Palantir's recent stock price slump does not signal the end of the AI premium, but rather suggests that the standards the market demands from enterprise AI solutions have become higher. From a technical analysis perspective, Palantir is below key moving averages and has lost technical support, and external variables such as the domestic priority policy in the European market and the possibility of regulation by the US administration are pressuring investment sentiment. Nevertheless, bulls like Wedbush argue that the potential of the enterprise AI market is still underappreciated and are confident that the agentic AI ecosystem built by Palantir will become a core infrastructure for enterprise operational data in the long term. Ultimately, the current stock price adjustment should be interpreted as part of a process where the initial bubble of AI introduction has cleared and only companies with the ability to solve real business problems can survive.

The standard that determines the true winner in the AI ​​era is not the size of the model, but how elaborately fragmented internal corporate data is structured. The ‘ontology layer’ that Palantir emphasizes is the core engine that regenerates scattered source data into relational knowledge that AI can understand. Samsung Electronics' automation of its failure response system through AIOps, and Korean company Infosys' development of industrial AI middleware under the banner of 'K-Palantir' all prove the importance of data maintenance. Because it is difficult to achieve fundamental innovation in business processes simply by introducing generative AI, companies are risking their lives to build an ontology that turns data into a 'semi-cooked state'.

As the battlefield is reorganized to focus on algorithms and software, the very concept of the defense industry is changing. While large military companies in the past focused on hardware production, now 'neo-prime' companies such as Palantir, Anduril, and SpaceX have emerged as key partners of the U.S. Department of Defense, dominating battlefield decision-making infrastructure. Through the 'Forward Deployed Engineer (FDE)' model, they analyzed data and improved algorithms in real time at the operational site, shortening the weapon system evolution cycle from years to a matter of weeks. These changes also have significant implications for K Defense. Beyond simply creating better weapons, the introduction of a ‘Korean FDE model’ that quickly learns data and evolves on its own to suit battlefield situations will become a key competitive edge in national security.

Both Eastern and Western capital markets are in the process of revaluation, reevaluating the value of AI software. Zhongke Wonge, listed on the Hong Kong stock exchange, is leading the AI ​​transition of the national decision-making infrastructure, aiming to become a Chinese version of Palantir, while Momenta is transforming cars into intelligent bodies through physical AI. This goes beyond simple technological competition and takes on the character of a geopolitical hegemony battle over how to design and operate AI as a national strategic asset. Companies are now moving beyond the stage of using AI as an auxiliary tool and moving to the stage of delegating failure prediction, autonomous operation, and even complex decision-making to AI. Data sovereignty and security issues that arise in this process will become the biggest topics of global business in the future.