The AI Revolution: Making Sense of Artificial Intelligence for Investors

Artificial Intelligence (AI) may seem brand new and novel, but scientists have been developing AI since the early days of computing in the 1940s and 50s. It’s only been over the last two years that the public has really started paying attention. In November 2022, ChatGPT – the popular program that allows people to interact conversationally with AI – was unleashed on the world, capturing everyone’s imagination, including investors.

Since then, billions have poured into the AI sector from venture capitalists, private equity firms and average investors, with some AI-related stocks seeing significant growth over the last couple of years. Research by Bloomberg Intelligence¹ found that generative AI – the ChatGPT-style of AI that people can interact with to produce text, images and audio, among other things – could become a $1.3-trillion market by 2032, growing at a compound annual rate of 42% over the next 10 years.

But as wide-eyed as everyone may be about the future of AI, it’s still unclear exactly how this technology will impact the world and which businesses will come out ahead. That makes it challenging for investors to know how to approach this sector.

“The industry is really moving quickly, and some of these models are mind-blowing,” says Marcello Montanari, RBC Global Asset Management’s managing director and senior portfolio manager of North American Equities. “But the thing is, nobody really knows where it’s going to go.”

What is AI’s potential?

There are massive expectations for AI, however, and most experts do agree that it will have a profound impact on society. “The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone,” Bill Gates wrote on his blog² in 2023. “It will change the way people work, learn, travel, get health care, and communicate with each other. Entire industries will reorient around it. Businesses will distinguish themselves by how well they use it.”

According to McKinsey research³, generative AI alone could add between US$2.6 trillion and US$4.4 trillion annually to the global economy in the near term. “In fact, it seems possible that within the next three years, anything not connected to AI will be considered obsolete or ineffective,” one McKinsey report noted. Similarly, PwC analysis⁴ estimated that AI could contribute up to US$15.7 trillion to the global economy in 2030, more than the current economic output of China and India combined. The International Monetary Fund⁵ has said that AI will affect almost 40 per cent of jobs around the world, replacing some and complementing others.

Montanari adds that despite people’s uncertainty about how the AI industry will unfold, “we are seeing the power of this and realizing we’re now in a completely different tech paradigm.”

Some industries are starting to realize the potential of this technology. Within the healthcare sector, generative AI is being used in drug discovery⁶ with scientists now able to study millions of biological data datasets to see how different medications might interact with one another. In the aerospace industry, AI is studying weather patterns⁷, air traffic control data, carbon emission outputs and more to find more optimal travel paths. At an employee level, staff are asking AI to find ways to improve a process⁸, which can then slash the amount of time they must spend on a task.

“The productivity gains that we’re probably going to see from this are going to be immense,” says Montanari. “And when different technologies come together to form something new, you get real breakthroughs.”

Decoding the AI sector

One challenge for investors is understanding all of the parts that make up the AI industry – and there are many. Montanari divides the investment opportunity into two key categories: enablers and deployers.

“Enablers” includes the many businesses creating the infrastructure for AI—“You might call them the picks and shovels,” he says. That includes tech giants: massive technology companies that spend billions of dollars every quarter developing AI solutions for their clients, their employees, and the broader population. Some of these companies also provide the virtual infrastructure that most AI solutions must run on.

Then there are the companies that make the semiconductors, servers, optical networks, data management capabilities and cooling required to operate an ever-expanding number of data centres. Recently, Jensen Huang, CEO of Nvidia, the popular semiconductor chip maker that’s benefited from interest over the last two years, said the amount invested in data centres will double to $2 trillion in the next five years⁹.

AI also requires massive amounts of electricity to operate. According to Goldman Sachs¹⁰, one ChatGPT query needs, on average, 10 times as much electricity to process as a Google Search. It estimates that demand for data centre power will grow 160% by 2030. Today, data centres consume about 1% to 2% of overall power, but that will jump to as much as 4% over the next six years. That means the companies that provide electrical power, such as utilities and transformer manufacturers, and those that create materials like copper, will benefit from AI’s growth.

The “deployers” category centres around the many operations that will benefit from AI, such as financial institutions, healthcare organizations, manufacturing companies and more. These businesses could become more efficient, productive and innovative. 

“They will benefit when AI is deployed into the broader economy,” he says. “They’re companies that are sitting on vast quantities of proprietary data that can be used to train specialized models or algorithms. Once trained, these models can be applied to improve or automate various business processes.

How far does AI have to go?

If you are interested in this sector, you should be aware the world-changing applications many people are waiting for are taking longer to develop than some had hoped.

“My biggest concern has been that the market gets a little bit too enthusiastic about AI solutions hitting the market very soon, because these things take time,” says Montanari. “In the vast majority of cases, we’re still in the prototyping period.”

Several prominent Wall Street analysts have recently raised concerns about the large gap between revenue expectations implied by the investment in AI infrastructure, and the actual revenue growth in the AI ecosystem. David Cahn at popular venture capital firm Sequoia Capital¹¹ calls this the “$600 billion question.”

Still, most think the AI revolution will come. But because of the vastness of the AI landscape, and the fact that it’s still early days, Montanari stresses that it’s challenging to pick winners and losers in this race.

“As the market evolves rapidly, we take a basket approach with a well-diversified selection of names we think will ultimately be winners,” he says, adding that “we don’t expect to be right with all of our picks. This is an iterative process.”

Like with any investment, it’s crucial to do your due diligence, consider the fundamentals, and stay on top of fast-moving developments.

All images in this article were created in Adobestock's Firefly. Generative AI was used to translate the words, "What artificial intelligence means for investing in stocks."

¹ _{Source: Bloomberg Professional Services, "Generative AI 2024 Report"}

² _{Source: GatesNotes, "The Age of AI has begun", March 2023}

³ _{Source: McKinsey & Company, "Beyond the hype: Capturing the potential of AI and gen AI in tech, media, and telecom", February 2024}

⁴ _{Source: PwC, "Global Artificial Intelligence Study: Sizing the prize"} 

⁵ _{Source: IMF Blog, "AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity.", January 2024}

⁶ _{Source: National Library of Medicine, "Artificial intelligence in drug discovery and development", October 2020}

⁷ _{Source: The New York Times, "Artificial Intelligence Gives Weather Forecasters a New Edge", July 2024}

⁸ _{Source: MIT Management Sloan School, "How generative AI can boost highly skilled workers’ productivity", October 2023}

⁹ _{Source: Reuters, "Data centre boom reveals AI hype’s physical limits", July 2024}

¹⁰ _{Source: Goldman Sachs, "AI is poised to drive 160% increase in data center power demand", May 2024}

¹¹ _{Source: Sequoia Capital, "AI’s $600B Question", June 2024}