Core Insights - The article discusses the urgent need for AI companies to bypass the aging public power grid by building their own gas power plants to meet the exponential demand for computing power, which has become a critical constraint for timely deployment [1][3][4]. Group 1: Power Crisis and AI Demand - The real bottleneck for AI data centers is not the lack of electricity but the slow delivery of power that cannot keep pace with the rapid expansion of computing needs [4][8]. - AI data centers are now being constructed in 12-24 months, while the typical cycle for power grid expansion and approval is still 3-5 years, making waiting for the grid a significant risk [5][6]. Group 2: Economic Implications of Power Supply - The time value of computing power is reshaping decision-making, with a 1GW AI data center potentially generating annual revenues of up to $10 billion, making it economically viable to incur higher electricity costs for faster deployment [9][10]. - Power is no longer just an operational cost but a prerequisite for the existence of AI projects, emphasizing the need for immediate power solutions [10][22]. Group 3: Onsite Power Generation Solutions - The BYOG (Bring Your Own Generation) model has emerged as a practical solution, allowing data centers to quickly start operations without waiting for grid connections [11][48]. - Major AI companies, including xAI, OpenAI, and Oracle, are leading the trend of onsite power generation, with significant projects underway, such as a 2.3GW gas power plant in Texas [16][29]. Group 4: Gas as the Preferred Energy Source - Natural gas has become the dominant choice for onsite power generation due to its scalability, stability, and rapid deployment capabilities, unlike nuclear or renewable sources [20][21]. - The competition in AI is increasingly defined by speed rather than cost, with companies prioritizing quick power access over traditional cost considerations [22]. Group 5: Market Dynamics and New Entrants - The onsite gas power generation market is experiencing unprecedented growth, with over a dozen suppliers securing contracts for AI data centers, indicating a shift in how power is viewed within AI infrastructure [17][30]. - New entrants, such as Doosan Energy and Wärtsilä, are capitalizing on this trend, with significant orders for gas turbines to support AI data centers [30][31]. Group 6: Challenges and Considerations - While onsite power generation offers speed, it also presents challenges, including higher long-term costs compared to grid power and complex permitting processes [34][36]. - The deployment of onsite power systems requires careful planning to ensure redundancy and reliability, as the complexity of managing power independently from the grid increases [94][100].