In the past year, few investment themes have sparked as much excitement as artificial intelligence (AI). Although there may be some good reasons for the hype, the trend is not without significant risks. So, what steps can investors take? 

Investors can't predict the future with certainty, but they can refine their strategy for making investment decisions. By constructing a clear framework, they can better evaluate and respond to the evolving AI landscape. 

Here are 10 considerations to assist investors in this process:

1. Understanding the AI ecosystem

AI generally refers to technology that enables computers and machines to simulate human intelligence and problem-solving capabilities [1].  But this can take a lot of different forms. For instance, generative AI, which has been in the spotlight lately, involves algorithms creating new text, images and videos [2].  

Data centres, cloud computing, robotics and AI chips (graphics processing units) are also part of the picture. Given the range of investment options, it's important for investors to deepen their understanding of the AI landscape, as there isn’t a one-size-fits-all approach.

2. Assessing the opportunity 

PwC, a professional services firm, estimates that, by 2030, AI could contribute as much as $15.7 trillion to the global economy, more than the combined output of China and India [3].  

Meanwhile, according to Nvidia CEO Jensen Huang, AI's impact could potentially surpass that of computers, mobile, and the internet [4].  

These projections highlight AI's potential. But it might be too early to make any sweeping predictions. In 1998, Nobel Prize-winning economist Paul Krugman wrote, “by 2005 or so, it will become clear that the internet’s impact on the economy has been no greater than the fax machine’s.” [5] 

3. Diversification potential

AI-focused ETFs could be a strategic way to tap into the trend. Investors should be aware that holdings and strategies can vary widely among ETFs: some may include big tech names, where AI is just one component of a diversified business, while others may combine AI with other technology themes. Investors should ensure a fund's strategy aligns with their investment goals, and be aware of potential pitfalls associated with ETFs, such as concentration risk [The ETF might hold a small group of AI stocks, potentially reducing diversification and increasing company risk].

4. Are we too early?

Investing early in new technologies can be a risky endeavour. For example, only 48% of dot-com companies survived past 2004, and many of those that did suffered significant price declines [6]. Today's AI landscape may have long-term winners and failures, and new AI companies may emerge down the line. Balancing these risks involves considering the uncertain timeline ahead and managing fears of missing out.

5. Rapid change

The speed of AI's development and adoption is a key factor to consider. OpenAI’s ChatGPT, for instance, amassed 100 million users in just two months—a milestone that took TikTok nine months and Instagram over two and a half years [7]. The internet and mobile phones pave the way for AI tools to reach people even faster and become more integrated into everyday life. Grasping the exponential qualities of the AI trend is essential, as is evaluating the potential risks and rewards associated with the pace of its proliferation.

6. Crossroads of innovation

Technological convergence describes the merging of previously unrelated technologies, often into a single device [8]. For instance, the iPhone, launched in June 2007, combined a phone, an iPod and an internet device, profoundly impacting the market in a way that Apple’s competitors couldn’t match. In mid-2007, Nokia's market share was 50.8%, but by mid-2013 it had fallen to 3.1% [9]. AI might also converge with current or future technologies and sectors, potentially opening new avenues for investors. 

7. Picks and shovels?

Broadly speaking, a “picks and shovels” approach means investing in companies that provide the tools for an industry. For AI, this could mean businesses like chip makers and data centres. These investments can be strategic, as they could benefit from the broader trend while maintaining diversified revenue streams. 

However, just as computers have shrunk from the size of a room to the size of our hand, AI hardware could also evolve over time. The tools powering AI in five or 10 years may differ from today’s.

8. Nobody owns the internet  

A range of firms have been beneficiaries of the AI trend to date, and the future might be even more distributed. AI's benefits could be widespread and accessible to many, rather than being concentrated among a few companies. Some AI applications are already being open-sourced [10].  

Could AI become so ubiquitous that it trends toward not being “owned” by anyone, just like the internet? In that future, AI technology might serve as a foundational platform that companies build upon, rather than something invested in directly.

9. Unintended consequences 

Technological progress often brings unforeseen consequences. In the 1950s, nuclear power promised energy "too cheap to meter" [11], but disasters like Chernobyl and the public opposition that followed halted its expansion. Could AI face similar resistance due to job displacement or rising inequality? 

McKinsey estimates that up to 30% of work hours could be automated by 2030 [12]. However, AI could also bring unexpected positive outcomes, such as eliminating mundane jobs and creating new ones.

10. Competitive landscape

The AI landscape is crowded, with approximately 75,700 AI companies within the sector as of 17 May, 2024 [13]. What does a competitive advantage look like in this new world? Start-ups with disruptive ideas can do more with less, with AI taking on a range of tasks and freeing up employees.

Meanwhile, big tech players could leverage their network effects and economies of scale to integrate AI into their existing platforms. Competition is pivotal because, in the world of AI, one company’s software update can put another company out of business [14]. 

Conclusion

An AI investment framework should be developed in line with individual objectives and risk profiles. The rapid changes in AI mean investors need to undertake thoughtful research and be able to quickly update their strategies. As with all forms of investing, it's essential to keep an open mind and a level head.

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[1] https://www.ibm.com/topics/artificial-intelligence
[2] https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai
[3] https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html
[4] https://www.youtube.com/watch?v=Au35_6UFM5g&ab_channel=NVIDIA
[5] https://www.nytimes.com/2023/04/04/opinion/internet-economy.html
[6] https://www.nytimes.com/2008/11/23/business/23proto.html
[7] https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/
[8] https://www.techtarget.com/searchdatacenter/definition/technological-convergence
[9] https://www.statista.com/statistics/263438/market-share-held-by-nokia-smartphones-since-2007/
[10] https://llama.meta.com/
[11] https://www.nrc.gov/docs/ML1613/ML16131A120.pdf
[12] https://www.mckinsey.com/mgi/overview/in-the-news/will-generative-ai-be-good-for-us-workers
[13] https://tracxn.com/d/sectors/artificial-intelligence/__cbMnXfS2GfFo4Vi2dxZyUy7l4O8WyzVYLseb9keW5cI
[14] https://techcrunch.com/2023/11/06/get-the-pdf-outta-here/

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