Investment Trends in Disruptive Technology: The Shift to AI

While venture capital is taking a more cautionary approach with crypto startups, the buzz around GenAI is only increasing.

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Welcome to Thoughts on the Market. I’m Ed Stanley, Morgan Stanley’s Head of Thematic Research in Europe. Along with my colleagues bringing you a variety of perspectives, today I’ll discuss what private markets can tell us about the viability and investability of disruptive technologies. 

It’s Tuesday, the 3rd of September, at 2pm in London. 

For the past three years we have been tracking venture capital funding to help stay one step ahead of emerging technologies and the companies that are aiming to disrupt incumbent public leaders. Private growth equity markets are -- by their very definition – long-duration, and therefore highly susceptible to interest rate cycles. 

The easy-money bubble of 2021 and [20]22 saw venture funding reach nearly $1.2trillion dollars – more than the previous decade of funding combined. However, what goes up often comes down; and since their peak, venture growth equity capital deployment has fallen by over 60 percent, as interest rates have ratcheted ever higher beyond 5 percent. 

So as interest rates fall back towards 3.5 percent, which our economists expect to happen over the coming 12 months, we expect M&A and IPO exit bottlenecks to ease. And so too the capital deployment and fundraising environment to improve. 

However, the current funding market and its recovery over the coming months and years looks more imbalanced, in our view, than at any point since the Internet era. Having seen tens- and hundreds of billions of dollars poured into CleanTech and health innovations and battery start-ups when capital was free; that has all but turned to a trickle now. On the other end of the spectrum, AI start-ups are now receiving nearly half of all venture capital funding in 2024 year-to-date. 

Nowhere is that shift in investment priorities more pronounced than in the divergence between AI and crypto startups. Over the last decade, $79billion has been spent by venture capitalists trying to find the killer app in crypto – from NFTs to gaming; decentralized finance. As little as three years ago, start-ups building blockchain applications could depend on a near 1-for-1 correlation of funding for their projects with crypto prices. Now though, despite leading crypto prices only around 10 percent below their 2021 peak, funding for blockchain start-ups has fallen by 75 percent. 

Blockchain has a product-market-fit and a repeat-user problem. GenerativeAI, on the other hand, does not. Both consumer and enterprise adoption levels are high and rising. Generative AI has leap-frogged crypto in all user metrics we track and in a fraction of the time. And capital providers are responding accordingly. Investors have pivoted en-masse towards funding AI start-ups – and we see no reason why that would stop. 

The same effect is also happening in physical assets and in the publicly traded space. Our colleague Stephen Byrd, for example, has been advocating for some time that it makes increasing financial sense for crypto miners to repurpose their infrastructure into AI training facilities. Many of the publicly listed crypto miners are doing similar maths and coming to the same outcome. 

For now though, just as questions are being asked of the listed companies, and what the return on invested capital is for all this AI infrastructure spend; so too in private markets, one must ask the difficult question of whether this unprecedented concentration around finding and funding AI killer apps will be money well spent or simply a replay of recent crypto euphoria. It is still not clear where most value is likely to accrue to – across the 3000 odd GenerativeAI start-ups vying for funding. 

But history tells us the application layer should be the winner. For now though, from our work, we see three likely power-law candidates. The first is breakthroughs in semiconductors and data centre efficiency technologies. The second is in funding foundational model builders. And the third, specifically in that application layer, we think the greatest chance is in the healthcare application space. 

Thanks for listening. If you enjoy the show, please leave us a review and share Thoughts on the Market with a friend or colleague today.

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