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Showing posts sorted by date for query consumer spending. Sort by relevance Show all posts

Friday, July 3, 2026

How Big is SpaceX Addressable Market, Really?

Nobody yet knows the eventual returns from hyperscaler high-performance computing investments, but SpaceX has estimated the artificial intelligence total addressable market at $26.5 trillion


If that seems questionable, Morgan Stanley projects a $25 trillion market for AI-powered robots alone by 2050. 


But such estimates always are contentious, partly because they rely on decades of growth, and the inclusion of many categories of revenue that might also be placed elsewhere. 


Consider the range of estimates for the current value of the “internet” ecosystem, which has had nearly three decades to develop. 


One of the challenges in estimating the "internet economy" is that there is no universally accepted definition. 


Depending on what is included, estimates range from roughly $7 trillion (counting only direct digital-industry revenues) to well over $40 trillion (counting all commerce conducted over internet-enabled channels).


Internet ecosystem segment

Estimated 2026 annual revenue (US$ trillions)

Value Chain Segments

Sources

Global IT spending

6.3

Hardware, software, IT services, communications supporting digital infrastructure

Gartner (Gartner)

Global telecommunications services

1.3–1.4

Fixed and mobile connectivity; largely overlaps Gartner communications services

Gartner (Gartner)

Public cloud infrastructure (IaaS/PaaS)

0.4–0.5

AWS, Azure, Google Cloud and other providers

Gartner forecast and industry estimates (Gartner)

SaaS / enterprise software

1.4

Includes enterprise application and infrastructure software

Gartner (Gartner)

Digital advertising

0.7–0.8

Search, social, retail media, video, display

(Digital Applied)

Consumer internet subscriptions

0.2–0.3

Streaming, gaming, digital media, subscriptions

Industry estimates

E-commerce platform revenues (fees, commissions—not merchandise value)

0.3–0.5

Amazon Marketplace, Shopify ecosystem, eBay, Alibaba, etc.

Industry estimates

Digital payments revenues

0.2–0.3

Payment processing and fintech platforms

Industry estimates


Adding these components (while avoiding obvious double counting where possible) suggests a reasonable market of perhaps $7 trillion to $11 trillion. 


Definition

Estimated 2026 revenue

Narrow definition (digital infrastructure, software, cloud, advertising, platforms)

$7–9 trillion

Broader definition (including telecom and digital media)

$9–11 trillion


That is still big, but nowhere near the $26 trillion figure. It might be more correct to say that, eventually, AI might be essential for supporting a wide range of economic activities that do range up into double-digit trillions of dollars.


So the SpaceX TAM is to be discounted by perhaps an order of magnitude. 


All we can measure, in the near term, is the capital investment and a relatively small, but fast-growing set of revenue streams. 


Segment

Revenue / spending level

Growth rate

Global corporate AI investment

$581.69B in 2025

+129.9% YoY linkedin

Global private AI investment

$344.66B in 2025

+127.5% YoY linkedin

Generative AI private investment

$170.87B in 2025

>200% YoY linkedin

AI infrastructure, models, research, governance funding

$143.22B in 2025

Steepest growth among focus areas; exact YoY not stated linkedin

AI software market, worldwide

~$251B in 2027

31.4% CAGR from 2022 to 2027 businesswire

AI platforms

Noted as one of the largest AI software categories

35.8% CAGR, 2023–2027 businesswire

AI applications

Roughly one-third of AI software revenue in 2023

21.1% CAGR, 2023–2027 businesswire

AI systems infrastructure software

Smaller category in 2023

32.6% CAGR, 2023–2027 businesswire

AI application development and deployment software

Smaller category in 2023

38.7% CAGR, 2023–2027 businesswire

Generative AI platforms and applications

$55.7B forecast for 2027

Forecast only; growth rate not stated in source businesswire

OpenAI annualized revenue

$25B by early 2026

Fastest-style scale-up; source describes exponential growth, not a formal CAGR linkedin

Anthropic annualized revenue

$19B by early 2026

Fast growth; source describes rapid rise, not a formal CAGR linkedin

xAI annualized revenue

$428M by early 2026

Fast growth; source describes rapid rise, not a formal CAGR linkedin

Mistral AI annualized revenue

$400M by early 2026

Fast growth; source describes rapid rise, not a formal CAGR linkedin


But near-term capex will still dwarf revenues. 


source: Futurum Group


 

source: Goldman Sachs


Thursday, June 11, 2026

Will the 2026 World Cup Create Any Long-Term Economic Benefit for Host Nations?

World Cup long-term economic effects will be negligible, economists at Goldman Sachs say. That might seem unlikely, given the 2026 FIFA World Cup featuring 48 teams and 104 matches across the United States, Canada and Mexico.


After Goldman Sachs International economists Kevin Daly and Mambuna Njie studied gross domestic product data covering every World Cup since 1982, they find hosting produces a marginally positive but statistically insignificant effect on real output, with long-run impact that is effectively zero.


FIFA and the World Trade Organization disagree.  A joint study they published in April 2025, developed by consultancy OpenEconomics, projects a $17.2 billion contribution to U.S. GDP, $30.5 billion in gross output and approximately 185,000 full-time equivalent jobs for the host country alone. 


Across all three host countries, the combined GDP estimate reaches $40.9 billion, the report argues. 


Different methodologies help explain the differences. 


Beer, merchandise and apparel purchased in their own markets does not register in U.S., Canadian or Mexican GDP. 


Domestic spending on World Cup-related goods and services may simply be redirected from other consumption categories rather than representing new activity.


There is short-term lift, but no lasting contribution.


Leakage effects also are real: profits from international licensing, sponsorship and supply chains accrue outside the host country’s GDP.


On the other hand, it stands to reason that several industries should benefit, including:

  • European and US consumer staples (brewing companies including AB InBev, Molson Coors, Constellation Brands, Heineken and Carlsberg)

  • European consumer discretionary, primarily sportswear (the ones we know: adidas, PUMA)

  • U.S. retail and softlines (Academy Sports + Outdoors, Dick’s Sporting Goods, Nike)

  • U.S. lodging and leisure (Hyatt, Marriott, Hilton, Airbnb)

  • U.S. airlines. 


There will be significant industrial impact in those segments of the market, to be sure. Concentrated, time limited but real. 


Wider and long-term benefits will likely be negligible, if measurable at all. 


In many ways, the impact is similar to that supposedly created by municipally-financed sports stadia. 


The claim that government-financed sports stadia act as engines for economic growth is widely contested within the field of economics. 


While proponents often cite job creation, increased tax revenues, and regional prestige as primary justifications for public subsidies, empirical research consistently demonstrates that these facilities rarely produce significant, measurable net economic benefits for host cities.


The core economic argument against public financing centers on the substitution effect. 


Economic models often fail to account for the fact that a large portion of spending at a stadium is not "new" money introduced into the local economy; rather, it is money that residents would have otherwise spent on other local entertainment options, such as restaurants, movie theaters, or other cultural activities. 


Because this spending is simply redirected, there is little to no net increase in total local economic activity.


Furthermore, economic impact studies commissioned by proponents often rely on flawed multipliers that exaggerate the stimulative effect of sports expenditures. 


These studies frequently ignore "leakage," where significant portions of the revenue (such as players' salaries) are exported out of the local economy because athletes and owners often do not reside in the city where they play. 


Consequently, most independent academic research concludes that the public cost of these subsidies far exceeds any marginal economic growth they may stimulate.


Study / Authors

Findings

Source

Bradbury, Coates, & Humphreys (2023)

Retrospective analysis confirming that stadiums are poor public investments and that public outlays provide meager benefits.

Link

Matheson (2018)

Found no evidence that stadium subsidies yield economic growth; suggested that at most 5–15% of public cost might be justified by "public good" (civic pride).

Link

Bradbury (2022)

Found negligible net increases in sales tax collections and noted that approximately one-third of stadium sales displace other local activity.

Link

Siegfried & Zimbalist (2002)

Demonstrated that standard impact multipliers exaggerate benefits by over 400% due to consumer substitution and economic leakage.

Link

Coates & Humphreys (2003)

Econometric analysis finding no evidence of positive economic benefits associated with stadium construction; some results indicated negative impacts.

Link


Tuesday, April 21, 2026

Anthropic, AWS Move from "Build It and They Will Come" to "Build and Fulfill"

Anthropic says it has gotten an additional $5 billion investment from Amazon Web Services, “with up to an additional $20 billion in the future.”

This builds on the $8 billion Amazon has previously invested in Anthropic, and embeds Claude within AWS in several ways.

For starters, the full Claude Platform will be available directly within AWS, allowing AWS customers to use the same account, same controls, same billing, with no additional credentials or contracts necessary.

The deal also signals an intent to shift training operations to non-Nvidia platforms, which could affect the graphics processor and acceleration chip markets.

The deal also suggests a reliance on Trainium is not a short-term cost saving move but has strategic implications: AWS is building an integrated ecosystem including chip design, model training, cloud delivery and enterprise distribution.

The new agreement adds up to 5 gigawatts of capacity for training and deploying Claude, including new Trainium2 capacity coming online in the first half of this year and nearly 1GW total of Trainium2 and Trainium3 capacity coming online by the end of 2026.”

The deal also makes AWS the preferred infrastructure platform for Claude operations.

The additional investment means Anthropic is “committing more than $100 billion over the next ten years to AWS technologies, securing up to 5GW of new capacity to train and run Claude,” Anthropic said.

Say what you will about the “circular” AI economy, where infrastructure providers and chip makers invest in model providers who buy infrastructure products and services from those investors, the deal turns AI infrastructure from a high-risk capital outlay into a partially pre-committed, vertically integrated demand engine.

Since investors keep pounding infra investors on the financial returns, the move is a logical result, tying investment outlay into committed services demand.

The move also shifts the infra story further into a sustainable, industrial scale model at a time when compute demand outstrips the supply.

For AWS, this deal is a masterstroke to answer skeptics who want proof of AI monetization “now.”

By securing a $100 billion spending commitment from Anthropic over the next decade, AWS can point to a massive, "guaranteed" revenue backlog for its AI infrastructure.

Though economists might caution against crudely applying Say’s Law, which suggests supply can create its own demand, this sort of deal is a "reciprocal growth loop" where a platform provider builds massive capacity and then strategically seeds the very companies that will consume that capacity.

One might note that it does not always work out as planned. But it does work, sometimes. 

Industry

Primary Actor

The "Supply" (Investment)

The "Demand" Created

Source

Cloud AI (2023-Present)

Microsoft

Invested ~$13B+ into OpenAI.

OpenAI committed to using Azure as its exclusive cloud provider for training/inference.

Azure AI revenue growth

Railways (19th Century)

US Government

Granted 175+ million acres of land to railroad companies.

The railroads were required to carry mail and troops at reduced rates and "created" the western markets they served.

Pacific Railway Acts

Telecom (Early 2000s)

Vendor Financiers (Lucent/Nortel)

Provided billions in "Vendor Financing" (loans) to startup telcos.

Startups used the loans specifically to buy hardware from Lucent/Nortel to build 3G/fiber networks.

The Dot-com Bust

Ride-Sharing (2010s)

SoftBank (Vision Fund)

Invested billions into Uber, Grab, and Didi.

These companies used the "supply" of cash to subsidize rides, artificially creating massive consumer demand for a new infra.

SoftBank Vision Fund

Energy (2020s)

AWS / Google / Microsoft

Investing in Nuclear/SMR startups (e.g., Kairos, Helion).

Data centers provide the "off-take" agreement (guaranteed demand) that allows the energy supply to be built.

Google/Kairos Power Deal


And in this case, the seeded company already has enterprise customer traction.

The new AWS deal with Anthropic is a landmark example of "circular infrastructure financing," where a cloud provider invests capital into a high-demand customer, who then immediately pledges that capital (and more) back to the provider in the form of long-term compute commitments.

For AWS, this deal is a tactical masterstroke to answer skeptics. By securing a $100 billion spending commitment from Anthropic over the next decade, AWS can point to a massive, "guaranteed" revenue backlog for its AI infrastructure. It transforms speculative capital expenditure (building data centers and custom Trainium chips) into a contractual future cash flow, providing the "proof of monetization" that investors currently crave.

In economics, this is often associated with Say’s Law, which suggests that the production of goods generates the income necessary to purchase them. In the tech industry, this often manifests as a "Reciprocal Growth Loop": a platform provider builds massive capacity and then strategically seeds the very companies that will consume that capacity.

It wouldn’t be the first time infrastructure or platform "supply" was used to intentionally manufacture its own "demand."

Firms might be expected to face scrutiny over "build it and they will come" strategies. This deal moves AWS from a "build and wait" model to a "build and fulfill" model.

It transforms speculative capital expenditure (building data centers and custom Trainium chips) into a contractual future cash flow, providing the "proof of monetization" that investors currently crave.

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