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J Studios
It’s time to start assessing the early winners of the AI race – here is how I do it.
ChatGPT launched nearly two years ago, marking the start of a new era where AI has become the central theme in tech investing. Since then, we’ve seen virtually every tech company seemingly “pivot” towards an AI-based business model.
With the AI race now in full swing, I think it’s time to have a serious conversation about the landscape of investing in AI. As an investor, I often find it challenging to distinguish which companies are genuinely leveraging AI to drive value and which are merely “faking it.”
Recently, I’ve started using the Rule of 40 as a key financial indicator to assess whether a company’s AI efforts are beginning to translate into monetization. I touched on this in my last article about Palantir, where I highlighted the company’s impressive Rule of 40 score as one of the reasons I am doubling my position in the stock. Following that article, a few readers reached out, seeking more insights on the Rule of 40 and my perspective on investing in AI.
In this new article, I will explore what, I believe, are the main applications of AI today—from chatbots to military software. Additionally, I will review the Rule of 40 scores for companies claiming significant investments in AI to gauge whether they are successfully monetizing these efforts.
The analysis will reveal that while AI can be effectively monetized and used to accelerate growth in established businesses, the path to monetization is often complex. Notably, a few key players are currently capturing the lion’s share of benefits in the AI space. I see AI as a catalyst that will intensify competition in the already volatile tech sector, potentially paving the way for new tech leaders to emerge while some of today’s giants may struggle to keep up.
The 3 categories of AI applications and their key players
AI is a broad term that has recently gained popularity in the business world to describe a range of technologies that have actually been in development for decades. Prior to the launch of ChatGPT, terms like ‘machine learning’ and ‘chatbots’ were more commonly used to refer to specific applications of what we now collectively call ‘AI.’
In this context, it can be difficult for investors to understand what exactly are the applications of AI and how they relate to businesses. I find online material on the subject to be confusing, as often it consists simply of a list of applications by industry. I do not think this kind of clustering is helpful to truly understand the impact that AI can have on a business.
I personally consider all applications of AI today as falling into one of three macro-categories:
Creative work.
Data analytics & Cybersecurity.
Automation & Robotics.
There is also a fourth category, which I call “Picks & Shovels.” This includes companies selling the hardware needed for AI tools and models to be developed, such as NVIDIA…
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Read More: Let’s talk about investing in AI
