As the artificial intelligence (AI) sector prepares for a pivotal year in 2026, experts are raising concerns about a significant gap between investment enthusiasm and actual advancements in research. A growing number of voices in the industry warn that the speed of investor excitement is outpacing the reality of AI’s progress, leading to potential overvaluation and missed opportunities.
Jenny Xiao, a former researcher at OpenAI and now the head of Leonis Capital, has emerged as a key commentator on this issue. In a recent interview, she emphasized the “years-long lag” in the AI investment hype cycle, noting that many investors continue to base their decisions on outdated understandings of the technology’s capabilities. As an expert who holds a PhD from Columbia University and founded her firm in 2021, Xiao highlights a fundamental disconnect: while leading AI labs are exploring innovations like multimodal models and autonomous agents, the investment community often lags behind in embracing these cutting-edge concepts.
The AI Investment Landscape
According to Xiao, this disconnect is largely due to the limited technical expertise among many venture capitalists. “There is a massive disconnect between what researchers are seeing and what investors are seeing,” she stated, underscoring the need for backers who can critically evaluate technologies beyond superficial trends. Leonis Capital focuses on “frontier AI” ventures, aiming to back startups that can effectively translate lab discoveries into viable commercial applications.
The AI investment boom has been striking, with global spending on AI infrastructure projected to surpass $500 billion in 2026. Yet, as Xiao points out, much of this excitement is based on ideas that have become foundational rather than groundbreaking. Technologies such as large language models (LLMs), which were at the forefront of discussions in 2023 and 2024, are now seen by researchers as limited tools. Investors, however, continue to funnel resources into LLM-centric startups, often overlooking emerging technologies like agentic AI systems capable of executing complex tasks autonomously.
Echoing this perspective, industry observers on social media platforms have suggested that 2026 could mark a turning point for agentic AI, with predictions that as much as 40% of enterprise applications will incorporate such technologies. This shift reinforces Xiao’s call for a new generation of technically savvy investors, as current funding often prioritizes popular pitches over rigorous technological validation.
Addressing the Disconnect
The persistent hype lag is not a novel phenomenon; it has been observed in previous technology booms, from the dot-com era to blockchain. However, the stakes are particularly high in the AI sector, where the potential for disruption spans industries such as healthcare and finance. Xiao argues that this lag results in inefficiencies: innovative startups often struggle to secure funding because their advancements are too complex for many investors to comprehend, while more familiar, safer ventures receive the majority of capital.
Recent analysis from Capgemini highlights a shift from hype to realism in AI investments, indicating a growing emphasis on building infrastructure and upskilling workforces to derive long-term value. This aligns with Xiao’s insights that advocate for bridging the gap between research and investment through education and collaboration.
Xiao’s firm hosts workshops and publishes insights designed to enhance investors’ understanding of frontier AI technologies. This initiative is gaining traction, as evidenced by a rise in AI-focused venture funds led by former researchers. Industry experts predict that as 2026 unfolds, a more informed funding ecosystem could emerge, potentially reducing the risk of market corrections.
The implications for startups are significant. Founders working in niche areas such as embodied AI or robotics are finding it increasingly difficult to attract funding amid the prevailing noise. Xiao’s firm is strategically investing in these sectors, as outlined in their newsletter that critiques overhyped areas while spotlighting undervalued opportunities in non-linear AI advancements.
As AI technology continues to evolve, the industry faces a critical juncture. With geopolitical dynamics influencing the landscape, as noted in a report from the Atlantic Council, the race to dominate AI between nations like the U.S. and China further complicates investor strategies. Xiao has emphasized the need for investors to focus on resilient, innovative firms capable of navigating these uncertainties.
Overall, the AI investment arena in 2026 is at a crossroads. By addressing the existing hype lag, as advocated by experts like Jenny Xiao, the sector could transition towards a more balanced future—one where funding aligns with genuine technological progress rather than echoes of past excitement. As the industry moves forward, investors who heed these warnings and adapt to the evolving landscape may be well-positioned to capitalize on the true potential of AI.
