European Tech Firms Emerge as Unexpected AI Winners as Enterprise AI Adoption Takes Off

Europe's established tech firms emerge as unexpected AI winners

August 5 (Reuters) - The AI boom was widely expected to favour the new companies building the models. Recent earnings suggest it is some of Europe's biggest, well-established technology groups that are emerging as AI beneficiaries. SAP, Capgemini, Sopra Steria and OVHcloud have all reported stronger demand, faster growth or upgraded outlooks as companies move from experimenting with artificial intelligence to deploying it across their operations. In the process, they discover that making AI productive inside a complex organisation is proving harder than gaining access to the technology. Large organisations are unlikely to rely on a single AI provider. Instead, they are expected to use different models for different tasks depending on performance, security and regulatory requirements. The challenge increasingly lies not in choosing a model, but in making AI work with the software, data and business processes companies already ⁠use. "AI applications are the battleground, and that is where most value will be created," UBS said in a recent note. That plays directly to the strengths of Europe's established software, consulting and infrastructure groups, many of which built their businesses helping large organisations integrate complex technologies long before generative AI emerged. Most large organisations do not start with a clean technological slate. AI systems must work with software built up over decades, fragmented databases, customised applications and increasingly complex governance requirements. They must also access live company information, while respecting permissions, preserving audit trails and fitting into workflows employees already use. The complexity of that task is becoming one of the biggest constraints on AI adoption. Boston Consulting Group said deployment was advancing faster than companies' ability to manage it, with more than 70% of investors expressing concern about whether organisations have the technical and operational capabilities needed to succeed with AI. As companies move from experimentation to application, spending on implementation, integration and governance is becoming an increasingly important part of the AI value chain. SAP's (SAPG.DE), opens new tab cloud backlog rose 26% at constant currencies to €22.9 billion as companies continued moving ⁠critical finance, procurement, supply-chain and human-resources systems onto platforms that increasingly serve as the foundation for AI deployment. The company's acquisitions of data specialist Dremio and AI company Prior Labs underline the growing importance of making enterprise data accessible to AI applications. Capgemini (CAPP.PA), opens new tab raised its annual growth target after bookings climbed 9.2%, while Sopra Steria (SOPR.PA), opens new tab upgraded its outlook after organic growth accelerated to 5.3%. The two Paris-listed companies are benefiting from the work that follows AI adoption: integrating models into workflows, managing data and building governance systems. That work is particularly valuable in sectors such as defence, aerospace, healthcare and critical infrastructure, where AI must be fitted ⁠around specialist software and tightly controlled operational processes. A second trend is reinforcing the position of Europe's incumbents: growing demand for greater control over AI deployment. Publicis (PUBP.PA), opens new tab Chief Executive Arthur Sadoun has said clients increasingly want advanced AI models operating within environments where they retain control over their technology and their data. The preference is strongest in defence, aerospace and critical infrastructure, where concerns over sovereignty, security and compliance are ⁠particularly acute. Airbus' (AIR.PA), opens new tab decision to use Scaleway -- owned by French telecoms group Iliad -- for sensitive industrial and defence applications, alongside AI tools developed with Mistral, reflects that shift. Airbus expects around 70 critical applications to run on Scaleway by the end of 2028. OVHcloud's (OVH.PA), opens new tab public-cloud revenue rose 20.2% in its third quarter, providing early evidence that demand for European-controlled AI infrastructure -- not exposed to ⁠extraterritorial laws such as the U.S. Cloud Act -- is beginning to translate into commercial growth. Europe's technology incumbents still need to prove that AI-driven demand can be sustained and that margins can withstand the automation of lower-value consulting and software work. Recent results, however, suggest the biggest beneficiaries of AI may not be limited to those building the models. Increasingly, they may be the companies that make those models usable inside the world's largest organisations. Reporting by Leo Marchandon in Gdansk; Editing by Matt Scuffham and Tomasz Janowski Our Standards: The Thomson Reuters Trust Principles., opens new tab * Suggested Topics: * Artificial Intelligence Leo Marchandon Thomson Reuters Leo's stories appear regularly on the technology and media desk, with a particular focus on France, Ukraine, and Europe's tech build up. He has reported extensively on major players across media & entertainment, artificial intelligence, and digital regulations. A background in tech-related law, Leo started his journalism career in Bordeaux, where he covered the full spectrum of the technology beat, from AI and spacetech to payment systems and regulations. He is now based in Gdansk, covering business, tech and entertainment news across Europe with Reuters.

Europe missed the AI labs but is winning the toolshed

The continent's established tech and industrial giants have become unexpected winners of the AI boom, even without a frontier lab of their own. Europe missed out on building the AI labs, and is quietly cashing in anyway. The continent's established tech and industrial giants have emerged as unexpected winners of the AI boom, according to Reuters, even as its startups struggle to rival OpenAI or Google. The pattern is a lesson in where the money actually lands. Frontier models grab the headlines, but the profits also flow to the companies that make the tools, run the software, and wire the power, and Europe is unusually strong in all three. The clearest case is ASML, the Dutch firm whose lithography machines are the only way to make the most advanced AI chips, and which has been closing on a trillion-dollar valuation as demand surges. Enterprise software is the other engine. SAP, now among Europe's most valuable companies, sells the systems that big firms are wiring AI into, and every AI feature it adds is one more reason for customers to stay. Then there is the unglamorous business of power and metal. Siemens has raised its outlook on AI-driven data-centre demand, and electrical firms such as Schneider and Prysmian are riding the buildout that every data centre requires. The mechanism is straightforward; every dollar spent training a model eventually reaches a chip, and every advanced chip passes through an ASML machine, so the spending that starts in California ends up, in part, in the Netherlands. Telecoms and utilities benefit too as data centres need connectivity and vast amounts of power, and the European firms that provide both are booking the demand whether or not a single European model competes at the frontier. That this counts as a surprise says a lot about the narrative. Europe has spent two years being told it lost the AI race, a story that measured the continent only by whether it had produced its own ChatGPT. By that measure it did fall behind. Europe has fretted openly about its AI sovereignty, dependent on American models and clouds for the frontier work its own firms cannot yet match. There are exceptions like Mistral, the French champion, who has finally started to make its sovereignty bet pay, but a single lab does not close a gap this wide. The incumbents' advantage is that they do not need to win the model race to profit from it. In a gold rush, selling picks and shovels has always been the steadier business, and Europe happens to own much of the hardware store. Collaborative efforts are trying to fill the rest. A pan-European alliance has built an open LLM as an alternative to American and Chinese models, though it remains a modest counterweight to the giants. The win is real but narrow. It rests on selling into a boom the incumbents do not control, and if the AI build-out slows, demand for their tools and power slows with it. It has also reshuffled Europe's corporate hierarchy. The most valuable companies on the continent are increasingly its AI-adjacent industrials and toolmakers, rather than its banks or luxury houses. The gains are unevenly spread, too. They cluster in chip tools, industrial software, and electrification, while Europe's consumer-internet and social platforms remain as absent from the AI story as ever. For policymakers, the result is awkward. Europe is profiting from AI while remaining dependent on others for the intelligence itself, a comfortable position that is also a fragile one. The danger is reading the profits as a strategy. Selling into someone else's boom is lucrative until the buyer builds its own supply, and Europe's dependence on foreign models is a vulnerability a strong quarter does not fix. Still, being the toolshed to a global boom is not the worst place to stand. Europe may not have built the future of AI, but it is selling a great deal of what that future runs on.

Global Market: Europe's tech giants emerge as surprise AI winners as enterprise adoption takes off

Europe's established technology companies are emerging as unexpected winners of the AI boom as enterprises move from experimentation to large-scale adoption. Companies such as SAP, Capgemini, Sopra Steria and OVHcloud are benefiting from rising demand for AI integration, cloud infrastructure, governance and data management. Growing concerns around security and data sovereignty are further boosting Europe's enterprise technology ecosystem. The artificial intelligence (AI) boom was initially expected to primarily benefit companies developing large language models and foundational AI technologies. However, recent corporate earnings suggest that some of Europe's largest and most established technology companies are emerging as major beneficiaries of enterprise AI adoption, according to a Reuters analysis. As businesses move beyond pilot projects and begin integrating AI into day-to-day operations, demand is shifting towards companies that can help organizations implement, manage and govern AI within complex existing technology environments. US MarketsPowered By As on 05 Aug 2026, 01:30 AM IST S&P 500 Top Gainers Palantir Technologies162.66(29.45%) Zebra Technologies368.83(26.47%) Gartner185.79(22.61%) Intel100.86(10.84%) Gainers" S&P 500 Top Losers Aptiv47.72(-16.62%) NRG Energy117.04(-15.48%) Chipotle Mexican Grill33.82(-9.72%) Coterra Energy32.56(-8.62%) Losers" Recent earnings from SAP, Capgemini, Sopra Steria and OVHcloud point to stronger demand, improved growth and more optimistic business outlooks as enterprises accelerate AI deployment across finance, supply chains, human resources and other critical functions, Reuters said. Enterprise AI moves beyond experimentation According to Reuters, organizations are discovering that deploying AI at scale is far more challenging than simply gaining access to AI models. Rather than relying on a single AI provider, companies are increasingly adopting multiple AI models for different use cases while balancing performance, security and regulatory requirements. The bigger challenge now lies in integrating AI with existing software systems, business processes and data infrastructure. UBS recently noted that the greatest value from AI is likely to be created through applications rather than models themselves, highlighting the importance of companies specializing in enterprise software and digital transformation. Established software firms gain competitive advantage Europe's technology leaders appear well positioned, given their decades of experience helping large organizations integrate complex technologies. Most enterprises operate with legacy software, fragmented databases, customized applications and strict governance frameworks. AI systems must seamlessly fit into these environments while maintaining security controls, audit trails, user permissions and existing workflows. Reuters reported that this complexity has become one of the biggest barriers to large-scale AI adoption. Research from Boston Consulting Group also suggests that AI deployment is advancing faster than companies' ability to manage it effectively, with more than 70% of investors expressing concerns over whether organizations have the technical and operational capabilities needed for successful implementation. AI implementation spending gains momentum As AI adoption matures, spending is increasingly shifting towards implementation, integration, governance and enterprise infrastructure. SAP reported a 26% increase in its cloud backlog at constant currencies to €22.9 billion, reflecting continued migration of critical enterprise applications -- including finance, procurement, supply chain and human resources -- to cloud platforms that increasingly support AI deployment. Reuters noted that SAP's acquisitions of data specialist Dremio and AI company Prior Labs further highlight the growing importance of making enterprise data accessible for AI applications. Consulting firms benefit from enterprise transformation French IT consulting firms Capgemini and Sopra Steria also reported improving business momentum. Capgemini raised its full-year growth guidance after bookings increased 9.2%, while Sopra Steria upgraded its outlook as organic growth accelerated to 5.3%. According to Reuters, both companies are benefiting from rising demand for AI integration, enterprise data management and governance systems that enable secure and compliant AI deployment. These capabilities are particularly valuable in industries such as defence, aerospace, healthcare and critical infrastructure, where AI must operate alongside specialized software and within tightly regulated environments. Data sovereignty becomes a competitive advantage Another trend supporting Europe's established technology companies is growing customer demand for greater control over AI infrastructure and data. Reuters reported that businesses increasingly prefer AI deployments that allow them to retain ownership and control of their technology and sensitive corporate information, particularly in highly regulated industries. This preference is especially strong in sectors such as defence, aerospace and critical infrastructure, where data sovereignty, cybersecurity and regulatory compliance are key concerns. Airbus has selected Scaleway, owned by French telecommunications group Iliad, for sensitive industrial and defence-related AI applications while also working with AI tools developed by Mistral. The aerospace company expects around 70 critical applications to run on Scaleway by the end of 2028. European cloud providers also benefit European cloud infrastructure providers are also beginning to gain from this shift. OVHcloud reported a 20.2% increase in public cloud revenue during its third quarter, indicating that demand for European-controlled AI infrastructure is translating into commercial growth. According to Reuters, infrastructure hosted within Europe is attracting customers seeking alternatives that are not subject to extraterritorial regulations such as the US Cloud Act. Long-term opportunity remains under watch Despite the improving outlook, Europe's tech incumbents still face challenges in proving that AI-driven demand can be sustained over the long term. Investors remain focused on whether automation could eventually put pressure on margins in lower-value consulting and software services. Nevertheless, recent earnings indicate that the financial benefits of the AI revolution are extending well beyond companies developing AI models. Firms that help organizations integrate, manage and securely deploy AI across complex enterprise environments are increasingly emerging as some of the technology sector's biggest winners.

AI deployment: Europe's established tech firms emerge as unexpected AI winners

SAP, Capgemini, Sopra Steria and OVHcloud have all reported stronger demand, faster growth or upgraded outlooks as companies move from experimenting with artificial intelligence to deploying it across their ⁠operations. The AI boom was widely expected to favour the new companies building the models. Recent earnings suggest it is some of Europe's biggest, well-established technology groups that are emerging as AI beneficiaries. SAP, Capgemini, Sopra Steria and OVHcloud have all reported stronger demand, faster growth or upgraded outlooks as companies move from experimenting with artificial intelligence to deploying it across their ⁠operations. In the ⁠process, they discover that making AI productive inside a complex organisation is proving harder than gaining access to the technology. Large organisations are unlikely to rely on a single AI provider. Instead, they are expected to use different models for different tasks depending on performance, security and regulatory requirements. The challenge increasingly lies not in choosing a model, but in making AI work with the software, data and business processes companies already use. "AI applications are the battleground, and that is where most value will be created," UBS said in a recent note. That plays directly to the strengths of Europe's established software, consulting and infrastructure groups, many of which built their businesses helping large organisations integrate complex technologies long before generative AI emerged. Most large organisations do not start with a clean technological slate. AI systems must work ⁠with software built up over decades, fragmented databases, customised applications and increasingly complex governance requirements. They must also access live company information, while respecting permissions, preserving audit trails and fitting into workflows employees already use. The complexity of that task is becoming one of the biggest constraints on AI adoption. Boston Consulting ⁠Group said deployment was advancing faster than companies' ability to manage it, with more than 70% of investors expressing concern about whether organisations have the technical and operational capabilities needed to succeed with AI. As companies move from experimentation to application, spending on implementation, integration and governance is becoming an increasingly important part of the AI value chain. SAP's cloud backlog rose 26% at constant currencies to €22.9 billion as companies continued moving critical finance, procurement, supply-chain and human-resources systems onto platforms that increasingly serve as the foundation for AI deployment. The company's acquisitions of data specialist Dremio and AI company Prior Labs underline the growing importance of making enterprise data accessible to AI applications. Capgemini raised its annual growth target after bookings climbed 9.2%, while Sopra Steria upgraded its outlook after organic growth accelerated to 5.3%. The two Paris-listed companies are benefiting from the work that follows AI adoption: integrating models into workflows, managing data and building governance systems. That work is particularly valuable in sectors such as defence, aerospace, healthcare and critical infrastructure, where AI must be fitted around specialist software and tightly controlled operational processes. A second trend is reinforcing the position of Europe's incumbents: growing demand for greater control over AI deployment. Publicis Chief Executive Arthur Sadoun has ⁠said clients increasingly want advanced AI models operating within environments where they retain control over their technology and their data. The preference is strongest in defence, aerospace and critical infrastructure, where concerns over sovereignty, security and compliance are particularly acute. Airbus' decision to use Scaleway - owned by French telecoms group Iliad - for sensitive industrial and defence applications, alongside AI tools developed with Mistral, reflects that shift. Airbus expects around 70 critical applications to run on Scaleway by the end of 2028. OVHcloud's public-cloud revenue rose 20.2% in its third quarter, providing early evidence that demand for European-controlled AI infrastructure - not exposed to extraterritorial laws such as the U.S. Cloud Act - is beginning to translate into commercial growth. Europe's technology incumbents still need to prove that AI-driven demand can be sustained and that margins can withstand the automation of lower-value consulting and software work. Recent results, however, suggest the biggest beneficiaries of AI may not be limited to those building the models. Increasingly, they may be the companies that make those models usable inside the world's largest organisations.

Europe's established tech firms emerge as unexpected AI winners

August 5 (Reuters) - The AI boom was widely expected to favour the new companies building the models. Recent earnings suggest it is some of Europe's biggest, well-established technology groups that are emerging as AI beneficiaries. SAP, Capgemini, Sopra Steria and OVHcloud have all reported stronger demand, faster growth or upgraded outlooks as companies move from experimenting with artificial intelligence to deploying it across their operations. In the process, they discover that making AI productive inside a complex organisation is proving harder than gaining access to the technology. Large organisations are unlikely to rely on a single AI provider. Instead, they are expected to use different models for different tasks depending on performance, security and regulatory requirements. The challenge increasingly lies not in choosing a model, but in making AI work with the software, data and business processes companies already use. "AI applications are the battleground, and that is where most value will be created," UBS said in a recent note. That plays directly to the strengths of Europe's established software, consulting and infrastructure groups, many of which built their businesses helping large organisations integrate complex technologies long before generative AI emerged. Most large organisations do not start with a clean technological slate. AI systems must work with software built up over decades, fragmented databases, customised applications and increasingly complex governance requirements. They must also access live company information, while respecting permissions, preserving audit trails and fitting into workflows employees already use. The complexity of that task is becoming one of the biggest constraints on AI adoption. Boston Consulting Group said deployment was advancing faster than companies' ability to manage it, with more than 70% of investors expressing concern about whether organisations have the technical and operational capabilities needed to succeed with AI. As companies move from experimentation to application, spending on implementation, integration and governance is becoming an increasingly important part of the AI value chain. SAP's cloud backlog rose 26% at constant currencies to EUR22.9 billion as companies continued moving critical finance, procurement, supply-chain and human-resources systems onto platforms that increasingly serve as the foundation for AI deployment. The company's acquisitions of data specialist Dremio and AI company Prior Labs underline the growing importance of making enterprise data accessible to AI applications. Capgemini raised its annual growth target after bookings climbed 9.2%, while Sopra Steria upgraded its outlook after organic growth accelerated to 5.3%. The two Paris-listed companies are benefiting from the work that follows AI adoption: integrating models into workflows, managing data and building governance systems. That work is particularly valuable in sectors such as defence, aerospace, healthcare and critical infrastructure, where AI must be fitted around specialist software and tightly controlled operational processes. A second trend is reinforcing the position of Europe's incumbents: growing demand for greater control over AI deployment. Publicis Chief Executive Arthur Sadoun has said clients increasingly want advanced AI models operating within environments where they retain control over their technology and their data. The preference is strongest in defence, aerospace and critical infrastructure, where concerns over sovereignty, security and compliance are particularly acute. Airbus' decision to use Scaleway -- owned by French telecoms group Iliad -- for sensitive industrial and defence applications, alongside AI tools developed with Mistral, reflects that shift. Airbus expects around 70 critical applications to run on Scaleway by the end of 2028. OVHcloud's public-cloud revenue rose 20.2% in its third quarter, providing early evidence that demand for European-controlled AI infrastructure -- not exposed to extraterritorial laws such as the U.S. Cloud Act -- is beginning to translate into commercial growth. Europe's technology incumbents still need to prove that AI-driven demand can be sustained and that margins can withstand the automation of lower-value consulting and software work. Recent results, however, suggest the biggest beneficiaries of AI may not be limited to those building the models. Increasingly, they may be the companies that make those models usable inside the world's largest organisations. (Reporting by Leo Marchandon in Gdansk; Editing by Matt Scuffham and Tomasz Janowski)