Artificial Intelligence: Signs of Acceleration in 2023

Global Head of Research

One final investment area that I’ll mention, that’s core to setting Amazon up to invent in every area of our business for many decades to come, and where we’re investing heavily is Large Language Models (“LLMs”) and Generative AI. Machine learning has been a technology with high promise for several decades, but it’s only been the last five to ten years that it’s started to be used more pervasively by companies. This shift was driven by several factors, including access to higher volumes of compute capacity at lower prices than was ever available. Amazon has been using machine learning extensively for 25 years, employing it in everything from personalized ecommerce recommendations, to fulfillment center pick paths, to drones for Prime Air, to Alexa, to the many machine learning services AWS offers (where AWS has the broadest machine learning functionality and customer base of any cloud provider). More recently, a newer form of machine learning, called Generative AI, has burst onto the scene and promises to significantly accelerate machine learning adoption.

-    Amazon CEO Andy Jassy1

When Amazon’s CEO makes such a statement, we pay attention. In 1997, had revenues of $147.8 million—in 2022, this figure was $434 billion for Amazon’s consumer business. Amazon Web Services was conceptualized in 2003, with the first services launched in 2006, and in 2022 generated $80 billion in revenues.

When Amazon’s CEO writes an entire letter on large language models—they are that transformative—we’ll look forward to reading that letter in the future!

The Stanford AI Index Steering Committee, Institute for Human-Centered AI, one of the best annual resources on artificial intelligence, just released a new report. 

AI is a big topic in 2023, and this report provides an excellent resource for understanding how it is progressing. The full piece is almost 400 pages, but we wanted to highlight some key points. 

ChatGPT Was Not the ONLY Big AI Development of 2022

On November 30, 2022, ChatGPT was launched, but the Stanford AI Index report helps us remember other notable events in 2022. Our five favorites:

1.  February 16, 2022: DeepMind trained a reinforcement learning agent to control nuclear fusion plasma in a tokamak2. While this doesn’t mean that fusion power plants are immediately around the corner, it does show a notable use case for AI to help scientific research in a very, very difficult area.

2.  April 5, 2022: Google released its PaLM large language model with 540 parameters. This was an important step, showing that one avenue to improve the performance of these models was simply to train them on more data. As of this writing, we do not know how this figure compares to the number of parameters in use for OpenAI’s GPT-4.

3.  May 12, 2022: DeepMind showcased Gato, a model that can generalize across such activities as robotic manipulation, game playing, image captioning and natural language generation.

4.  June 21, 2022: GitHub makes Copilot available as a subscription-based service for individual developers. Copilot is a generative AI system that can turn natural language prompts into coding suggestions across multiple languages.

5.  July 8, 2022: Nvidia uses reinforcement learning to design better-performing GPUs, accelerating the performance of its latest H100 class of GPU chips.

Insights on Global Corporate Investment

AI has been one of the hottest areas for corporate investment, but figure 1 shows the total level of investment shifted downward, from $276.14 billion to $189.59 billion in 2022 with the market volatility.

The two biggest categories comprising the level of AI investment recently have been “Merger/Acquisition” and “Private Investment.” Both categories dropped significantly from 2021 to 2022, but this is not surprising in that both would be expected to slow in a less certain economic environment, with the U.S. Federal Reserve quickly raising the cost of capital.

Figure 1: Global Corporate Investment in AI by Investment Activity, 2013–2022

One of the most informative charts in the 400-page report is the specific focus areas of investment and how they changed. 

•  Medical & Healthcare was the biggest focus area in 2022, after being the second-biggest in 2021, trailing only “Data Management, Processing, Cloud.”  

•  Cybersecurity, Data Protection was the fourth-biggest investment area in 2022 and the largest that saw an acceleration in investment—meaning investment in 2022 was actually larger than in 2021. The Russia/Ukraine conflict in 2022 created a big focus on cybersecurity.

Figure 2: Private Investment in AI by Focus Area, 2021 vs. 2022

Conclusion: Even if the Current “Hype” Fades, AI Will Have Staying Power

There is little question that the first four months of 2023 have seen a massive focus on AI, and a massive focus usually leads to at least some hype and some risk of near-term overvaluation. Sometimes this is the nature of thematic investment—we all want something to get excited about, especially if economic growth and geopolitics are less positive. What is emphasized in the letter from Amazon CEO Andy Jassy and then measured in the 2023 Stanford AI Index report is that the AI megatrend is continuing to grow and increase in its impact on society and on businesses.

For those investors thinking about the topic but having some concerns about near-term hype, we have noted the WisdomTree Artificial Intelligence & Innovation Fund (WTAI) because it takes a diversified approach to the broad AI ecosystem rather than a narrow focus on more singular AI activities.



1 Source: Andy Jassy, “2022 Letter to Shareholders,” Amazon,
2 A tokamak, put simply, is a device, somewhat of a doughnut in shape, used to contain the plasma in a fusion reaction.

Important Risks Related to this Article

Click here for a full list of Fund holdings. Holdings are subject to change.

There are risks associated with investing, including the possible loss of principal. The Fund invests in companies primarily involved in the investment theme of artificial intelligence (AI) and innovation. Companies engaged in AI typically face intense competition and potentially rapid product obsolescence. These companies are also heavily dependent on intellectual property rights and may be adversely affected by loss or impairment of those rights. Additionally, AI companies typically invest significant amounts of spending on research and development, and there is no guarantee that the products or services produced by these companies will be successful. Companies that are capitalizing on Innovation and developing technologies to displace older technologies or create new markets may not be successful. The Fund invests in the securities included in, or representative of, its Index regardless of their investment merit, and the Fund does not attempt to outperform its Index or take defensive positions in declining markets. The composition of the Index is governed by an Index Committee, and the Index may not perform as intended. Please read the Fund’s prospectus for specific details regarding the Fund’s risk profile.


About the Contributor
Global Head of Research

Christopher Gannatti began at WisdomTree as a Research Analyst in December 2010, working directly with Jeremy Schwartz, CFA®, Director of Research. In January of 2014, he was promoted to Associate Director of Research where he was responsible to lead different groups of analysts and strategists within the broader Research team at WisdomTree. In February of 2018, Christopher was promoted to Head of Research, Europe, where he was based out of WisdomTree’s London office and was responsible for the full WisdomTree research effort within the European market, as well as supporting the UCITs platform globally. In November 2021, Christopher was promoted to Global Head of Research, now responsible for numerous communications on investment strategy globally, particularly in the thematic equity space. Christopher came to WisdomTree from Lord Abbett, where he worked for four and a half years as a Regional Consultant. He received his MBA in Quantitative Finance, Accounting, and Economics from NYU’s Stern School of Business in 2010, and he received his bachelor’s degree from Colgate University in Economics in 2006. Christopher is a holder of the Chartered Financial Analyst Designation.