As I read through multiple blogs on the valuation of OpenAI and its cousins, I found myself reflecting on the ideas of financial nihilism and narrative-driven investments. Financial nihilism refers to the belief that financial assets, markets, or even the very notion of money do not possess intrinsic value or significance. This perspective often causes investors to view speculative assets—such as cryptocurrencies, meme stocks, or NFTs—as essentially worthless, with their prices being influenced not by fundamental realities but by speculation and the expectation that others will pay more in the future. The term, which gained popularity through Demetri Kofinas, is based on the concept that price becomes self-referential: value is regarded as entirely subjective, and investment choices are driven by narrative or short-term demand rather than any economic basis or long-term usefulness. In this context, narrative-driven investing emphasises how captivating stories can influence investor behaviour and asset prices, often regardless of underlying economic fundamentals.
There is certainly a significant amount of financial nihilism present in the AI sector. The critical question is when a company accumulates enough substance to navigate through various narratives. While I’m not a finance expert, I have served on numerous boards and have experience in both technology-focused and established businesses. Twice a year, I review the valuation of the top ten stocks according to Fortune 500 and observe how the value of AI-driven companies fluctuates based on the perceived “plausibility” of their digital assets, geopolitical conditions, and their operating capacity to execute strategies effectively.
AI-centric companies, whether based in the United States or China, have several distinguishing – and repeating – features. These include access to proprietary data (real-world data rather than synthetic), a substantial intellectual property portfolio, investments in their own semiconductor capabilities and/or significant partnerships regarding chipsets, advanced knowledge in designing and constructing data centres, and the recruitment of top university professors to serve as Chief AI officers or similar roles. They also have efficient and effective operating models that facilitate a swift transition from research and development to product lines and maintain captive venture capital to scout and invest in talent and third-party technologies. I first discussed these topics in my book “The AI Imperative: A Practical Roadmap for Businesses,” published in 2018.
In 2017, nine AI-centric brands ranked among the top ten, including five familiar names from the US West Coast, alongside their Chinese counterparts, such as Baidu, Tencent, and Alibaba. However, by 2023, these Chinese firms had vanished from the list—not due to a loss of their substance in intangible assets, but because geopolitics had become as influential in the AI arena as weather is in agriculture and tourism. In 2023, Tesla secured a place in the top ten, which I believe was well-deserved, as it opted for a video-driven computing approach to gather real-world data for training its models, rather than investing heavily in expensive sensors (in a complex hardware like a car, the best feature is when the feature is absent, after all). Now, it has dropped out of the top ten, and there are numerous fabulous blogs discussing the reasons for that – be it assessing the psycho of Elon and Trump, or the company’s substance and corporate governance.
Only time will reveal whether scaling the transformer-based architectures will generate value at OpenAI and its cousins, but I am inclined to believe it won’t. All that remains is to watch the spectacle unfold, filled with endless consultants and self-proclaimed AI influencers swallowing it all—with or without a spoonful of sugar, depending on who you ask.