026 — the first such gathering under new Fed Chair Kevin Warsh, who was confirmed by the Senate in a 54-45 vote in May 2026. While the symposium’s stated theme is financial innovation and payments policy, fiscal sustainability and its interaction with monetary policy are likely to feature in sideline discussions given the scale of the debt milestone.
Investors and households should watch upcoming Treasury auction results and any further changes to the buyback program as early indicators of how markets are digesting the government’s borrowing needs. A weak auction — one that requires higher yields to attract sufficient buyers — would be a signal that investor appetite for U.S. debt is softening further.
The $40 trillion figure is a threshold, not a crisis in itself. But combined with a bond market already showing signs of strain, it adds urgency to a fiscal conversation that has largely been deferred by successive Congresses and administrations.
Economics
Economic Profile of the United States of America (2026–2030 Horizon)
Published
2 weeks agoon
August 22, 2026
Executive Summary & Core Macro Outlook
The United States enters the 2026–2030 macroeconomic window as the unquestioned heavyweight of nominal economic output, retaining its status as the primary engine of global financial liquidity, private enterprise innovation, and high-margin technological deployment. According to multi-year projections from the International Monetary Fund (IMF) World Economic Outlook and complementary datasets from the World Bank, the US nominal Gross Domestic Product (GDP) is projected to reach $32.38 trillion by 2026, accounting for approximately 25% of global nominal output and roughly 14.5% of world GDP measured at Purchasing Power Parity (PPP).
Unlike many of its advanced-economy peers across Western Europe and East Asia—which are grappling with acute demographic contraction and structural energy shocks—the United States demonstrates remarkable macroeconomic resilience. The IMF projects a real GDP Compound Annual Growth Rate (CAGR) of 2.1% to 2.3% through 2030. This expansion is sustained by three structural anchors: unmatched capital depth driving massive private-sector investment in Artificial Intelligence (AI) infrastructure, complete energy independence as a net exporter of hydrocarbons and liquefied natural gas (LNG), and high labor productivity gains that cushion the economy against rising debt-servicing costs.
Macroeconomic Data Matrix (2026–2030 Projections)
| Economic Metric | IMF / World Bank Baseline (2026–2030) | Global Benchmark & Context |
| Nominal GDP (2026 Projection) | ~$32.38 Trillion | Rank #1 Globally |
| GDP at Purchasing Power Parity (PPP) | ~$32.40 Trillion | Rank #2 Globally (Behind China’s ~$38.5T PPP) |
| Projected Real GDP CAGR (2026–2030) | 2.1% – 2.3% | Top decile among G7 advanced economies |
| Gross Public Debt (% of GDP) | ~122.5% – 128.0% | Structural fiscal deficit trajectory |
| Core Inflation Rate (PCE Target) | Stabilizing at 2.0% – 2.2% | Federal Reserve inflation target alignment |
| Current Account Balance (% of GDP) | -2.8% to -3.2% | Persistent capital import & reserve currency demand |
Deep Structural Growth Drivers
1. The AI Infrastructure Hyper-Cycle & TFP Expansion
The defining growth catalyst for the US economy over the 2026–2030 horizon is the unprecedented scale of private capital expenditure (Capex) poured into artificial intelligence infrastructure, enterprise software integration, and advanced computing hardware.
Major technology mega-caps and private equity funds are directing hundreds of billions of dollars annually into hyper-scale data centers, domestic semiconductor fabrication, high-voltage electrical grid upgrades, and AI-driven workflow platforms. According to World Bank economic research, technological adoption across American service and manufacturing sectors is driving a notable uptick in Total Factor Productivity (TFP). This productivity surge allows US companies to expand profit margins and output even in an environment characterized by higher structural real interest rates and tight skilled-labor markets.
2. Deep Capital Markets and Private Sector Liquidity
The structural backbone of US economic outperformance remains its financial system. US capital markets represent over 40% of global equity market capitalization and a vast majority of global venture capital and private credit assets.
This liquidity creates an efficient mechanism for capital allocation: high-potential emerging industries (such as quantum computing, synthetic biology, and advanced defense technology) receive early-stage funding at a scale that no other national market can match. When global monetary conditions tighten, global capital flees toward safety and yield, reinforcing US capital depth and lowering the relative cost of equity capital for American corporations.
3. Net Energy Independence & Industrial Cost Advantages
Unlike industrial hubs in Germany, Japan, or South Korea—which remain highly vulnerable to volatile sea-lane logistics and imported fuel price spikes—the United States operates as a major net exporter of petroleum, natural gas, and refined chemical products.
Access to abundant, cheap domestic natural gas provides US heavy industry, advanced manufacturing, and electricity-hungry data centers with a persistent structural cost advantage. Furthermore, federal policy frameworks (including the CHIPS and Science Act and clean energy tax provisions) continue to catalyze domestic private manufacturing investment, re-shoring high-value supply chains from East Asia back to the American Sunbelt and Midwest.
Macroeconomic Vulnerabilities & Downside Risks
1. Structural Sovereign Debt Trajectory
The most significant medium-term threat to US macroeconomic stability is the path of federal public debt. With gross national debt exceeding 120% of GDP and annual federal deficits running between 5% and 7% of GDP, the US fiscal baseline faces increasing structural pressure.
As older legacy low-yield Treasury bonds mature, they are refinanced at higher prevailing interest rates. According to IMF fiscal monitor assessments, federal net interest payments are absorbing an expanding share of total fiscal revenue, crowding out discretionary spending and narrowing the government’s capacity to deploy counter-cyclical fiscal stimulus during future downturns.
2. Commercial Real Estate (CRE) & Banking Sector Realignment
The structural transformation toward hybrid work models has permanently altered office space utilization across major US metropolitan areas. Regional and community banks, which hold a disproportionate share of commercial real estate debt, face ongoing balance-sheet pressure as legacy office loans mature and require refinancing at lower property valuations and higher interest rates. While systemic money-center banks remain well-capitalized, localized credit tightening from regional lenders presents a headwind for small-and-medium enterprise (SME) borrowing.
High-Outperformance Sector Matrix (2026–2030)

- Enterprise AI, Cloud Compute, & Cybersecurity: Companies building enterprise-grade software, AI agents, cloud architectures, and specialized hardware protection layers.
- Next-Generation Energy & Grid Modernization: Power generation utilities, high-voltage electrical equipment makers, small modular nuclear reactor (SMR) developers, and energy storage systems catering to exponential data center energy demands.
- Advanced Defense Technology & Aerospace: Autonomous systems, satellite networks, hypersonic defense, and advanced materials supplying both domestic security needs and global allied demand.
Strategic Summary for Global Investors & Executives
The United States through 2030 remains the ultimate high-volume, high-yield destination for institutional capital. While fiscal debt risks require long-term monitoring, the immediate 5-year outlook is defined by strong technology-driven productivity, resilient private consumption, and unmatched market liquidity. For global corporations and institutional allocators, exposure to the US economy remains an indispensable pillar of long-term growth strategy.
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