Token Index Decline:: The Silicon Data LLM Token Expenditure Index is down nearly 20% from its May peak after nearly doubling since its December inception. This index is the clearest measure of AI pricing power available to investors.
$700B+ Capex Under Scrutiny:: The index's decline questions whether the enormous sums being poured into AI infrastructure will generate sufficient returns. Allianz Research reports a **46% growth gap** between AI investment and sales — worse than the **32% divergence** measured during the 2001 telecom bust.
Why this matters:: If AI companies cannot maintain pricing power, the entire bull case for chip makers like NVIDIA, memory manufacturers, and data-center operators rests on shaky ground. The decline suggests customers are becoming increasingly cost-sensitive.
'SaaSpocalypse' Hits Software:: Software-as-a-service stocks are being pummeled by fears of AI disruption. Top losers year-to-date include Intuit (-58%), HubSpot (-51%), Atlassian (-49%), Workday (-41%), Salesforce (-38%), Adobe (-38%), and Microsoft (-22%).
Historical Context:: The current situation echoes the **2001 telecom bust**, where overinvestment in infrastructure outpaced actual demand. A sustained weakness in the token index could end the trade that saw the entire AI cohort rally hard this cycle.
The Silicon Data LLM Token Expenditure Index blends prices and usage of AI tokens — the fundamental unit of AI computation. A dip in this index can imply three very different scenarios:
List prices are falling — AI providers are cutting prices to stay competitive.
Demand is shifting toward cheaper models — Users are opting for more cost-effective alternatives.
A genuine softening in willingness to pay — Buyers are reaching their spending limits.
Silicon Data itself has cautioned against reading the index as a simple price tag, calling it a proxy for *marginal willingness to pay*.
Token prices have collapsed more than 90% since 2023, yet total spend has roughly doubled since last year. Cheaper tokens have expanded the market. If the recent flattening of the index is merely "digestion" as the market adjusts, then demand is real and capex spending remains justified. As David Miller, senior portfolio manager at Catalyst Funds, noted: *"During the training phase, the cost of AI infrastructure is extraordinarily high, but in the current inference stage, the economics are significantly better. The net use of AI delivers a positive return on investment for companies, at least over the long term."*
Bears warn that sustained weakness in the token index could end the AI rally. Token spending justifies the next capex order, and that bill is already looking stretched. Allianz Research's finding of a 46% growth gap between AI investment and sales — exceeding the 2001 telecom bust's 32% — is a stark warning.
Regulatory headwinds add to the pressure. The EU's AI Act targets frontier models for mandatory evaluations and stringent transparency requirements. Meanwhile, the US government recently removed foreign access restrictions on Anthropic's Fable 5 model after requesting OpenAI to stagger an upcoming release. These compliance burdens give finance chiefs a rational reason to route workloads to cheaper models.
This is not a chip-glut call. Top-end GPUs and high bandwidth memory are sold out through 2026, with no real relief until 2028. However, the demand mix is shifting away from top-end training GPUs toward inference-optimized parts, changing the winners in the AI supply chain.
The software sell-off adds another dimension. As José Torres, senior economist at Interactive Brokers, explained, the market initially worried about AI replacing SaaS products, and now worries about AI investments not panning out. Mark Malek, CIO of Siebert Financial, added: *"The market is definitely questioning itself on the AI trade."*
DWS strategists led by CIO Vincenzo Vedda remain cautious: *"We are monitoring areas where valuations may look stretched."*
Investors in AI and tech stocks: face heightened volatility and the need to reassess positions.
Enterprise customers: may benefit from falling AI prices but face uncertainty about which platforms will survive.
Software companies: are under existential pressure to adapt or risk disruption.
Chip manufacturers: like NVIDIA remain in strong demand, but the mix of demand is shifting.
What is the Silicon Data LLM Token Expenditure Index?
It's a gauge that tracks what users pay for AI tokens — the units of computation used by large language models. It blends pricing data with usage patterns to measure the market's marginal willingness to pay for AI services.
What is the 'SaaSpocalypse'?
The term refers to the severe sell-off in software-as-a-service stocks driven by fears that AI agents and tools could replace traditional software products. Major companies like Intuit, HubSpot, and Salesforce have seen double-digit percentage declines in 2026.
How does this compare to the 2001 telecom bust?
Allianz Research found a 46% growth gap between AI investment and sales, which is worse than the 32% divergence during the 2001 telecom bubble. This suggests AI infrastructure spending may be outpacing actual revenue generation by an even greater margin than during the dot-com era.
Is the AI hardware demand still strong?
Yes. Top-end GPUs and high-bandwidth memory are sold out through 2026 with no relief until 2028. However, demand is shifting from training-focused chips toward inference-optimized hardware.
For Investors:: Diversify beyond pure AI plays. Monitor the Silicon Data Token Index as a leading indicator. Consider that the most expensive part of the AI trade — the pricing power story — may crack first.
For Businesses:: Take advantage of falling token prices to experiment with AI integration. However, be cautious about long-term vendor lock-in as the regulatory landscape evolves.
For Software Companies:: The "SaaSpocalypse" is a clear signal to innovate or risk obsolescence. AI agent capabilities are rapidly reducing the need for traditional SaaS interfaces.
Key Insight:: The AI trade is entering a new phase where the question is no longer *"How fast is AI growing?"* but *"Who will profit from that growth?"* The answer increasingly points to companies that can maintain pricing power and adapt to a more cost-conscious customer base.
The AI trade is at a crossroads. Token prices are sliding, software stocks are cratering, and regulators are circling — yet hardware demand has never been stronger. Do you think the AI boom is entering a healthy correction, or are we witnessing the early stages of a bubble bursting?
*Share this with others who need to stay ahead of this trend!*
Share on: Twitter/X | LinkedIn | Reddit
*Do you think this trend will last? Let us know in the comments below!*
On July 24, 2026, a coalition of 25 major technology companies — including **Nvidia, Microsoft, Meta, Palantir, Google, IBM, and Hugging Fac...
On Saturday, July 25, 2026, OpenAI experienced a significant global outage that left thousands of users unable to access ChatGPT, the compan...
A 55-year-old Florida pastor, Scott Winters, has filed a lawsuit against OpenAI and its founder Sam Altman, alleging that medical advice fro...
On July 20, 2026, a federal court in San Francisco gave final approval to what is now the largest copyright class action settlement in US hi...
⚠ Disclaimer: Yanuki provides article summaries and links for reference only. Yanuki does not endorse, verify, or guarantee the accuracy of third-party sources. Please review original sources and verify information independently. Managed by the Yanuki Data Engine. Full Disclaimer