OpenAI's triple layout intensifies, catalyzing the AI industry ecosystem further.

Recently, OpenAI has been making simultaneous efforts in technology research and development, infrastructure, and capital to further strengthen its market-leading position. Upgrades to enterprise-level models, localized deployment of supply chains, and strategic investments provide additional support for its commercialization process and valuation expectations.

Core Progress Overview

In terms of model iteration, OpenAI has launched a new generation of model versions for enterprise users, achieving a balance between inference speed and the performance of complex task processing. This version is integrated by default into the enterprise custom GPT building process and has added more than a dozen enterprise-level connectors, covering scenarios such as payments and data analysis, supporting the direct invocation of third-party tools within the ChatGPT environment, thereby promoting a closed workflow.

At the infrastructure level, OpenAI has signed a joint R&D agreement with Foxconn to jointly develop multi-generation AI data center cabinet systems, with key power supply and cooling equipment to be produced domestically in the United States. This move marks a strategic extension from a light asset model to a self-built computing power system, helping to optimize supply chain stability, in conjunction with the expansion of the core technology team, to ensure long-term computing power demand.

Capital and customer scale expand synchronously. SoftBank plans to add an investment of $22.5 billion, with funds expected to be in place by December, specifically supporting computing power infrastructure construction. Currently, OpenAI has surpassed 1 million global enterprise customers, with 7 million paid seats for ChatGPT for Work, and the number of enterprise clients has increased ninefold year-on-year, with the commercialization pace exceeding expectations.

Market Transmission Effect

The A-share AI industry chain-related stocks responded strongly, with the artificial intelligence-themed ETF rising over 2%. The stock prices of computing equipment and supply chain partners performed actively. In the U.S. stock market, core computing suppliers' stock prices rose in tandem, reflecting the market's ongoing expectations for expanding demand for AI infrastructure. On the application side, the API call volume increased significantly month-on-month, and the usage of tools such as code generation has surged since the third quarter, with enterprise clients reporting noticeable efficiency improvements.

Institutional Assessment and Risk Consideration

Mainstream investment banks have generally raised their valuation expectations for OpenAI, with some institutions increasing their target valuation to the range of $500 billion to $600 billion. They believe that its "model-infrastructure-ecosystem" closed loop has taken initial shape, and that revenue is expected to break through a key threshold in 2026. The rapid accumulation of enterprise customers lays the foundation for subsequent service monetization, with API and enterprise subscriptions seen as core growth engines.

At the same time, some institutions maintain a cautious attitude. Attention should be paid to the alignment between the level of quarterly losses and the pace of capacity expansion, and vigilance is required regarding the profit realization pressure that may arise from the investment and order cycle. In addition, the cooperation model of the chip supply chain, the costs of localized production, and the risks of technological iteration still need to be continuously monitored.

Investment Logic Recommendations

In the infrastructure segment, focus on key equipment suppliers for AI data centers and local manufacturing partners; at the application level, pay attention to enterprise-level tool service providers that have connected to the OpenAI connector ecosystem; in terms of technology routes, leading computing power chip manufacturers and domestic replacement targets have long-term allocation value. Enterprise-level AI tools and data security supporting services are expected to benefit from increased demand.

Short-term, it is necessary to avoid conceptual targets that lack substantial order support to prevent sector fluctuations caused by production capacity falling short of expectations. In the long term, the synergistic evolution of AI infrastructure autonomy and model commercialization will continue to reshape the competitive landscape of the industry. #Gate广场圣诞送温暖 #非农数据超预期 #反弹币种推荐