How to Appraise the AI Craze

December 19, 2023 | Devon Waskiewicz, Associate Client Analyst

This chart description is for illustrative purposes only and its accuracy cannot be guaranteed. Please see full disclosures at end of PDF document in the web post. General description: Column chart showing precent of U.S. venture funding going to AI-related startups. Chart subtitle: Venture capital money has poured into companies tied to artificial intelligence since the start of the year due to advances in the field. Chart source: Crunchbase as of June 30, 2023. Chart visual description: Y-axis labeled “Percent of U.S. Venture Funding Going to AI.-Related Startups” and ranges from 0% to 30%. X-axis labels six columns by year, from 2018 through 2023 (1Q-2Q). Each column is plotted in a shade of purple, from light to dark. Chart data description: 2018: 11%. 2019: 15%. 2020: 12%. 2021: 13%. 2022: 11%. 2023 (1Q-2Q): 26%. End chart description. See disclosures at end of document.

Even the most casual observers of market dynamics are likely aware that investor interest in artificial intelligence (AI) has surged in recent time. Within public equity markets, the share prices of companies tied to AI like Meta, Microsoft, and Nvidia have seen massive rallies since the start of the year, and a similar story exists in the world of venture capital. On a year-to-date basis through June 30, 2023, which is the most recent date for which information is available, companies focused on AI-related initiatives received 26% of total U.S. venture funding according to Crunchbase. This number represents a significant increase from the 11% figure posted in 2022. According to Pitchbook, a total of $23.2 billion has been committed to generative AI start-up businesses in 2023 through mid-October, which is already an increase of 250% when compared to last year’s total.

There are several factors that help to explain this surge in investor interest. First, recent advances in the field of generative AI have allowed for the automation of creative processes that have applicability across the market spectrum. To that point, a recent survey conducted by Boston Consulting Group found that roughly 70% of marketing companies are already employing generative AI processes for a variety of use cases including content creation and the personalization of advertising. Additionally, the field of adaptive AI, which includes machine learning, has also seen progress in recent time, with many companies now using these tools in forecasting and data analysis. Indeed, whether these new technologies are utilized to increase efficiency or decrease costs, it is clear that businesses across the economy find the benefits of AI extremely appealing, as do many investors.

Given the significant capital flows into the AI space this year, readers may be questioning the extent to which the current landscape mirrors that of the Dot-Com Bubble of the late 1990s. While it is likely too early to answer that question, it is clear that not all AI-related companies will succeed in the long run, and investors with excessive exposures to the space may be taking on elevated risk levels given a lack of diversification. At the same time, the use cases of AI are clearly significant and broad, so market participants will certainly benefit from some level of exposure to the space across both public and private markets. This dynamic speaks to the importance of investment manager due diligence and selection, which Marquette conducts on an ongoing basis across the asset class spectrum.

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