面向欧洲企业的私有AI：合规与性能的两全之道

PoVDeloitte 2025 Table of contents Introduction 4 1.1 Background on GenAI in Europe41.2 Digital transformation pressure in European markets41.3 Private and Sovereign AI: a strategic priority41.4 Regulatory reality: why do European organizations need Private AI51.5 GDPR and data sovereignty requirements51.6 EU AI Act compliance considerations51.7 Industry-specific regulations5 2. Benefits of Private AI infrastructure and success stories6 2.1. Three core benefits of Private AI infrastructure62.4. Strategic use-cases for German organizations6 3. Our Private AI offering7 3.1. Design principles for secure, scalable AI73.2. Functional scope83.3. Enterprise success stories8 4. Intel OpenVINO™ Toolkit: Open Source, AI Acceleration9 4.1. Why does this matter?94.2. OpenVINO™ in enterprise Private AI deployments94.3 CPU vs GPU performance for AI10 5. Implementation framework11 5.1. Your path to Private AI115.2. Three-Phase implementation approach11 6. Business Impact and Value Proposition12 Executive Summary European businesses face a critical AI dilemma: how toleverage artificial intelligence while maintaining strictcompliance with GDPR, the EU AI Act, and industry-specific regulations. Traditional cloud AI solutions createdata sovereignty risks and regulatory gaps, while GPU-dependent infrastructure requires substantial hardwareinvestment. Deloitte and Intel, as strategic alliancepartners, address this challenge through consulting andintegration services based on compliance-by-design andan open-source GenAI architecture optimized for Intelhardware. We bring expertise in deploying and integratingenterprise-ready Private AI solutions precisely wherecompany data lives—on-premises, in private clouds, orhybrid environments—without vendor lock-in or costlyGPU requirements. Key takeaways from this POV •Enterprises can achievesignificant cost savingsby deployingAI on existing Intel®Xeon®processors, avoiding costlyGPU upgrades. •Open-source Intel OpenVINOTMtoolkitdelivers competitiveperformance (18–75 tokens per second on standard CPUs[1]),reducing dependency on expensive GPU hardware whilemaintaining enterprise reliability. •Complete data sovereigntyis ensured by deploying AI exactlywhere company data resides—on-premises, in private clouds,or hybrid environments—addressing GDPR and EU AI Actcompliance requirements that carry penalties of up to€35 million[2]. •Lower infrastructure costsand operational efficiencies candrive significant ROI, with rapid payback periods comparedto traditional GPU-centric approaches. •Amodular, Kubernetes-based architectureenables fastdeployment across existing Intel-based environments,accelerating AI adoption without vendor lock-in orcloud dependency. 1.Introduction 1.3 Private and Sovereign AI: astrategic priority 1.1 Background on GenAIin Europe and China ($138B) makingmassive commitments, whilethe EU announced a €200 billioninvestment in AI in February, plus anadditional €20 billion fund for fiveAI gigafactories equipped with over100,000 processors, and focusedon the development and training ofnext-generation AI models.[5] Europe’s approach to AI is definedby compliance, data protection,and strategic caution. While globalhyperscalers like Azure, AWSand Google offer rapid GenAIdeployment, European enterprisesprioritize responsible, sustainable,and compliant AI infrastructures.This restraint is not a weakness buta strategic advantage that allowsproactive alignment with evolvingregulations in advance of externalpressure. As AI becomes a central part ofbusiness operations, countries areinvesting hundreds of billions tosecure technological independenceand protect national securityinterests.Recent investment datashows nations like Saudi Arabia($500B), the US ($500B), 1.2 Digital transformationpressure in European markets Digital transformation is puttingpressure on European markets.Global spending on solutionspowered by generative AI isprojected to reach almost €200billion, amounting to a compoundannual growth rate (CAGR) of 29%over the next four years.[1] •Sovereign AIgoes even further,offering complete independenceby using European solutions likeMistral, which provides full modelaccess and modification rightsunder open-source licensing. TheGerman government has pledgedto increase AI research anddevelopment for national defense,so companies under contractwith the Ministry of Defensehave rigid constraints on their AIinfrastructure.[7] European companies now facea pivotal choice betweenthree approaches. AI presents the next great challengein digital transformation andchange management, introducingnew applications, features, andmethodologies that enhanceefficiency and productivity. •Public AIfrom hyperscalers suchas AWS, Azure, and Google Cloudoffers scalability and ease ofdeployment but raises concernsabout data residency, vendorlock-in, and dependency on foreigninfrastructure. "We aim to mobilize a total of€200bnfor Al investmehts inEurope" - Ursula von der LeyenEU