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Industry Applications

Another Industrial Revolution? – Artificial Lawyer

By Advanced AI EditorAugust 5, 2025No Comments3 Mins Read
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By John Nay, CEO, Norm Ai.

Over the past two years, much of the conversation around AI has shifted from algorithms to atoms.

Tech giants are ploughing money into chips, data centres, and dedicated power generation, at a pace that is materially moving national macro stats. Paul Kedrosky estimates that AI‑related capital expenditure will hit roughly 2 % of US GDP in 2025, enough on its own to add about 0.7% to real GDP growth, already larger (as a share of the economy) than the earlier telecom build‑out.

The numbers coming out of individual firms are eye‑popping. In their most recent quarters the ‘Magnificent 7’ spent a record $100+ billion on capital expenditure; Microsoft and Meta each devoted more than one‑third of sales to new computing facilities, racks of GPUs, and the electricity to feed them.

Economists are taking notice of the potential broader implications. MIT’s Erik Brynjolfsson asked on X: ‘In what year will the US spend more on new buildings for AI than for human workers?‘ and shared this stunning chart below, which suggests the answer is ‘soon’.

Image by Joseph Politano – Apricitas Economics.

Where is all this money coming from? Kedrosky traces six key funding pipes:

• Internal Cash Flows

• Debt Issuance

• Equity Issuance

• SPVs, Leasing, and Asset-Backed Vehicles

• Cloud Consumption Commitments

Meanwhile economist Noah  Smith warns that this shift is siphoning capital away from ‘everything else’ and could plant the seeds of the next financial crunch if highly correlated bets on AI infrastructure sour. If private‑credit vehicles and off‑balance‑sheet leases continue to balloon, an AI demand shock could ripple through banks, insurers, and alternatives investing giants.

The bottom line: AI has graduated from software feature to a massive capital‑intensive infrastructure play that could completely revolutionize the economy.

Whether that sets the stage for a correction depends on:

(1) how quickly AI capabilities improve with larger models and more test-time compute and reasoning capacity,

and

(2) how much advanced AI is actually deployed in high ROI use cases that drive economic growth.

The former depends on research advances and the foundation model labs like OpenAI and Anthropic, and the latter depends on being able to deploy AI agents in a compliant manner to unleash their capabilities in all regulated enterprises, e.g. financial services, healthcare, energy.

—

About the author: John Nay is founder and CEO of Norm Ai, an agentic AI startup focused on compliance needs. His article is inspired by the work of Paul Kedrosky and you can see a more in-depth post on the above themes on Paul’s own blog here. This longer piece above builds on an earlier LinkedIn post by Nay, here.

You can find more about Norm AI here.

—

[ This is an educational repost of an article Nay wrote and that AL really liked and so asked if this site could share it. ]

—

Legal Innovators Conferences in New York and London – Both In November ’25

If you’d like to stay ahead of the legal AI curve….then come along to Legal Innovators New York, Nov 19 + 20, where the brightest minds will be sharing their insights on where we are now and where we are heading. 

And also, Legal Innovators UK – Nov 4 + 5 + 6

Both events, as always, are organised by the awesome Cosmonauts team! 

Please get in contact with them if you’d like to take part

Discover more from Artificial Lawyer

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