European traditional tech stocks rise against the trend, surprising winners of the AI era in the earnings season.

The initial wave of AI was widely seen as a new opportunity for model developers, but recent financial reports show that a number of large established technology groups in Europe are rising against the trend, becoming the actual beneficiaries of the AI dividend. From SAP (SAP.US), Capgemini, Sopra Steria to OVHcloud, many European tech giants have reported strengthening demand, accelerating growth, or raised performance guidance, driven by a common factor: enterprises are moving from the AI experimentation phase into comprehensive deployment. However, these companies have also found that achieving real productivity from AI within complex organizations is far more challenging than acquiring the technology itself. Large organizations are unlikely to rely on a single AI vendor and will select different models based on task attributes, performance, security levels, and compliance requirements. The current challenge is no longer "which model to choose," but how to ensure that AI can seamlessly collaborate with the existing software, data, and business processes within the organization. UBS Group AG noted in a recent report: "The application of AI is the real battleground and the core of value creation." This aligns perfectly with the traditional advantages of established European tech companies, which have been deeply involved in helping large organizations integrate complex technologies long before the advent of generative AI. Most large organizations do not start with a "clean slate" technology. AI systems must be compatible with decades of accumulated software stacks, fragmented databases, customized applications, and increasingly stringent governance requirements. They also need to access real-time enterprise data while addressing permission management, audit trail retention, and being embedded in employees' accustomed workflows. The complexity of these tasks is becoming one of the biggest bottlenecks restricting AI implementation. Boston Consulting Group pointed out that the speed of deployment has outpaced organizational management capabilities, with over 70% of investors expressing concerns about whether organizations have the necessary technology and operational capabilities for AI success. As companies transition from experimentation to practical application, spending on AI implementation, integration, and governance is becoming an increasingly critical component of the value chain. SAP's cloud backlog orders grew by 26% at fixed exchange rates, reaching 22.9 billion, as enterprises continue to migrate core systems such as finance, procurement, supply chain, and human resources to its cloud platform, which is becoming an increasingly important base for AI deployment. The company's recent acquisitions of data specialist Dremio and AI company Prior Labs highlight the rising importance of making enterprise data accessible for AI applications. Capgemini raised its full-year growth target after a 9.2% increase in order bookings; Sopra Steria adjusted its performance outlook after organic growth accelerated to 5.3%. Both publicly traded companies in Paris are benefiting from the follow-up work after AI adoption: integrating models into workflows, managing data, and building governance frameworks. Such work adds significant value particularly in sectors like defense, aerospace, healthcare, and critical infrastructure, where AI must be embedded in specialized software and highly controlled operational processes. Another trend further reinforces the positioning of Europe's established companies: the growing demand for control over AI deployment. Publicis CEO Arthur Sadoun stated that clients increasingly desire to run advanced AI models in an environment where they can autonomously control the technology and data. This preference is especially pronounced in defense, aerospace, and critical infrastructure, where concerns about sovereignty, security, and compliance are particularly salient. Airbus's decision to deploy sensitive industrial and defense applications on the Scaleway cloud platform, owned by French telecom group Iliad, while utilizing AI tools co-developed with Mistral, is a reflection of this trend. Airbus expects that by the end of 2028, approximately 70 critical applications will be running on Scaleway. OVHcloud reported a 20.2% increase in public cloud revenue in the third quarter, indicating that the demand for Europes autonomous AI infrastructure (unaffected by extraterritorial laws like the U.S. Cloud Act) is beginning to commercial growth. Of course, established European tech companies still need to prove that the AI-driven demand is sustainable, while also ensuring that profit margins can withstand the pressure from low-value consulting and software work automation. However, recent performances have revealed a signal: the biggest beneficiaries of AI may not be limited to model builders; those companies that can make models truly "usable" within large global organizations are taking center stage in this transformation.