In recent months, the conversation around artificial intelligence (AI) has reached a fever pitch, with its impact on financial markets and the broader economy continuing to materialize rapidly. As with all new technologies, and especially with those that stand to revolutionize productivity and innovation so drastically, it's crucial for investors, financial professionals, and consumers alike to understand the implications this technology has on the investment landscape. 

The Rise of AI in Finance

Early conversations on AI often cited the need for “productivity gains” to be realized before any large-scale implementation efforts could be undertaken, as there were still doubts on AI’s implications outside of theory. However, from high-frequency trading algorithms to personalized banking experiences and robo-advisors, AI is already being implemented in the financial sector. Recent data from the International Monetary Fund (IMF) shows that AI content in algorithmic trading patents has risen dramatically, from 19% in 2017 to over 50% annually since 2020[1].  

Additionally, major financial institutions are investing heavily in AI capabilities and research. According to recent reports, between 2017 and 2022 Wall Street’s largest banks filed roughly 90% of AI-related patents, published two-thirds of AI research papers, and accounted for half of AI investments in the sector[8]. JPMorgan Chase, for instance, is projecting the firmwide technology spend to be roughly $17 billion for 2024, up $1.5 billion year-over-year, with a significant portion dedicated to AI and machine learning initiatives[3]. The firm is also continuing to spearhead the AI research landscape, accounting for 45% of all research published by financial institutions in 2023, up from 31% in 2018[4]. 

JPM Total Share of AI Related Research

Figure 1. Source: Evident Insights*

Investment Opportunities in AI Related Sectors

Without reservation, the sector given the most attention thus far in the AI boom is technology. Companies at the forefront of AI development, such as NVIDIA, AMD, and Intel, have seen share prices soar as demand for AI-capable hardware increases exponentially. Cloud computing giants like Amazon, Microsoft, and Google are also benefiting from the increased demand for AI-powered services. However, beyond the tech sector, AI is creating opportunities across various industries: 

• Healthcare: AI is revolutionizing drug discovery, personalized medicine, and diagnostic imaging. 

• Finance: Robo-advisors, algorithmic trading, and fraud detection systems are becoming increasingly sophisticated. 

• Automotive: Self-driving technology is advancing rapidly, with implications for car manufacturers and ride-sharing companies. 

• Retail: AI-powered recommendation engines and inventory management systems are transforming e-commerce and traditional retail. 

One would be hard-pressed to find a recent earnings call that does not mention AI in some capacity; this further illustrates that the challenge for investors is identifying companies that are meaningfully integrating AI in a value-accretive fashion, and not just “AI-signaling” its usage to make investors happy. 

Impact on the Job Market and Economic Growth

AI is reshaping the job market profoundly. While there are concerns about job displacement, particularly in routine cognitive tasks, AI is also creating new job categories and driving demand for skills in data science, machine learning, and AI ethics. A recent report by the World Economic Forum predicts that while AI may displace 85 million jobs globally by 2025, it could also create 97 million new roles[5]. This shift is likely to accelerate the trend towards lifelong learning and reskilling in the workforce. Additionally, from an economic growth perspective, AI has the potential to significantly boost productivity. PricewaterhouseCoopers (PwC) estimates that AI could add $15.7 trillion to the global economy by 2030[6]. This growth is expected to come from increased productivity, personalization of products and services, and time savings for consumers.

Projected Impact of AI to the Global Economy

Figure 2. Source: PricewaterhouseCoopers*

Challenges and Risks Associated with AI Adoption

Despite its potential, the rapid adoption of AI in finance is not without risks. The European Central Bank (ECB) warns that widespread AI adoption may increase operational risks, including potential market concentration, increased cyber risk, higher likelihood of herding behavior, and greater market correlation[2]. Other commonly discussed challenges surrounding AI are: 

• Algorithmic bias: AI systems can perpetuate or even amplify existing biases in financial decision-making, potentially leading to unfair lending practices or investment decisions. 

• Cybersecurity concerns: As financial systems become more reliant on AI, they may become more vulnerable to sophisticated cyber-attacks. 

• Regulatory challenges: Regulators are struggling to keep pace with AI advancements, raising questions about accountability and transparency in AI-driven financial decisions. 

• Market volatility: The IMF notes that AI-powered trading systems can potentially exacerbate market swings, leading to increased volatility. 

• Job displacement: While new jobs are being created, the transition may be challenging for many workers, potentially leading to short-term economic disruptions. 

However, the Commodity Futures Trading Commission (CFTC) also highlights AI's potential benefits, including mitigating human error, countering human biases, improving financial system inclusivity, and streamlining customer onboarding[7].

Conclusion

The AI revolution is fundamentally altering the financial landscape, creating new investment opportunities while also posing significant challenges. As AI continues to evolve, it will likely lead to more efficient markets, personalized financial services, and new economic growth drivers. For investors, staying informed about AI developments and their potential impacts across various sectors will be crucial for making sound investment decisions. However, it will also require investors to grapple with complex ethical, regulatory, and economic challenges.

Sources (*including source data for graphic illustrations in blog):

[1] Source: International Monetary Fund, October 2024

[2] Source: European Central Bank, May 2024

[3] Source: JPMorgan Chase May 20, 2024

[4] Source: Evident Insights, April 2024

[5] Source: World Economic Forum, October 26, 2020

[6] Source: PricewaterhouseCoopers, 2017

[7] Source: Commodity Futures Trading Commission, October 2019

[8] Source: Evident Insights, July 2023

Disclosures

Canterbury believes that the information contained herein is accurate and/or derived from sources which are reliable, but Canterbury does not warrant its accuracy or completeness. Canterbury has no obligation (express or implied) to update any or all the information contained herein or to advise you of any changes. The drivers of any technology as well as its effect on economic conditions are complex. The blogpost does not aim to provide accurate or complete description of its dynamics. To the extent any information herein constitutes "forward-looking statements" (which can be identified by the use of forward-looking terminology such as "may", "will", "should", "expect", "anticipate", "upside", "potential", "project", "estimate", "intend", "continue", "target", "pending" or "believe" or comparable terminology), please note that, due to various risks and uncertainties, actual events, results or performance may differ materially from those reflected or contemplated in such forward-looking statements. Any forward-looking statements are for illustrative purposes only and are not to be relied upon as predictive of any specific economic or financial outcome.  The blog is for informational purpose only and not to be construed as a recommendation to invest in any specific security or strategy.  It is not to be seen as a solicitation to engage Canterbury for its consulting services.

As a member of Canterbury’s Research Group, Mr. Sorenson is responsible for aiding in the evaluation, due diligence, and monitoring of private capital and public market investment managers. Prior to joining Canterbury full-time, Mr. Sorenson completed Canterbury’s investment research internship program. Mr. Sorenson holds a Bachelor of Science in finance from California State University, Long Beach. While at California State University, Long Beach, he gained hands-on experience in security analysis and portfolio management as part of a one-year honors program called Beach Investment Group.