Global investing and the AI opportunity
IN Partnership with
Featuring Capital Group equity portfolio manager Jeremy Burge and equity investment specialist Kathrin Forrest on critical investment opportunities in AI
More
AS ARTIFICIAL INTELLIGENCE takes the investment world by storm, a growing number of investors are wondering how to take advantage of it, beyond poster child Nvidia and other tech superstars in the Magnificent Seven.
“AI is creating opportunities for companies well beyond the big, early winners,” says Jeremy Burge, portfolio manager at Capital Group Global Equity Fund (Canada).
Fundamentally, AI has the potential to help workers become more efficient and businesses more productive across all sectors of the market, all industries, and all regions of the world. What’s more, the implementation and economic impact of AI may occur faster than technological innovations in the past because AI is software-based and can be rolled out quickly on the internet.
Established in 1931 in Los Angeles, California, Capital Group’s mission has always been to improve people’s lives through successful investing. As one of the world’s largest active asset managers,* we strive to use our extensive global footprint to provide unique investment insights to our clients, consistent with our belief in the transformative power of partnership.
Our culture and values are at the heart of our enduring goal of delivering for our clients. The focus on robust analysis based on fundamental research and the diverse points of view of our long-tenured portfolio managers, combined with mutual respect and collaboration, is embodied in our distinctive investment approach. We call it The Capital System™, and, along with our industry-leading thought leadership, it’s helped people build the financial freedom to pursue their dreams.
Find out more
“The key as fundamental investors is to get into the nuance and ask the right questions: Which parts of the value chain are poised to benefit, and in what order? Who’s going to be hurt? And which companies stand to benefit from secondary and tertiary knock-on effects?”
Jeremy Burge,
CAPITAL GROUP EQUITY PORTFOLIO MANAGER
As the market matures, a deep, growing set of investment opportunities is emerging up and down the value chain.
“The key as fundamental investors is to get into the nuance and ask the right questions: Which parts of the value chain are poised to benefit, and in what order? Which geographies are going to be farther ahead or behind on adoption? Which companies are poised to lead as critical suppliers or makers of the necessary tools and equipment? Who’s going to be hurt? And which companies stand to benefit from secondary and tertiary knock-on effects?” says Burge.
The most immediate investable opportunity has been concentrated in the compute segment related to the AI build-out. Constituents are semiconductor chip designers, equipment manufacturers, foundries, and other highly specialized companies. Not surprisingly, many of these companies are already big stock market winners: Nvidia is a prime example, designing GPUs that have seen a surge in demand from companies that look to build and train AI models. Capacity for compute businesses is difficult to scale quickly given capital intensity and specialization within highly connected global supply chains.
Going beyond this first layer, we anticipate investment opportunities across a broader set of “picks and shovels” equipment providers. This may include complements, such as semiconductor equipment makers (Applied Materials),
chip foundries (TSMC), suppliers of memory chips (SK Hynix), and server makers able to meet artificial-use cases (Dell). We may also see chip alternatives emerge – “x”PUs with distinctive features such as higher specialization, lower cost, or higher electricity efficiency (Broadcom).
“Other opportunities may be in the ecosystem of companies that provide specialty chemical solutions,” adds equity investment specialist Kathrin Forrest.
The rapidly growing infrastructure segment also offers potential. It’s primarily made up of cloud companies, data centres, and networking firms – all necessary enablers making AI possible. Due to the explosive growth in AI, global spending on data centre construction is expected to reach US$49 billion by 2030, according to McKinsey & Company. This may benefit equipment suppliers beyond compute.
Further, the centres have enormous power needs, which is favourably affecting electricity providers, both traditional and renewable. In June of last year, Constellation Energy, one of the largest electricity providers in the US, agreed to sell Microsoft nuclear power for its data centre in Virginia.
More recently, in January, US construction-equipment maker Caterpillar, which already has a 60 percent share of the back-up power generation market for data centres, announced a successful test of its hydrogen fuel cell technology at a centre. This, says the company, opens the door to possibly using large-format hydrogen fuel cells to supply back-up power for data centres.
“The approach to innovation, the role of regulation, ability to source scarce inputs, competitive pressures, and customer preferences all play a role creating differentiated opportunities and risks for companies”
Kathrin Forrest, CAPITAL GROUP EQUITY INVESTMENT SPECIALIST
AI models are the programs trained on a set of data to recognize certain patterns or make certain decisions without further human intervention. They require large data sets, lots of computing power, and specialized engineers. Microsoft-backed Open AI’s model is called GPT4, Meta’s is Llama, and Alphabet’s (Google’s) is Gemini, to name a few. Each of these companies has invested billions of dollars in foundation models trained on broad data, designed for generality of output and adaptable to a wide range of tasks. These types of models provide a broad set of potential opportunities for commercialization/monetization. Time will tell which companies are best positioned to benefit.
The application segment of the AI value chain may be the most exciting and broadest in terms of investment opportunities. An early example is CoPilot, now embedded in Microsoft Office for a higher subscription fee. In time, beneficiaries may span all GIC sectors, industries, and sub-industries around the world, due to the broad spectrum of potential use cases.
Share
Compute
Infrastructure
Infrastructure
Infrastructure
Published June 17, 2024
Share
About
Directories
Resources
Investments
Pensions
benefits
News
RSS
Sitemap
Privacy
Contact us
About us
External contributors
Authors
Terms & Conditions
Terms of Use
Subscribe
People
Companies
Copyright © 1996-2024 KM Business Information Canada Ltd.
About
Directories
Resources
Investments
Pensions
Benefits
News
RSS
Sitemap
Privacy
Contact us
About us
External contributors
Authors
Terms & Conditions
Terms of Use
Subscribe
People
Companies
Copyright © 1996-2024 KM Business Information Canada Ltd.
About
Directories
Resources
Investments
Pensions
Benefits
News
RSS
Sitemap
Privacy
Contact us
About us
External contributors
Authors
Terms & Conditions
Terms of Use
Subscribe
People
Companies
Copyright © 1996-2024 KM Business Information Canada Ltd.
Sources: Next Move Strategy Consulting, Statista. Years 2023 through 2030 are estimated. Data as of January 2023. CAGR = compound annualized growth rate. Dollar values in USD
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
500
1,000
1,500
2,000
B ($)
$96B
$420B
$1.8Tn
Implied CAGR 2021 to 2025
Implied CAGR 2025 to 2030
34.5%
44.8%
Value of AI market globally, 2021–30
Global AI market projected to reach US$2tn by 2030
As of December 2023.
The information provided is not intended to be comprehensive or to provide advice.
*Please note the views of individual investment professionals may vary.
As AI permeates every facet of our lives, global research depth will become even more critical
Staying focused on real investment opportunities
Infrastructure
Compute
Opportunities
Capital Group perspectives*
Current investability
- Chip designers & providers
- Foundries
- Manufacturing equipment
- Most immediate investable opportunity
- 'Picks and shovels' providers are often attractive investments
- Highly consolidated industry with significant barriers to entry
- Requires rapidly expanding information
- Cloud likely to see growth uplift
- Data ecosystem equipment providers can become very entrenched
- Cloud hyperscalers
- Datacentres
- Networking
- Oligopolistic structure; best models 'owned' by a handful of firms
- High barriers to entry
- Be wary of difficulties in commercialization and potential commoditization
- Foundational models
- Platforms
- 'Big Data' owners
Models
- Difficult to predict emergence of new companies
- Current focus on existing companies productizing AI successfully
- Look for sustainable competitive advantages, e.g. access to captive data
- Software
- IT Services
- Physical applications
Applications
- Transformational for the global economy and will likely impact all industries
- Early stages of adoption - few companies have meaningfully transformed their business
- Health care
- Financial services
- Many others
Beneficiaries
Models
Applications
In healthcare, AI is already aiding diagnostics, drug discovery, and patient care. Startups and established players are leveraging the technology to analyze medical images, predict disease outcomes, and personalize treatment plans. US-based Eli Lilly and Swiss-based Novartis have, for example, inked a deal with Alphabet’s digital biotech AI company, Isomorphic, aimed at accelerating the companies’ drug discovery processes.
Meanwhile, advertising and marketing companies are using AI to personalize ads, optimize campaigns, and predict consumer behaviour. France’s Publicis Groupe, one of the world’s largest advertising agencies, has made AI the core of its business, personalizing content, optimizing campaigns, and predicting consumer behaviour across its database of 2.3 billion profiles of people around the world.
Targeting precision
Less clear
Strong
In financials, a range of banks, insurance companies, and investment firms are starting to integrate AI into their operations using algorithms to analyze market data, optimize portfolios, and detect fraudulent transactions. JP Morgan has, for instance, rolled out a Cash Flow Intelligence AI tool to about 2,500 corporate customers to help them with forecasting. The company says the software has reduced human work in this area by 90 percent and may charge for it in future.
“The approach to innovation, the role of regulation, ability to source scarce inputs, competitive pressures, and customer preferences all play a role in creating differentiated opportunities and risks for companies,” says Forrest.
A final point regarding the AI opportunity and Global Equity is that it’s not just about picking stocks, it’s about building a portfolio – a portfolio that considers more than just one market theme and is positioned to deliver against its objectives as it seeks to provide long-term, superior results. That means a diversified, balanced approach with many opportunities.
“We need to get more than just AI right,” says Burge.
Capital Group Global Equity Fund (Canada)
Global Equity is underpinned by a distinct investment approach called The Capital System , which divides portfolios into segments, each run by an individual manager. While managers collaborate and share insights, each invests independently according to their strongest convictions. The resulting portfolios are a diverse collection of investment ideas, not just one manager’s perspective. Capital Accumulation Plan sponsors and consultants can access Global Equity via the Sun Life Core Investment Platform, the Canada Life Top Shelf Program, and by request through Manulife Investment.
For more information contact Kevin.Martino@capgroup.com, vice president of institutional for Capital Group in Canada.
* Morningstar asset flows as of February 28, 2023. Based on total net assets. Active only. Excludes money markets, fund of funds, feeder funds, and obsolete funds.
Source: Capital Group voted #1 for thought leadership by advisors in 2019, 2020, 2021 and 2023: The Advisor View, May 2023, July 2021, June 2020; Fund Intelligence, February 2020. FUSE Research surveys of 500–1,000 advisors identifying the “most-read thought leaders.” Survey was not conducted in 2022.
TM
TM
Commissions, trailing commissions, management fees and expenses all may be associated with mutual fund investments. Please read the prospectus before investing. Mutual funds are not guaranteed, their values change frequently, and past performance may not be repeated.
Capital Group funds in Canada are offered by Capital International Asset Management (Canada), Inc., part of Capital Group, a global investment management firm originated in Los Angeles, California in 1931.
Views of individual Capital Group investment professionals may vary.
IN Partnership with
TM
Find out more
Established in 1931 in Los Angeles, California, Capital Group’s mission has always been to improve people’s lives through successful investing. As one of the world’s largest active asset managers,* we strive to use our extensive global footprint to provide unique investment insights to our clients, consistent with our belief in the transformative power of partnership.
Our culture and values are at the heart of our enduring goal of delivering for our clients. The focus on robust analysis based on fundamental research and the diverse points of view of our long-tenured portfolio managers, combined with mutual respect and collaboration, is embodied in our distinctive investment approach. We call it The Capital System™, and, along with our industry-leading† thought leadership, it’s helped people build the financial freedom to pursue their dreams.
The application segment of the AI value chain may be the most exciting and broadest in terms of investment opportunities. An early example is CoPilot, now embedded in Microsoft Office for a higher subscription fee. In time, beneficiaries may span all GIC sectors, industries, and sub-industries around the world, due to the broad spectrum of potential use cases.
AI models are the programs trained on a set of data to recognize certain patterns or make certain decisions without further human intervention. They require large data sets, lots of computing power, and specialized engineers. Microsoft-backed Open AI’s model is called GPT4, Meta’s is Llama, and Alphabet’s (Google’s) is Gemini, to name a few. Each of these companies has invested billions of dollars in foundation models trained on broad data, designed for generality of output and adaptable to a wide range of tasks. These types of models provide a broad set of potential opportunities for commercialization/monetization. Time will tell which companies are best positioned to benefit.
TM
†
†