The AI surge was expected to benefit mainly new firms creating the models. Recent results indicate that some of Europe’s largest, long-established technology companies are instead gaining from AI adoption. SAP, Capgemini, Sopra Steria and OVHcloud have reported higher demand, quicker expansion or improved forecasts as businesses shift from testing artificial intelligence to rolling it out in operations. During this shift, they find that integrating AI effectively within complex organizations is more difficult than simply accessing the tools. Large entities are unlikely to depend on one AI supplier. They are instead projected to apply varied models for separate tasks based on performance, security and compliance needs. The main issue is moving beyond model selection to connecting AI with existing software, data and processes. AI applications form the key area where most value will arise, according to a recent UBS note. This situation suits Europe’s established software, consulting and infrastructure companies, many of which have long helped large organizations integrate complex systems before generative AI appeared. Most large organizations do not begin with a blank technological slate. AI systems must operate with software accumulated over decades, scattered databases, tailored applications and stricter governance rules. They must also reach live company data while following access rules, maintaining records and matching employee workflows. The difficulty of this integration is emerging as a major limit on AI use. Boston Consulting Group noted that rollout is progressing quicker than firms’ capacity to handle it, with over 70 percent of investors worried about whether organizations possess the technical and operational skills required for AI success. As companies advance from testing to application, spending on implementation, integration and governance is becoming a larger part of the AI value chain. SAP’s cloud backlog increased 26 percent at constant currencies to €22.9 billion as firms moved key finance, procurement, supply-chain and human-resources systems to platforms that increasingly support AI deployment. The company’s purchases of data firm Dremio and AI company Prior Labs highlight the rising need to make enterprise data available to AI tools. Capgemini raised its yearly growth goal after bookings grew 9.2 percent, while Sopra Steria improved its outlook after organic growth reached 5.3 percent. The two Paris-listed firms are gaining from the follow-on work after AI adoption: fitting models into workflows, handling data and creating governance frameworks. This work holds particular value in areas such as defence, aerospace, healthcare and critical infrastructure, where AI must align with specialist software and tightly regulated processes. A further trend is strengthening Europe’s incumbents: rising demand for greater control over AI deployment. Publicis Chief Executive Arthur Sadoun noted clients want advanced AI models to run in settings where they keep control of their technology and data. This preference is strongest in defence, aerospace and critical infrastructure, where worries about sovereignty, security and compliance are highest. Airbus chose Scaleway, owned by French telecoms group Iliad, for sensitive industrial and defence uses, along with AI tools developed with Mistral. Airbus expects about 70 critical applications to operate on Scaleway by the end of 2028. OVHcloud’s public-cloud revenue rose 20.2 percent in its third quarter, offering early signs that demand for European-controlled AI infrastructure, not subject to laws such as the U.S. Cloud Act, is turning into commercial growth. Europe’s technology incumbents still must show that AI-driven demand can continue and that margins can handle the automation of lower-value consulting and software tasks. Recent results suggest the main AI beneficiaries may extend beyond those building the models to include firms that make those models usable inside major organizations.
