As the artificial intelligence (AI) industry grows and related stocks swing sharply, investors are shifting their attention to more precise demand-tracking gauges.
Until now, Nvidia's GPU sales and the scale of data center construction by global big tech have served as key indicators. But alternative data that shows in real time how much AI is actually being used is emerging as a new investment guide.
A new leading indicator for the AI era, the "Silicon Data LLM Token Expenditure Index" (SDLLMTK), is drawing attention. The index estimates actual usage of large language models (LLMs) by token consumption to calculate the measure.
SDLLMTK is designed on a token basis because most Generative AI services on the market charge based on "tokens," the basic units of characters or words. Therefore, token usage is the most intuitive and direct gauge of the scale of AI service utilization.
The index goes beyond simple usage to measure "token expenditure" by applying each model's price to token usage. In formula form, it is "Σ(token usage × price per token)."
Thanks to this calculation method, the index reflects not only usage but also which models are used more. For example, if the share of usage shifts toward newer premium AI models with relatively higher unit prices, the index rises further even if the total number of tokens consumed is the same as before. It captures both quantity (Q) and price (P) of revenue.
◇GPU sales and power consumption are lagging indicators… tokens show "frontline demand"
Kang Hyun-gi, an analyst at DB Securities, said SDLLMTK is earlier in timeliness than existing AI-related indicators.
Looking at the AI industry's value chain, when AI users consume tokens as they use services, AI models run GPUs to perform inference. In this process, AI data centers linked to the cloud operate, and large amounts of electricity are used.
Indicators the market has focused on—Nvidia's GPU sales, the scale of infrastructure investment by big tech (hyperscalers), and data centers' power consumption—are all closer to "lagging indicators" that reflect the latter part of the AI industry. In contrast, token usage serves as a "leading indicator" that most quickly captures changes in actual demand at the front line of the AI industry.
For stock investors, movements in SDLLMTK can inform strategies to time and calibrate the intensity of investments in AI-related stocks.
Kang noted that a continued rise in the index means actual frontline demand for AI is increasing. In that case, it is advisable to expand exposure to AI-related stocks or step up investment. Conversely, if the index turns down or slows, investors should allow for the possibility of demand stagnation and move to manage risk.
Kang said, "It is risky to put blind faith in a single indicator, so existing gauges such as GPU sales and infrastructure investment should also be monitored," but added, "Given that it allows early detection of substantive changes in AI demand, a strategic approach that assigns relatively greater weight to the leading indicator SDLLMTK is needed in future investment decisions."