The top four ways to invest in AI
And 5 must have AI tools you need at your disposal
Look up the term intelligence and according to the dictionary you get an interesting definition:
the ability to learn, understand, and make judgments or have opinions that are based on reason.
The key term there is reason of which the dictionary goes on to further define as:
the ability of a healthy mind to think and make judgments, especially based on practical facts.
This is a rabbit hole you can continue down, as the next key term there is mind.
And the mind, as we know, enables us to think, feel, learn… and cycle back to reason.
When you really think about what intelligence is, you find yourself moving further and further away from the idea of processing and interpreting information and data towards the idea that real intelligence is about emotion, feeling and intuition.
Yes, there’s a philosophical (arguably also spiritual) element to intelligence. However, I’m of the view that part of true intelligence is also biological, unquantifiable and almost impossible to replicate.
However, the reason you’re reading this report is due to the fact we’re amid an artificial intelligence (AI) boom – or as we like to call it, the AI Collision. A period where the acceleration of AI has reached an inflection point and exponential growth is on offer as AI collides with every single industry on earth.
This leaves investors at a fork in the road.
Down one path, you can just absorb superficial information that you will regularly find in the mainstream media and technology “news” platforms.
On the second path, you can dive deeper to understand the core fabric of the AI industry, as well as the underlying developments (good and bad) and the role of AI in our world today, tomorrow and long into the future of the world for generations to come. It means rethinking your approach to your understanding of technology, philosophy, the markets and the fabric of society.
Now, that might seem intensive. It might even seem a little hyperbolic. But the reality is once you come to truly understand what AI is about, what makes it tick (so to speak) and how it’s already changed the course of history, you then start to see doors to opportunity open – which for investors, could lead to the kinds of mega-profits only dreamed about.
It’s that second pathway, the righteous pathway towards real AI understanding, that we’re on here at AI Collision. And it’s why this may be the most valuable report we will ever produce for you.
In this report, you will find four ways to prepare yourself for the AI onslaught that’s taking markets by storm. You will learn how to get ready and then act in four key ways to profit from the AI mega boom.
To get your head around the first of these, I want to take a dive into my own personal editorial archives. This takes us back a decade to when I first began coverage of the emerging AI sector…or…
Into the dusty archives
In mid-2013 I decided that I needed to write to my readers about a relatively under-the-radar stock that was the key to an immersive future that included artificial intelligence. In fact, I liked the stock so much that I even made it an official buy recommendation in December 2013. Much like I’m writing to you about your smartphone continuing AI in it today, back then I said:
Your smartphone is a computer. If you strip away the screen and look beneath there’s a bunch of pretty complex machinery whirring away. At the heart of it is the Central Processing Unit (CPU). This is important as it does a lot of the computational grunt work. But technology advances, and we demand more processing power from our devices. The humble CPU has its limitations. It simply runs out of puff.
That’s why the CPU’s best buddy is the Graphics Processing Unit (GPU). The GPU has the ability to process memory much faster than a CPU. So, when you’re looking at the crystal-clear visuals on your smartphone, it’s really the GPU that’s making it happen. Or you might be watching a movie on the computer, again it’s the GPU that’s key to making it all happen smoothly.
As the world expects more complex interaction with everything, more responsibility is falling onto the shoulders of the GPU.
At the time the stock had a price of $15.96. Adjusted for a 4-for-1 stock split in July 2021, that put the entry price at $3.99.
Today the stock had undertaken another stock split (10-for-1) and with a stock price now around $120 that equates to over 29,975% return in a decade.
The stock, by the way, was Nvidia.
I’m telling you this for a few reasons.
Humblebrag.
The situation now hasn’t changed all that radically from then to now.
If you understand how things work, you get a better understanding of where the opportunities lie.
I’m no fortune teller. But what I saw in 2013 with Nvidia is the same kind of thing I see now when I look at developments in AI. It’s knowing how to break down an idea into its simplest form, down to the materials and metals needed to make technology, that helps investors to uncover the biggest and best opportunities.
You don’t need an engineering degree; you don’t need to be a rocket scientist or brain surgeon. You just need to take a rational, logical, committed approach to understanding a mega trend and how it works to uncover the biggest and best investment opportunities.
Once you can do that, then you can use the tools I’m about to tell you about and take a strategic approach to investing – and then potentially prof from that mega trend… which in this case is the AI revolution.
If you’ve committed to this investment idea, and you are hungry to know what to do next, the good news is that there are four ways, in my view, that maximise your potential to profit from the AI Collision and the first of those is to buy into the theme itself…
#1: Invest in the idea
When it comes to investing in AI from a high-level position, one effective way is through thematic exchange-traded funds (ETFs). That means a basket of stocks that is focused on the AI sector which you can easily invest in through one ETF.
Why would you look at using an AI ETF to invest in this opportunity?
Diversification
Thematic ETFs offer investors exposure to a diversified portfolio of AI-related stocks. This is a smart first step as it helps to reduce risk you find when investing in individual companies. AI is a fast-paced, agile industry. Individual companies can be highly volatile. ETFs mitigate this risk by investing in a basket of stocks across various AI-related companies, such as chip manufacturers, software developers and even robotics firms.
Liquidity
ETFs are traded on stock exchanges and typically invest in highly liquid stocks. Therefore, they are also typically highly liquid investments on the market. This means investors can easily buy and sell ETF shares at market prices throughout the trading day. This provides flexibility and easy access to AI-themed investments, as well as ease of exit should the idea break down.
Cost effective
Typically, ETFs have lower expense ratios compared to actively managed mutual funds. This cost efficiency can enhance the overall returns for investors, as less money is lost to management fees.
Transparency
ETFs disclose their holdings daily, allowing investors to know exactly what assets they own. This transparency is valuable for those who want to understand the underlying companies and sectors within the AI theme.
Accessibility
ETFs are accessible to both individual and institutional investors, making them an inclusive investment option. Investors can purchase ETF shares through brokerage accounts, like buying individual stocks.
Hang on a second…
Before you get too thrilled about the idea of an AI thematic ETF, you should also know something else.
While a basket of stocks focused on a specific theme can be a good overall exposure and mitigate some of the risk of individual stocks, it also means returns tend to get “smoothed”.
For example, if a thematic ETF invests in an equally weighted basket of ten companies and Company 1 rises by 50%, the ETF return is based on all ten companies. So, if the nine other companies only rise by 5% each, then the ETF would expect to rise by 9.5% considering the return of all positions.
Likewise, you could have nine companies doing great and one company doing horrible, which effectively operates as a handbrake on the overall ETF return potential.
So, while a good idea, you need to be aware of how ETFs work and if they fit in with the part of your portfolio you’re looking to allocate to this opportunity.
AI-focused ETF examples
The Global X Robotics & Artificial Intelligence ETF (BOTZ)
BOTZ seeks to provide investment results that generally correspond to the performance of the Indxx Global Robotics & Artificial Intelligence Thematic Index. It includes companies involved in the development, production and application of AI and robotics. BOTZ’s holdings encompass industry leaders like Nvidia, Intuitive Surgical and C3.ai.
ARK Autonomous Technology & Robotics ETF (ARKQ)
Managed by ARK Invest, ARKQ aims to track the performance of the ARK Autonomous Technology & Robotics Index. This ETF focuses on companies at the forefront of AI, autonomous vehicles, 3D printing and automation. ARKQ’s holdings feature prominent names such as Tesla, Teradyne and Deere & Co.
iShares Robotics and Artificial Intelligence ETF (IRBO)
IRBO seeks to track the investment results of the NYSE FactSet Global Robotics and Artificial Intelligence Index. This ETF offers exposure to companies involved in AI, robotics and automation technologies. Its holdings include companies like Splunk, Nvidia and Intel.
What next?
Investing in AI-themed ETFs provides an efficient and diversified way to tap into the potential of AI. These ETFs offer diversification, liquidity, cost-effectiveness, transparency and accessibility. This makes them a suitable choice for both novice and experienced investors.
By looking at ETFs like BOTZ, ARKQ and IRBO, investors can align their portfolios with the rapidly evolving AI landscape, potentially reaping the rewards of this transformative technology.
However, as with any investment, it is crucial for investors to conduct thorough research and consider their financial goals and risk tolerance before investing in AI-focused ETFs.
#2: The titans of AI
If thematic ETFs are one way of investing in AI – then another that you should get familiar with is the large and mega-cap section of the AI market.
If you want to build yourself a mini-AI-portfolio within your existing overall investment portfolio, then you should look at a couple of the mega-cap players in this space. These will provide an element of predictability for this investment idea.
By homing in on a couple of these giants of AI, you’re looking to specifically tap into their distinct advantages such as market presence, brand strength, cash flows, strength of balance sheet, reputation and research and development (R&D) investment.
It’s worth looking at those factors to understand why large and mega-cap AI stocks can be good additions to your AI portfolio.
Market presence
Large and mega-cap AI stocks are typically established industry leaders with a strong market presence. These companies often have a history of stable performance and a proven track record of adapting to technological shifts. While their stock prices can be volatile, as giant industry incumbents, they’re nowhere near as volatile as small and microcap stocks. Therefore, investing in this big end of the spectrum can provide some price stability to a portfolio.
Global reach
Many large AI-focused companies operate on a global scale, serving multiple markets and customer bases. This global reach can help mitigate risks associated with regional economic fluctuations – albeit that can also leave them exposed to geopolitical issues, as we’ve seen in recent times with Apple and China. Nonetheless, this true global reach means these mega-caps can draw on revenues from multiple sources, providing an element of consistency.
Cash flow and balance sheet stability
Speaking of revenues from multiple sources, these mega-cap giants often come with substantial financial resources. This includes revenues, profits and even cash at hand into the billions, giving investors some comfort by knowing these companies aren’t about to “go to the well” to tap investors for extra capital.
If they need funding, the banks usually clamour over each other to serve the needs of mega-caps. But if you’re like Apple, Microsoft or Google, you’re carrying tens of billions of dollars in cash and cash equivalents on your balance sheet anyway… so money isn’t really a problem.
Profits also extend into the tens of billions. When you’re looking at mega-caps, you’re paying for the cash flows and the balance sheet stability. You’re paying for the obscene volumes of money these companies make and reinvest back into their organisations and technologies.
Research and development
Which takes us to their R&D spend. Large-cap companies tend to have substantial resources allocated to R&D. This allows them to continue innovating in AI technologies, maintain competitiveness and adapt to changing market dynamics. Following on from the points about financial stability, Apple spent $29 billion on R&D expenses in 2023, Microsoft spent $27 billion and Google spent a whopping $41 billion.
Arguably there’s a lot of wastage there, but that money also goes towards the innovation and development these mega-caps are (supposedly) renowned for.
Liquidity and accessibility
Large and mega-cap stocks are highly liquid in the market. That makes it easy for investors to buy and sell shares when needed. They are also accessible to both individual and institutional investors. You can log into almost any online broker or broking app and quickly and easily trade in and out of these mega-caps at the current market price.
Examples of large and mega-cap AI stocks
We’ve already mentioned a few of these mega-caps with an AI focus, but it’s worth reminding you exactly how these mega-caps are developing their AI technologies…
Alphabet Inc. (GOOG)
Google’s parent company, Alphabet, is a prime example of a mega-cap AI stock. Google has been at the forefront of AI research and development, integrating AI into its search algorithms, advertising and cloud services. Google’s AI subsidiary, DeepMind, has made significant breakthroughs in machine learning.
Microsoft Corporation (MSFT)
Microsoft is a leading player in AI with its Azure cloud platform and AI services. This has accelerated since its buyout of AI company OpenAI. The company's AI initiatives include natural language processing, computer vision and AI-driven productivity tools such as its emerging Co-Pilot upgrades. Microsoft’s market presence and diversified business make it a prime mega-cap AI stock.
Amazon.com, Inc. (AMZN)
Amazon uses AI extensively in its e-commerce operations, supply chain management and cloud computing division (Amazon Web Services, AWS). The company’s AI-powered recommendation engine and fulfilment centres are ways in which AI is used in the company daily.
Nvidia Corporation (NVDA)
Nvidia has fast become the darling of the AI market. It is a mega-cap company with a focus on AI-related hardware, such as graphics processing units (GPUs) and data-centre chips optimised for AI and deep learning applications. Its technology is fundamental to AI training learning and the advancement of AI in cloud-based companies.
Tesla Inc. (TSLA)
Tesla is a mega-cap car company that isn’t your typical car company. Tesla has integrated AI into its electric vehicles, enabling features like autonomous driving and over-the-air software updates. Its “Dojo” supercomputer is believed to be the companies intentional attempt into pushing forward their own AI agenda and integration further into its products and services. Tesla’s innovative AI applications and AI-future have attracted significant attention from investors. They’re not even really a car company any more but a high-tech car, AI and robotics company.
What next?
Large and mega-cap AI stocks offer an easy, straightforward way for investors to gain exposure to the AI revolution while benefiting from the stability and global reach of established industry leaders.
These giants have already made significant strides in AI research and development and continue to pump capital into this sector. However, you also need to consider that they’re already large. That means the potential upside from further advancements in AI may already be baked into the stock price.
Mega-cap companies are a good portfolio foundation when looking at AI, but for big, blue-sky, exponential growth opportunities, it’s unlikely you’re going to get it from the mega-cap and large-cap section of the AI market. For that, you need to get small… and micro.
#3: Get down and dirty in the small-cap market
As investors, we always want to turn a profit. We know, however, that there’s a sliding scale of risk vs. reward that’s always factored in when looking to invest in a particular opportunity.
That’s why through this report, you’ve seen multiple approaches to that, from ETFs to large and mega-cap stocks. What you might notice is as you work your way through these options, you’ll find that risk increases with each level you drill down into.
That’s for good reason. Because the next way to invest in the AI boom is by investing directly into AI companies and AI-focused companies that make up the small and microcap sections of the world’s stock markets.
These are the tiny little darlings that are often overlooked or simply ignored by the mainstream media and by large investment houses. They’re companies that have far greater risk than the mega-caps, because they are often close to start-ups that are ideas rich… and cash poor.
Sometimes you’ll find that these tiny companies are still in experimental and development stages, with little to no substantial cash flows or revenues. They’re funded by investment capital and the potential for their product or service is so great that one day they become those mega-cap stocks and deliver astronomical returns to investors.
Nvidia is often referenced as an example of this. And for good reason. The company was founded on a shoestring budget in 1993, almost went bankrupt in 1995 and then went public with its initial public offering (IPO) in 1999 with a stock price of $12 per share (and a market cap of only around $600 million).
Nvidia is now worth more than $2 trillion. That’s a true rags to riches story.
Of course, not every small cap goes on to that kind of market domination. Most don’t. But there are plenty of tiny little companies involved in the world’s biggest most exciting exponential trends and technologies that offer blue-sky potential for investors.
They’re high risk, but if they come good, the high returns on offer make the small-cap sector a prime hunting ground for investors with the right approach and risk appetite. While this is all great, what are some of the other benefits that small caps offer to risk-hungry investors.
Innovative edge
Small caps also provide somewhat of a more innovative edge than mega caps. Smaller companies are often more agile and can pivot quickly to capitalise on emerging opportunities in AI. They may have innovative AI solutions that larger companies have yet to explore. They have less baggage, so to speak, and because their focus is often more refined, they can inject all their energy into the one company-making outcome.
Market undervaluation
The market may undervalue small and micro-cap AI stocks, presenting opportunities for investors to buy shares at a lower cost relative to their growth potential. This is where asymmetric risk comes into play. If you are aware of the risk of these smaller stocks and can adequately manage your capital, you can find a sweet spot between potential return and risk of losing the value of your investment.
Takeover targets
As we’ve seen, large and mega-caps are often cashed up (into the tens of billions in some cases). This means that they aren’t afraid of simply heading out and buying smaller innovative companies in the AI space. A mega-cap to spending $100 million from its $20 billion cash coffers only equates to half a percent of its available cash. Therefore, it’s often worth the effort. Investing in small and micro-cap AI stocks can potentially lead to lucrative acquisition opportunities if you can get in early, and then the company becomes a takeover target.
Niche focus
Smaller AI companies often specialise in niche markets or cutting-edge AI applications, allowing investors to target specific segments of the AI industry. Perhaps it’s just vision systems or AI software, maybe it’s a particular piece of AI hardware in development, or perhaps a robotics company integrating AI. The smaller you go, the more specific and focused your stock investment can be.
Examples of small-cap AI stocks around the world
It’s important to know these companies are dotted all over the world, focus on different parts of the AI market and they’ve had varying success during the early parts of this AI boom. These are some examples of how diverse and varied AI stocks can be when you start digging in and exploring the small-cap parts of the world’s markets.
Innodata (NASDAQ:INOD)
With a relatively small market cap (under $1 billion), technically Innodata is a small-cap AI stock in the US. It uses data and AI applications to help businesses to analyse and interpret their data and workflows. As the company puts it, “We provide AI-enabled software platforms and managed services for AI data collection/annotation, AI digital transformation, and industry-specific business processes.”
Brainchip Holdings (ASX:BRN)
Brainchip is developing AI processors (chips) that mimic the brain. The company calls it a digital neuromorphic processor, or by its commercial name, Akida. It is also a small company with a market cap under AU$500 million. It is relatively unknown by the wider market due to its geographic location and the fact the company still straddles the fine line between development and commercialisation.
DotDigital (LSE:DOTD)
DotDigital is a digital marketing company. At first glance you wouldn’t think “AI company”. However, this is one of those small-cap companies that might not be a pure-play AI company, but they’re leveraging AI to make their business better and to deliver a better product and reach more customers. DotDigital’s AI platform, WinstonAI, is AI for marketing. It makes DotDigital an example of a niche-focus small-cap stock that also rides the bigger AI boom.
What next?
Investing in small and micro-cap AI stocks can offer investors the opportunity to tap into the growth potential of innovative AI technologies. These companies may be at the forefront of niche AI applications or poised for rapid expansion as they develop or integrate AI solutions into their businesses. However, it’s important to acknowledge that small and micro-cap stocks are riskier due to their volatility and illiquidity (meaning they can be hard to buy and sell when you want or need to). In this segment, you must be prepared to take on much greater risk and be disciplined with your capital management.
#4: Invest in yourself
The best investors take time to understand, educate and immerse themselves in particular areas of speciality.
The point isn’t that you need to aim to become some kind of AI developer or semiconductor engineer. The point is that you should dedicate time, and some resources where necessary, to clue yourself up on everything this huge opportunity presents.
Self-investment in learning and research can enhance personal knowledge and skill, as well as help you to allocate your investment capital into investments that are most suited to your portfolio strategy, investment objectives and risk tolerance.
With the emergence of AI and the explosion of AI tools available to the wider public, this dedication to the AI Collision means that you’ll also likely come out more productive, effective and efficient in your own day-to-day work and life.
While many people are fearful of AI and what it might mean for the future of work and society, I’m of the view that we should embrace AI and augment our existence with it, which has the potential to improve the living standards of all of us.
So even if you don’t invest in AI opportunities, by investing in yourself by learning about AI and all the tools available to you, I think it will be not just be worth it, but also perhaps one of the most profitable investments you’ll make.
And here’s why…
Why should you really bother?
Future relevance
As AI becomes increasingly integrated into various industries, understanding its fundamentals and applications is crucial to remain relevant in the job market. Learning about AI is an investment in your own employability and career prospects. And if you run your own business, then it puts you ahead of the curve compared with others who decide to ignore this emerging opportunity. I doubt few people would consider a “prompt engineer” a job of the future, but there’s a good chance that is exactly one of the things AI will open as future employment opportunities for people.
Be “smarter”
AI can assist in solving complex problems more efficiently. Learning to leverage AI tools can enhance your ability to figure out problems faster and with greater insight, allowing you more time to develop other ideas.
Do more with less
AI-powered apps and tools can automate routine tasks, freeing up time for more strategic and creative time. This boost in productivity can significantly impact your personal and professional life. Think of an AI assistant organising your calendar, even optimising travel routes and helping you maximise time at home. Or perhaps AI that can take an extensive Word document and build a complete PowerPoint presentation in seconds – seems a world away, except these are the kinds of AI tools available now.
Things we know we don’t know
AI innovations have given rise to countless startup opportunities. By gaining expertise in AI, and building a skill set in understanding the sector, if an opportunity arises to move, you’ll be prepared both intellectually and with your investment capital.
The smartest person in the room
Taking the time to learn about AI is intellectually stimulating and puts you ahead of most people who will hear about it and then do nothing about it. It makes you the smartest person in the room when people are talking about AI and what they hear on the news. You’ll have a depth of understanding and insight that not just makes you smarter, but even an expert in this field.
Sounds great, so how do I “AI”?
The reasons why you’d invest in self-education with AI are numerous. Then there’s the practical application and learning to do.
Here are several available applications you can use to start your AI education journey. Dive into these, explore them, use them and get a feel for the speed and innovation happening in AI today.
ChatGPT is a large language model chatbot developed by OpenAI. It’s arguably the reason that 2023 kicked off the mass hysteria around the AI Collision. A bit like the “iPhone moment” for consumer-facing AI tools. ChatGPT can hold conversations, answer questions, generate text, translate languages, write different kinds of creative content, as well as answer your questions in an informative and human way. It has a free and a paid version (the paid one utilises its more updated large language model (LLM)).
Replika is a chatbot that is designed to be a friend and companion. It can be used to talk about anything, from your day to your deepest thoughts and feelings. It may seem a little weird, I know. But it’s worth a look and a play even if it is just to see the kinds of things that are available to people now.
Grammarly is an AI-powered writing assistant that can help you improve your grammar, spelling and style. It can also help you find and fix plagiarism. Grammarly is available as a browser extension, a desktop app and a mobile app.
QuillBot is an AI-powered writing tool that can help you rewrite your text in a more concise and engaging way. It can also help you improve your vocabulary and grammar. QuillBot is available as a browser extension and a mobile app.
Midjourney is an AI-powered image creation tool that can help you create images from your imagination. Anything you can imagine, it can and will create. ANYTHING! It has the potential to be a powerful tool for artists and designers, but there’s also a lot of criticism that it’s a threat to artists and designers as well. Either way, check it out. It is available by invitation-only through Discord and you need a subscription to generate images.
These are just a few of the many AI applications that are available today. As AI technology continues to develop, we can expect to see even more innovative and useful AI applications in the future.
What next?
Investing in yourself by learning about AI doesn’t require any formal education or significant financial resources. Numerous online resources, courses and AI-powered applications are accessible to anyone with an internet connection.
As I’ve mentioned, investing in AI doesn’t always have to be about gaining immediate returns from the market. Invest in understanding this sector, learn to find and use new AI tools and prepare yourself to be worth more personally and professionally in the future.
Regards,
Sam Volkering
Editor in Chief,
AI Collision
