What is the “AI” hype all about?

Key Takeaways

• 1. Adoption of generative Artificial Intelligence (AI) has increased with significant investments made as businesses have recognised the potential for generative AI to improve efficiency.
• 2. Investors looking to tap into the structural growth opportunities presented by the increasing adoption of generative AI can consider doing so through stocks, ETFs and mutual funds.
• 3. However, with the strong rally in AI stocks in the past few months, it pays to take a more measured approach, including using a dollar-cost average strategy to smooth out near term price volatility.

AI has been the buzzword amongst investors since the launch of ChatGPT late last year when the AI chatbot took just five days to reach 1 million users. Based on Google search trends, the level of interest in AI has reached unprecedented levels over the past 20 years.

The hype about AI, which stands for Artificial Intelligence, is centred around the incredible potential it holds to transform various aspects of our lives and industries. AI is seen by some as a revolutionary technology with the capability to perform tasks which require human intelligence in the past, such as problem-solving and decision-making.

If you are new to AI, it is a broad term that refers to the development of computer systems that can perform tasks that typically require human intelligence. It encompasses various techniques and approaches, including machine learning, natural language processing, computer vision, robotics, and more. The main goal of AI is to create intelligent systems that can learn from data, adapt to new situations, and make decisions based on the knowledge acquired.

On the other hand, generative AI is a subset of AI that focuses specifically on creating new and original content rather than simply analysing existing information. It's like having a super creative and imaginative assistant! Instead of only answering questions based on what it already knows, generative AI can actually generate new and original content.

Imagine this. You have a generative AI model that has been trained on a massive amount of text, images, or other types of data. Once trained, this AI model can take that knowledge and produce new text, pictures, or even sounds that it has never seen before. This is effectively a large language model (LLM), which acts as the system behind ChatGPT.

How is generative AI used?

While the real-world usage of the metaverse is debatable, generative AI has found more practical uses across the personal and business spheres.

Planning a trip abroad and looking for a customised itinerary? Generative AI can be used to personalise your itinerary, just like how it has been used for product recommendations and marketing campaigns to enhance user experiences.

For content creators, generative AI can be used to create new and original art, music, or creative writing. It has been applied to produce realistic images, design logos, and even compose music. Generative AI can create natural-sounding speech and even mimic specific voices, which can be used in voice assistants, audiobook narration, and voiceovers.

In business, chatbots powered by generative AI can engage in more human-like conversations and provide personalised responses based on user input, making them more effective virtual assistants Within the financial sector, generative AI combined with business intelligence could be used to simulate various financial scenarios, generate new investment strategies, or even create realistic stock market trends based on historical data.

What is driving the explosive growth in generative AI?

So what is driving all the excitement about generative AI, and why is it only happening now?

Businesses and industries have recognised the potential of generative AI to solve complex problems and improve efficiency, and have invested more resources into it. According to a report by McKinsey & Company in 2019 , the world invested $39 billion in AI, and by 2025, it is anticipated that this amount will increase to $150 billion. In the same survey, 63 per cent of respondents reported an increase in revenue from AI adoption in the business units where the companies use AI.

In addition, the availability of huge datasets and increasingly sophisticated hardware have also facilitated the growth of AI. The success of generative AI models heavily relies on the availability of large and diverse datasets for training. With the exponential growth of data and the ease of data collection, there is a wealth of information that can be used to train these models effectively.

Training sophisticated generative AI models requires significant computational resources. The development of powerful GPUs (Graphics Processing Units) and other specialized hardware has made it feasible to train large-scale AI models much faster and more efficiently.

What opportunities are present for investors?

Investors looking to tap into the structural growth opportunities presented by the increasing adoption of generative AI can do so through single stocks or ETFs and mutual funds.

Those who can identify individual companies that are at the forefront of AI development can consider single stock investments. This may include established companies that are investing heavily in AI research and development, such as the US tech giants.

As AI requires robust hardware for processing large amounts of data, companies that provide hardware used in AI, such as GPUs (Graphics Processing Units) or AI chips may also benefit. Citi Global Investment believes that there will be investment opportunities for companies that facilitate its infrastructure, such as hardware manufacturers and cloud computing vendors.

Investors looking at a diversified portfolio of stocks exposed to the AI theme can consider ETFs and mutual funds. This would include funds that are focused on technology, robotics, or AI themes.

Should investors invest in AI?

Undoubtedly, AI has the potential to drive significant productivity gains and accelerate global growth. According to estimates by McKinsey, generative AI could add US$2.6 trillion to US$4.4 trillion annually to the global economy. This is equivalent to the size of the United Kingdom’s economy in 2021.

That said, the share prices of AI-related stocks have surged significantly over the past year. For example, the share price of AI chipmaker Nvidia has more than tripled in the first half of 2023, causing its market capitalisation to exceed US$1 trillion. This has also helped to boost the tech-heavy Nasdaq index, which rose by close to 32% over the same period.

Such exuberance has led to concerns about an AI ‘bubble’ forming. This was a view shared by Charlie Munger, who said that “I’m personally sceptical of some of the hype that has gone into artificial intelligence”.

Investors who are keen to get exposure to the structural theme of AI can consider taking a dollar-cost average approach rather than investing in the sector in a lump-sum manner. This may allow investors to tap into the growth potential over the long-term while smoothing out near-term share price fluctuations, especially with the strong rally year-to-date.

What would Beansprout do?

Generative AI is a technology that opens up exciting possibilities across various industries, including finance. It enables the creation of new and original content, leading to innovative insights and solutions that can benefit both individuals and businesses.

As with any powerful tool, there are challenges with generative AI. To ensure that the deployment of AI is ethically responsible and prevent any potential bias, company policies may need to be updated to take into account the growing adoption of AI. At the same time, human intervention may also be required to make sure that the generated content is accurate and reliable. What this means is that human intelligence and business intelligence need to be combined with AI for a more customer centric outcome.

Investors can look for stocks or funds relating to companies investing significantly in AI, producers of AI chips and cloud computing vendors to gain exposure to the structural growth of AI adoption. However, with the strong rally in AI stocks in the past few months, it pays to take a more measured approach, including using a dollar-cost average strategy to smooth out near term price volatility.

This research is commissioned by Citi in collaboration with Beansprout, an MAS-licensed platform offering individuals simple financial guidance.

Gerald Wong, CFA, has more than 10 years of experience in the investment advisory industry, and is passionate about helping others make better investment decisions.

Sources

1. McKinsey & Company. (2019, November 22). Global AI survey: Ai proves its worth, but few scale impact. McKinsey & Company.
https://www.mckinsey.com/featured-insights/artificial-intelligence/global-ai-survey-ai-proves-its-worth-but-few-scale-impact

2. Chui, M., Hazan, E., Roberts, R., Singla, A., Smaje, K., Sukharevsky, A., Yee, L., & Zemmel, R. (2023, June 14). The economic potential of Generative AI: The Next Productivity Frontier. McKinsey & Company.
https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier

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