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This paper analyses the artificial intelligence (AI) investment boom and the potential for a much-forecast bust.

We ask three important questions:

1. How is AI investment funded? We consider whether it is self-funded through cash flow or debt.

2. What will be the business model post launch? We see three distinct revenue streams: First advertising cannibalising search engines. Second, subscriptions from B2B customers and B2C firms, with a wide geographic spread. Third, utility-style cash flows: Once AI is embedded in a system, it is needed forever.

3. What is the competitive model? There is risk of oligopolistic competition, or collusion, which would invite the regulators’ wrath.

Bubbles, booms and busts: The story is always the same and has always ended in busts. The story typically serves as a parable about greed and avarice, misplaced hopes and destroyed lives. It is not an urban myth; it is real and resonates and repeats across centuries: Dutch tulips in 1637; the South Sea Bubble of 1720; railway mania of the 1850s in the United Kingdom and the 1860s/1870s in the United States; 1929, a crash so infamous that mentioning the year alone is a reminder to investors; the dot-com crash of 2001; and the global financial crisis (GFC) of 2008, which was so traumatic that we don’t even mention the subprime mortgage boom that caused it. These are only the major events; between these notable examples are countless others of local and international importance, including in 1907, 1987 and others.

So, do we need to welcome a new chapter of tears: the AI boom and bust?

In this paper, we assess the size of this boom, including whether it is truly big enough to change the world. Another critical question is its financing, given all of the earlier busts came from the weight of debt. And we will look at how AI generates revenues and profits.

Only after discussing these topics can we then draw a conclusion about whether the boom is sustainable or more likely to end in a bust.



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