Core Insights - The CEO of Futurum Group, Daniel Newman, argues that the AI industry is not in a bubble but is facing a significant crisis due to a global shortage of compute power necessary for a long-term technological shift [1][2] - The rise of "agentic" AI systems will lead to unsustainable levels of compute intensity, resulting in a critical hardware shortage in the technology sector over the next 5 to 10 years [2] - 2026 is identified as a pivotal year for enterprise AI, where substantial corporate returns on investment (ROI) will begin to materialize, moving beyond consumer applications [3][4] Infrastructure Gap - Newman emphasizes that the current market frenzy is a preliminary stage of a multi-decade super-cycle, rather than a bubble [1] - The demand for compute power is expected to outstrip supply, with Newman stating, "We don't have enough turbines" to meet current and future needs [2] Enterprise AI and ROI - The industry is currently underutilizing available trained data, with much of it locked in proprietary systems for various applications [3] - The transition from the "build phase" of AI model training to the "monetization phase" of inference is underway, which will lead to measurable productivity gains [4] Efficiency at Scale - Google's Gemini AI model is generating an impressive 10 trillion tokens daily, showcasing the scale of current AI activity [5] - AI has significantly improved operational efficiency, reducing complex market research workflows from six months to just two weeks [5] Investment Opportunities - A list of AI-linked ETFs is provided for investors, highlighting their performance over six months and one year, with notable options including: - Defiance Quantum ETF (NASDAQ:QTUM) with a one-year performance of 44.55% [6] - iShares Expanded Tech Sector ETF (NYSE:IGM) with a six-month performance of 16.51% [6]