Artificial Intelligence

Artificial intelligence ("AI") continues to bridge the separation between machine and human intelligence, led by substantial advancements in generative AI such as Large Language Models.
Artificial intelligence has the potential to add trillions to global economic growth, with broad influence across all sectors of the economy. Productivity gains are likely to be driven by gains in labour productivity, although labour displacement is also likely.
The Artificial Intelligence value chain for investment can be broadly grouped into three main categories: 1. Data collection, 2. Computing power, and 3. Use cases.
Geographic and regulatory landscapes for artificial intelligence are rapidly evolving, in some cases hindering AI growth in particular areas or geographies but in many cases helping to drive forward innovation through competition.
Aligning investments to capture AI growth can help investors participate in the transformative potential of Artificial Intelligence.

As Artificial Intelligence (“AI”) capabilities continue to evolve, the separation between machines and human intelligence is becoming less clear, paving the way for AI to fulfil functions traditionally limited to humans or requiring human input and oversight. Currently, advancements in generative AI are reshaping how AI can replicate human behavior through the origination of text, image, and audio content that are increasing indiscernible from human-generated content. For instance, OpenAI’s GPT model can effectively converse in human-like text, making general connections across vast knowledge domains and almost instantaneously answering queries or prompts across a broader scope than previously thought possible.

Experts believe AI growth has the potential to dramatically increase capital efficiency, with the potential to add trillions to economic growth and to shift human labour away from mundane, repetitive tasks. The collection, analysis, and even creation of data has sweeping application across economic and social landscapes. Sceptics, however, caution against the potential unintended consequences of AI, ranging from mass unemployment and increased wealth inequality to infringement on privacy and other personal liberties. What is inarguable is the increasing importance of AI in our daily lives.

In this paper, we will explore and define the broad categories of AI, illustrating real-life examples of AI application across industries. For investors, considering the effects of AI development on the investment landscape is an important consideration to investing strategically. Thus, we outline the pillars of AI within the public equity universe and how business profitability might be shaped by AI going forward. We then discuss the investment landscape across the AI value chain, which we view in three broad categories: 1. Data collection, 2. Computer power and 3. Use cases. Finally, given the important economic, moral, and ethical questions that AI growth brings about, we highlight the current geographical and regulatory landscape for AI integration.