Not all bubbles have negative consequences for the economy. An AI bubble is more likely to generate value than wreak havoc.

Already a member? Sign in Not a member? Member Free 5 Free Articles per month, $6.95/article thereafter. Free newsletter. Subscribe $75/Year Unlimited digital content, quaterly magazine, free newsletter, entire archive.

With investments in artificial intelligence rising rapidly, especially in China and the United States, two questions arise: Are we heading toward an AI bubble? And if so, how bad would it be if the bubble were to burst?

Having studied AI intensely for the past two years, our best guess to the first question is, yes, today’s fascination with all things AI has most of the trappings of a financial bubble. But unlike the housing bubble, the effects of a bursting AI bubble wouldn’t cause great harm. Indeed, this bubble seems to have more in common with the dot.com bubble, which helped finance the internet backbone, than the housing bubble, which wreaked havoc on the household finances of millions of homeowners.

The Making of a Bubble

Bubbles occur when the market value of assets decouple from their intrinsic value and expectations of rising valuations generate investor demand. In typical bubbles, both the volume and valuation of investments expand rapidly. We are seeing both trends in AI. (See “Funding for AI Startups.”)

Funding for AI Startups





Volume. From 2013 through 2018, both the number and size of AI deals soared. Overall investments rose by 75% annually. It’s not just the Chinese government making investments; private investment in all regions has also surged. AI investments are rising, both in absolute terms and also relative to other categories of technologies. For example, between 2012 and mid-2018, investors poured $110 billion into 9,800 AI startup rounds of financing, dwarfing the $12 billion invested in 1,500 blockchain startups during that time and the $700 million invested in 60 quantum computing startups.

Valuations. The AI era is different from the dot.com era in at least one key respect. The biggest new dot.com companies began selling their stock on the public market quickly, whereas AI companies typically remain private; this makes direct comparisons difficult. As shown in the accompanying exhibit, the average deal size — a rough proxy for valuation — has almost tripled over the past five years.

Read the Full Article Already a subscriber?

About the Authors Philipp Gerbert is senior partner and managing director in the Munich office of Boston Consulting Group and a BCG Henderson Institute fellow exploring the impact of AI on business. He leads the company’s global digital strategy topic and its AI@Scale initiative. Michael Spira is a project leader in Boston Consulting Group’s Munich office and a core member of BCG’s Digital Accelerator System and its Energy practice.

Acknowledgments The authors thank Lorenz Pammer and Friederike Reuter for support in compiling this article and Mark Voorhees for writing assistance.