Private funds' edge in differentiated AI exposure

Precisely how artificial intelligence (AI) will grow and shape human society is unclear. What is clear is that its impact is likely to be significant, both from a human and investment perspective.

For investors with a long-term mindset - which should be almost everyone - seeking exposure to the growth of AI seems to be (to put it mildly) a sensible investment decision. The sheer breadth of sectors that may be impacted by AI offers enormous upside potential for innovators in the space - even if their initial application is narrow. AI’s potential to lift productivity across numerous industries - there is no sector in which improved productivity is not worth investing in - should underpin rapid growth over the coming decade and beyond. AI’s global market size is estimated to have reached $137B in 2022 and is projected to expand 37.3% annually from 2023 to 2030 to a size of more than $1.8T.² Sliced another way, the AI market is expected to be 13 times larger by 2030 than it was in 2022. (For context, the giant pharmaceuticals market was worth an estimated $1.6T globally in 2022.)³

The biggest question is how to best gain exposure.

You can certainly create exposure to AI through public markets. Two of the most obvious approaches are via ETFs, or by allocating to individual companies that have direct or indirect exposure to AI:

1. ETFs: For those looking for a simpler, diversified public market approach, an AI-focused ETF could be suitable. There are a variety of flavors of AI exposure available - currently 31 such ETFs are listed on US markets, with total assets under management of $6.5B⁴ - but each will invest in companies that may benefit from increased adoption of AI.

2. Individual Companies: On the one hand, a number of well-known, large-cap companies are investing in, leveraging and creating applications of AI, and may be considered a lower risk approach to investing in the space. Market leaders such as Alphabet, Amazon, and Tesla are already all developing or acquiring AI solutions, and will continue to do so. On the other hand, you could look directly at companies providing the tech supporting the development of AI - such as chipmakers, data providers, and certain software providers.

These strategies will definitely offer you exposure to AI, albeit in a slightly imprecise and indirect way. An ETF approach is not particularly selective, constrained by the range of available public companies in the space.⁵ Meanwhile, investing in the individual companies is typically not a pure AI play, with very few AI-led companies yet publicly listed.

Indeed, investing via private markets may offer a differentiated, direct and far more selective exposure to AI:

1. Differentiated, most obviously because private companies are by definition simply not accessible via public markets, but also in terms of the types of tech you gain exposure to. The most innovative emerging technologies are typically being originated by companies at an early stage of development, too small to list publicly and forced to (or choosing to) access finance via private market funds.

2. Direct, in the sense of the private investment model involving putting money directly to work in AI-focused companies. This can increase upside potential, but may also increase risk of loss.

3. Selective, because rather than investing in a sector as a whole, private funds invest in specific companies in which they have a high conviction. This is an important benefit of private funds’ active management approach, particularly when there are likely to be a few big sector winners, but many more failures.

VC funds are the most obvious vehicles through which to invest directly in AI innovation, and offer the most upside, given that they are investing in early-stage companies. It is much easier to double a $10M valuation than a $10B one - though a $10M company typically comes with greater risk of failure. This wide range of outcomes elevates the importance of selecting (and gaining access to) the right VC manager.

However, there will be secondary impacts of AI growth that will create opportunities for investment from private funds across the spectrum. For example, rising demand for hardware infrastructure should provide opportunities for infrastructure and real estate funds to develop and invest in specialist facilities, such as high-performance computing data centers.

Private funds have been ramping up investment in AI in recent years (see chart below). While investment may have moderated in 2022, the overall trend towards greater investment is likely to resume once current market conditions ease. 

This funding should help the private opportunity set expand even further. New applications for AI are likely to emerge and find support in parallel to continually improving technology.

For clients that can stomach a little illiquidity, advisors looking to take advantage of the upside in AI might well consider putting their money to work at a time when entry valuations for tech companies are resetting, potentially presenting attractive opportunities to realize value over the longer term.

To discuss how Opto can help you get your clients exposure to coveted VC funds that invest in AI, please get in touch with us at advisory-services@optoinvest.com.