Riding the wave of AI investing — here's what you need to know

Why is artificial intelligence (AI) attractive to investors now?

Lately, there has been plenty of buzz and hype around certain artificial intelligence (AI) and technology stocks. Tech giants are racing to develop new AI capabilities. Generative AI tools in particular — such as ChatGPT and DALL-E — are seeing rapid advances and can create a huge range of content such as text, images, videos, and audio. These AI systems can now brainstorm ideas, write resumes, come up with jokes, generate computer code, summarise articles, draft up complex business proposals, and much more.

Such developments have the potential to revolutionise industries, boost productivity and efficiency, increase the rate of innovation, and transform the way many jobs are performed. More research studies are now showing how AI can help increase productivity in certain tasks or jobs.

Given the surging interest in this field, many companies — including those beyond the technology industry — are expected to benefit from the AI theme.

Large tech companies such as Microsoft, Alphabet, and Nvidia have been direct beneficiaries of the surge in AI demand. Microsoft and Alphabet have incorporated generative AI across a broad selection of services and increased their average revenue per user (ARPU) as more people utilise the tools to boost productivity. Meanwhile, chipmakers such as Nvidia make specialised chips to train large-scale AI models such as ChatGPT.

Beyond technology names, many industries that use AI to boost productivity are expected to improve earnings and margins. In a recent report, Goldman Sachs said it expects generative AI to raise US labour productivity by 1.5 percentage points per year over a decade.

However, even as AI transforms the way we learn, work, and live, it’s important to also note that it is not without risks. Using such nascent technologies can have ethical implications and may potentially cause major disruptions in labour markets, as experts have warned.

How can Singapore investors get exposure to AI stocks?

There are essentially a few ways for Singapore investors to gain exposure to equities related to the artificial intelligence (AI) theme:

• Single stocks: Buying shares of an individual company on a stock exchange
• Funds: Buying a fund — which may either be an exchange-traded fund (ETF) or a unit trust — that is invested in multiple stocks
• Advised portfolios: Investing in an advised portfolio that has a selection of funds curated by experts

Investing in a fund, such as a unit trust or ETF, allows investors to ride the wave of the AI boom while limiting exposure to the specific risks of a single company, and can offer diversification benefits at a low cost.

While it can be tempting to jump on the AI bandwagon, we encourage retail investors to exercise caution and carefully consider the risk and reward. Many of these technology stocks have experienced recent spikes in their share prices, and valuations are sky high.

Investors in Singapore who have a keen interest in this emerging trend can consider accessing AI themes through globally diversified funds that consider companies in the entire supply chain holistically — as opposed to investing only in companies with direct exposure to the theme. 

At Endowus, we advise our clients to take a long-term view and avoid unnecessary concentration risk. Investing in a portfolio of stocks that are positioned to benefit from the AI ecosystem is the best way to avoid the rollercoaster ride of ups and downs as well as the higher volatility that comes with betting on only a handful of stocks.

How should I start investing in artificial intelligence?

The best place to start is to invest in an expertly-curated portfolio with globally diversified funds that has AI as one of its main themes, without an overly concentrated weightage in just that one sector.

For example, the Endowus Technology Portfolio gives investors in Singapore access to the most innovative companies around the world. Designed by the Endowus Investment Office, it offers a curated selection of best-in-class tech funds in a multi-manager portfolio, with the expertise, scale and proven track records in identifying opportunities across key technology themes such as AI, robotics, digitalisation, blockchain, and more. 

This provides more systematic diversification benefits for investors to take advantage of higher long-term returns from exposure to the leading tech companies globally.

Underlying funds of the Endowus Technology Portfolio

Ideally, investors who are keen on AI should look for a portfolio that places focused, strategic allocations on core technology sectors, as well as non-traditional technology sectors. These include companies that perhaps do not originate from the industry, but will leverage technology to enhance their competitive advantage within their specific sectors and create long-term shareholder value. 

That is also a key trait of the Endowus Technology Portfolio, which strives to give investors exposure to private tech companies in the growth stage, before they list in public markets. This will give the broadest exposure to a diverse basket of companies to generate higher, long-term returns. 

It is also important to understand the fees associated with any investment product. High fees inadvertently eat into your returns. Endowus works with the global leaders in technology investing to offer clients a lower net fee on such funds, via access to the institutional share classes or 100% rebate of trailer fees as Cashback, with no hidden sales charges. 

Portfolio allocation of the Endowus Technology Portfolio

Are ETFs the best way to invest in AI?

If you prefer to buy single funds with AI or tech exposure to customise your ideal investment portfolio, you may now be thinking whether unit trusts or exchange-traded funds (ETFs) may be more suitable for you. 

Put simply, the biggest difference between unit trusts and ETFs is their listing status. ETFs are listed on a stock exchange and therefore they trade throughout the day (intraday) like a stock does, which means investors are subject to volatility in the bid and ask price. If an ETF has low liquidity, the bid-ask spread can be quite large, even exceeding the expense ratio (fees) of the fund itself. In such cases, investing in an ETF can become costly. 

By comparison, unit trusts — also known as mutual funds in the US — are not listed, and they trade once a day at a specific net asset value (NAV). The NAV takes into account the trading costs associated with the index fund on that specific day. This is why it is less complicated to invest in unit trusts compared with ETFs — the investor does not have to consider bid-ask spread costs. To learn more about the general differences between unit trusts and ETFs, refer to this article.

When it comes to ETFs, it is even more imperative that investors do their due diligence to find out which index or stocks the ETF is tracking, and how the index is being constructed. The potential downside to ETFs is that they may not offer enough exposure to artificial intelligence (AI), and some ETFs may also be too focused on a narrow subset of companies.

Besides ETFs, actively managed unit trusts are another diversified way to access the AI theme. These actively managed funds typically invest in companies that benefit from the developments because they provide AI infrastructure, produce applications that make use of AI, and/or are in industries that are poised for disruption because of AI.

Retail investors in Singapore can invest in unit trusts with their Cash, SRS, or CPF savings on the Endowus Fund Smart platform. Click here to browse our investment funds list — if you wish to filter for only technology funds, please select “Technology” under the Equity Sector.

Here are some key unit trusts or mutual funds that have AI exposure:

Note that the table above is a non-exhaustive list. There is a wide, and growing, range of investment funds offering varying amounts of exposure to AI or technology-related stocks. Furthermore, the universe of AI-related stocks will continue to expand as more technology companies develop AI capabilities, and as the adoption of AI becomes increasingly widespread — with many companies outside of the technology sector finding ways to incorporate it in their operations and businesses.

For more on how investors can approach artificial intelligence and technology, check out our Q&A with Franklin Templeton, or watch the replay of our webinar hosted by Endowus Chief Investment Officer Samuel Rhee.

AI buzzwords explained

Want to learn more about the world of AI? Here’s a quick guide to the definitions of some commonly used terms.

• Artificial intelligence: A non-human program or model that simulates or mimics human intelligence, and can solve sophisticated tasks. AI features can include human-like communication or decision making.
• Algorithm: A set of rules that a machine can follow to learn how to do a task. An algorithm may be able to perform calculations, process data, and automate reasoning.
• Chatbot: A computer program or an AI designed to interact with human users through conversation from text or voice commands.
• Deep learning: A function of AI that imitates the human brain by learning from the way data is structured, rather than from an algorithm that is programmed to do a specific task.
• Generative AI: Deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on.
• Large language models (LLMs): A deep-learning algorithm that can recognise, summarise, translate, predict, and generate text and other types of content based on knowledge gained from massive datasets.
• Machine learning: A subfield of AI that often uses statistical techniques to give computers the ability to “learn” — that is, progressively improve performance on a specific task, with data, without being explicitly programmed.
• Natural language processing (NLP): Techniques used by large language models to understand and generate human language, including the person’s intent and sentiment. NLP technologies enable computers to process human language in the form of text or voice.

Explore our Fin.Lit Academy for a free, curated repository of expertise on investment fundamentals, wealth building, and personal finance.

Investing with a core-satellite approach

The Endowus Technology Portfolio is part of our Satellite offerings, which are used to supplement Core portfolios such as the Endowus Flagship Portfolio.

Satellite portfolios are meant to express an active decision by the investor to provide further diversification opportunities to try to generate alpha (above market returns), or to express a specific investment view or strategy. This can be done through a single fund or a portfolio of funds. 

Here’s how satellite strategies differ from that of core portfolios:

• They tend to be more concentrated in nature and narrow in exposure, targeting a certain sector or country or theme, as compared to the passive broad market exposure of core portfolios.
• While they may follow an index and can be passive, most satellite portfolios and funds tend to be active in the way they invest and seek to generate alpha.
• The investments tend to be shorter term in nature and reflect tactical or opportunistic investment strategies, as opposed to the strategic nature of core investments. 

Meanwhile, a core asset allocation should always anchor any investor’s asset allocation strategy and investment portfolio. The Core portfolios are used to provide long-term, stable market returns, growing your wealth with the power of compounding over the long term.

The Endowus Flagship Portfolio has been the most popular solution among our clients who are starting their investment journeys, as investing is made simple, fair, transparent, and low-cost for you. Read more about the portfolio here.

To start investing your Cash, SRS, or CPF savings with Endowus, follow this link. 

Read more:

• Webinar replay: Does ChatGPT herald a new era for AI and tech investing?
• The age of artificial intelligence
• Artificial intelligence and technology investing — Q&A with Franklin Templeton

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