In 2026, the growing disconnect between investor enthusiasm and actual advancements in artificial intelligence (AI) has raised concerns among experts. As billions of dollars continue to flow into the sector, many venture capitalists and tech insiders are grappling with the realization that their excitement often outpaces the progress in AI research. This disparity, highlighted by key figures like Jenny Xiao, the founder of Leonis Capital, is prompting discussions about potential overvaluation and missed opportunities in an industry that has experienced rapid growth since the advent of models like GPT-3.
Xiao, a former researcher at OpenAI, has voiced her concerns regarding a “years-long lag” in the AI hype cycle. In an interview, she emphasized that many investors are operating under outdated assumptions about AI’s capabilities. With a PhD from Columbia University, she founded Leonis Capital in 2021 and is keenly aware of the disconnect between what researchers are achieving and what investors are funding. She stated, “There is a massive disconnect between what researchers are seeing and what investors are seeing.”
The Gap Between Investment and Innovation
Despite the projected global spending on AI infrastructure exceeding $500 billion in 2026, this surge often reflects excitement over concepts that are now considered foundational. For instance, large language models (LLMs), which garnered significant attention in 2023 and 2024, are now viewed as limited tools by researchers. Investors, however, continue to funnel funds into LLM-centric startups, frequently overlooking emerging technologies like autonomous agentic AI systems that can perform complex tasks without human intervention.
Industry observers have noted a potential shift on platforms like X (formerly Twitter). Predictions indicate that 2026 could be the “breakout year for agentic AI,” with forecasts suggesting that up to 40% of enterprise applications will incorporate such technologies. This reflects Xiao’s call for a more technically astute investor base, as current funding often prioritizes buzzworthy innovations over thorough technical assessments.
A recent report from Capgemini reinforces this sentiment, indicating a transition from hype to more realistic assessments. Organizations are focusing on infrastructure and workforce development to derive long-term value from their AI investments. The lag between excitement and reality is not a new phenomenon; similar patterns have been observed in previous technological revolutions, from the dot-com boom to the rise of blockchain technologies. However, the implications of this lag in AI are particularly significant, given the potential for the technology to disrupt vital sectors such as healthcare and finance.
Investor Blind Spots and Market Dynamics
The lag in the AI investment landscape is evident in valuation discrepancies. Major tech firms, known as hyperscalers, such as Microsoft, Google, and Meta, have dramatically increased their capital expenditures for AI, with estimates suggesting they could spend over $500 billion in 2026 on data centers and chips. While this spending trajectory is accelerating, some analysts warn that it may outpace profit growth, reminiscent of market corrections seen in the past.
Xiao has pointed out that the industry is suffering from a shortage of investors who possess deep technical knowledge, which often leads to a herd mentality in funding decisions. The current exuberance surrounding AI stocks has caused market highs, but it has also sparked fears of a potential correction. Analysts from Yahoo Finance predict that the year 2026 will force a shift in AI investments toward tangible returns, moving away from mere hype.
Geopolitical factors further complicate the landscape. The Atlantic Council recently outlined the ways AI will shape global affairs by 2026, highlighting issues like supply chain disruptions and international competition in chip manufacturing. As nations like the U.S. and China race to dominate AI technologies, investor strategies often lag behind these rapid developments.
Xiao emphasizes the importance of focusing on resilient and innovative firms capable of navigating these uncertainties, advocating for better education and collaboration between researchers and investors. At Leonis Capital, she leads initiatives aimed at demystifying frontier AI, helping venture capitalists evaluate startups more effectively.
As the AI sector moves forward, it is crucial for investors to align their strategies with the latest research and technological advancements. By acknowledging the current lag between investment and innovation, the industry may foster a more sustainable funding ecosystem that prioritizes real progress over fleeting trends.
Looking ahead, Leonis Capital’s predictions for 2026, co-authored by Xiao and her team, advocate for diversified portfolios that include local AI growth and advanced technologies like embodied systems. This forward-thinking approach is essential as AI becomes increasingly integrated into critical sectors. The call for informed investment strategies, championed by voices like Xiao’s, may ultimately help mitigate the risks of market bubbles and lead to a more balanced and innovative future in the AI landscape.
