Concerns regarding a potential artificial intelligence bubble have been circulating among investors, but LPL Financial’s chief equity strategist, Jeff Buchbinder, posits that the current advances of the Nasdaq 100 index still appear modest when compared to the frenzied growth and subsequent collapse seen during the dot-com bubble. He highlights the similar trajectories of the tech index since the launches of both Netscape, marking the onset of the dot-com era, and OpenAI’s ChatGPT, indicating that the current AI boom is indeed reminiscent of that bygone period.
Despite the Nasdaq 100’s substantial gain of over 140% since the debut of ChatGPT, Buchbinder points out that this performance pales in comparison to the staggering 1,090% increase experienced by the index at the peak of the dot-com bubble in March 2000. This suggests that the current AI-driven market trajectory may not be as irrational as critics claim.
Buchbinder emphasizes that several fundamental differences set these two periods apart. Notably, the leaders driving this AI expansion are primarily relying on internal cash flow for financing rather than engaging in speculative capital raising. This financial strategy, alongside more diversified business models, appears to create a sturdier foundation for growth compared to the earlier tech boom.
Current valuation metrics further reinforce this argument; during the dot-com peak, the tech sector’s forward earnings multiple soared to 58 times, while today it stands at a more reasonable 25 times. Furthermore, the initial public offerings (IPOs) linked to today’s AI advancements come with larger revenue streams and clearer paths to profitability.
Buchbinder elaborates that the current AI expansion is significantly grounded in infrastructure development. With adoption rates still in their infancy, the solid balance sheets of infrastructure firms are positioned to facilitate the emergence of new AI leaders.
However, some analysts are sounding alarms regarding the rising levels of debt among major hyperscalers such as Alphabet and Oracle. Bloomberg data indicates that these companies have been increasing their debt loads significantly to finance a projected $725 billion in capital expenditures by 2026.
In terms of spending predictions, AI expenditures are expected to surge from $340 billion in 2025 to around $3 trillion by 2035, as per Oxford Economics. This dramatic increase would elevate AI’s share of total tech spending from less than 4% today to approximately 23% over the next decade.
A recent UBS survey reveals a notable shift in sentiment regarding AI’s impact on employment; 42% of participants anticipate that AI may lead to a reduction in hiring, an increase from 31% in a similar survey conducted in October 2025.
Additionally, analysts from BNP have flagged the credit supply risk associated with AI hyperscalers as being adequately priced into the market.
Buchbinder clarifies that he does not predict an outright repetition of history wherein the Nasdaq 100 experiences another 900% gain followed by a severe downturn. Instead, he asserts that the current stock market’s trajectory appears to be more rational than it seems, potentially aligning more closely with the tech landscape of 1997 rather than the perilous highs of late 1999 or early 2000.
