EU vs US paths on AI regulation and Luxembourg’s strategic choices

By Erwin SOTIRI

Partner, Jurisconsul Law Firm

Inside the White House’s AI playbook: Deregulation, infrastructure, and strategic dominance

The “Winning the Race: America’s AI Action Plan”, released by the White House in July 2025, is a comprehensive U.S. federal blueprint outlining over 90 policy actions across three strategic pillars. The Plan’s overarching goal is to cement U.S. dominance in artificial intelligence (AI) for economic competitiveness and national security. Key points and recommendations include:

• Pillar I – Accelerate AI Innovation: Emphasises deregulation and rapid innovation led by the private sector. The plan calls for removing “red tape” and onerous regulations that might stifle AI development. It rescinds previous guidelines seen as burdensome and directs agencies to review and repeal rules that “unnecessarily hinder AI development or deployment”. Federal funding will be steered away from U.S. states that impose overly restrictive AI laws. The Plan also highlights support for open-source AI, encouraging the availability of open models and weights to spur research and adoption, while leveraging federal procurement to steer AI development (e.g., prioritising contracts to “frontier” AI models deemed free of top-down ideological bias and supportive of free expression). Notably, it directs updates to procurement guidelines to ensure AI systems uphold free speech and “objective truth” rather than enforcing any particular ideology.

  
  

• Pillar II – Build American AI Infrastructure: Recognises AI’s massive demand on hardware, energy, and talent. The plan proposes to streamline permits and accelerate the build-out of physical infrastructure like data centres, semiconductor fabrication plants, and energy generation capacity. This includes establishing expedited environmental reviews (e.g. new categorical exclusions under NEPA) to fast-track data centre and chip factory construction. We may make federal lands available for AI infrastructure and implement security measures to keep adversarial technology out. A national initiative will identify and train workers in "high-priority occupations" (such as electrical engineers and data centre technicians) essential for the AI era, including apprenticeships and workforce development programs. The plan also stresses upgrading the electric grid (preventing premature power plant shutdowns, expanding nuclear and geothermal energy, etc.) to meet AI’s energy needs. Additionally, it prioritises boosting domestic semiconductor manufacturing (leveraging the CHIPS Act investments but removing extraneous policy conditions on funding) and integrating AI tools into chip production. High-security AI computing facilities for military and intelligence use will be built, alongside technical standards for secure AI centres. Cybersecurity of AI systems is addressed by encouraging “secure-by-design” practices (like pre-deployment safety testing, access controls, and red-teaming of models) and developing AI-tailored incident response protocols. NIST is tasked with creating voluntary AI cybersecurity and safety benchmarks to guide industry and government procurement.

  
  

• Pillar III – Lead in International AI Diplomacy and Security: Position AI as a geopolitical arena. The plan asserts that the U.S. must lead globally in AI standards and alliances, especially to outcompete China. It proposes to create an “America’s AI Alliance” by exporting “full-stack” AI technology packages (U.S.-made hardware, models, software, and support) to allied nations. The Department of Commerce, in partnership with industry consortia, will facilitate deals delivering secure AI systems to partners, effectively spreading U.S. standards abroad. Simultaneously, the U.S. will tighten export controls on critical AI components (advanced chips, etc.), enhance monitoring to prevent diversion of technology to adversaries, and push allies to adopt similar controls. The Plan explicitly aims to counter Chinese influence in international AI forums and promote “American values-based” technical standards globally. Other security measures include evaluating cutting-edge, "frontier" AI models for national security risks and recruiting top AI researchers into government service for defence and intelligence needs. The Plan’s tone makes clear that “winning the AI race” is viewed as non-negotiable for U.S. prosperity and security.

Cross-cutting themes in the U.S. Action Plan include a focus on American workers, values, and security. The plan insists AI-driven automation should “expand opportunities and raise living standards” for workers rather than replace them. It also stresses guarding against “Orwellian” misuses of AI – aligning AI with principles of freedom (e.g., avoiding authoritarian surveillance or social credit systems) even as it accelerates adoption. There is a heavy emphasis on minimising regulatory friction to unleash innovation, using government purchasing power and deregulation as levers to speed AI development. In summary, America’s AI Action Plan maps out an aggressive, innovation-first strategy: turbocharging R&D and infrastructure, loosening regulatory constraints, and asserting U.S. leadership globally to ensure the next generation of AI is dominated by American technology and aligned with U.S. interests.

Europe vs America on AI: Where regulation, innovation, and strategy collide

The U.S. plan’s vision and approach can be contrasted with the current European Union (EU) AI regulatory and policy framework, including the forthcoming EU AI Act, the General Data Protection Regulation (GDPR), and various European Commission AI strategies. While there are areas of alignment between the U.S. and EU (both recognise the transformative power of AI and the need for leadership), there are also significant divergences in philosophy and method. Additionally, the U.S. plan introduces some novel approaches that highlight gaps or differences relative to the EU’s stance. Below, we outline key points of alignment and divergence, referencing EU strategic documents where relevant (from the EU’s 2018 AI strategy up to the 2025 “AI Continent Action Plan”).

Areas of alignment and common goals

Despite differing rhetoric, the U.S. Action Plan and EU strategies share several broad goals:

• Global AI Leadership: Both the U.S. and the EU explicitly strive to be frontrunners in AI on the world stage. The White House plan frames AI dominance as critical to national prosperity and security, and similarly the EU’s recent “AI Continent Action Plan” (April 2025) proclaims that global AI leadership is “up for grabs” and aims to “turbocharge” Europe’s AI sector to enhance strategic autonomy. EU leaders, including Commission President Ursula von der Leyen, have signalled determination to make Europe a “serious contender” in AI, backing this ambition with initiatives like the InvestAI fund (€200 billion) to boost AI investment. Both strategies acknowledge that cutting-edge AI (e.g., foundation models, generative AI) is evolving quickly, and they seek to position their respective blocs at the forefront of these advancements.

  
  

• Investment in AI innovation and R&D: There is alignment in recognising the need to fuel AI innovation through investment. The U.S. plan emphasises accelerating innovation by mobilising the private sector and removing barriers. The EU, for its part, has outlined an “ecosystem of excellence” in its 2020 White Paper on AI, focusing on boosting research, supporting startups, and scaling AI solutions. Through programmes like the Horizon Europe research funding, the EU has been increasing R&D spending on AI. The Coordinated Plan on AI (first launched in 2018 and updated in 2021) aligns EU and Member State funding efforts to spur AI innovation and deployment across sectors. Both the U.S. and the EU, therefore, see significant public investments and public-private partnerships as crucial to AI competitiveness.

  
  

• Infrastructure and capacity building: Both plans stress building robust foundations for AI. The U.S. Pillar II highlights physical infrastructure—data centres, advanced chips, high-performance computing, and an upgraded energy grid. The EU has similarly prioritised infrastructure: one pillar of the AI Continent Action Plan is dedicated to “computing infrastructure” (expanding Europe’s compute capacity and cloud/edge infrastructure). The EU’s Digital Compass 2030 targets include significantly increasing EU capacity in semiconductors and cloud, and initiatives like the EuroHPC Joint Undertaking (to build world-class supercomputers) and the EU Chips Act (to boost semiconductor manufacturing) mirror U.S. efforts like the CHIPS Act. Both frameworks also emphasise developing the AI talent pipeline (skills and education). The U.S. plan calls for training workers in high-demand AI infrastructure jobs, while the EU Action Plan has an entire pillar on skills, aiming to train AI specialists and upskill the workforce at scale. In essence, bolstering computing power, data capacity, and human capital for AI is a shared priority.

  
  

• Addressing AI risks and security concerns: There is broad agreement on the need to manage AI’s risks, though the approaches differ. Both recognise issues like AI-driven bias, safety, and misuse. For example, the U.S. plan encourages AI model safety testing (red teaming) and development of security benchmarks. The EU’s AI Act explicitly aims to ensure AI systems are safe, transparent, and respect fundamental rights. It mandates risk management, testing, and human oversight for high-risk AI systems, which parallels the U.S. interest in pre-deployment testing and fail-safes (albeit the EU will require these by law). Both also reject certain harmful uses of AI: the EU AI Act bans “unacceptable risk” AI such as social scoring and mass surveillance, reflecting a stance against “Orwellian” AI abuse that U.S. officials likewise rhetorically oppose. Furthermore, on international security, both frameworks see AI as pivotal in the geopolitical arena. The U.S. focuses on export controls and protecting AI from adversaries, and the EU too has been tightening controls on sensitive technology exports (often coordinating with U.S. measures regarding, e.g., China). Both the U.S. and EU participate in international AI cooperation forums (like the OECD AI Principles and the Global Partnership on AI), indicating alignment in certain high-level ethical principles (e.g. human rights, democracy) even if implementation differs.

  
  

• Public-private collaboration and ecosystem approach: Both approaches underscore working with industry and other stakeholders. The U.S. plan explicitly seeks private sector input (via RFIs and partnerships) on removing barriers to AI adoption and aims to cultivate a “try-first” culture across industries with regulatory sandboxes. The EU likewise has engaged industry and academia in shaping policy – for instance, through the High-Level Expert Group on AI, which crafted ethics guidelines in 2019, and through the European AI Alliance (a forum for stakeholders). The AI Act even provides for regulatory sandboxes where companies, especially startups, can test AI innovations under supervision of authorities without immediately facing full compliance burdens. Both recognise that effective AI governance involves multi-stakeholder input and iterative learning, not just top-down rules.

Both the U.S. and EU acknowledge AI’s transformative potential and the need for proactive policy action. They share goals of promoting innovation, investing in enabling resources (from data to talent to HPC), ensuring AI is developed safely, and maintaining a competitive edge internationally. These common themes provide a basis for transatlantic cooperation despite differences in regulatory philosophy.

AI lawfare: Europe codifies, US commercialises

While the end goals align in many ways, the means and philosophy of the U.S. Action Plan diverge sharply from the EU’s regulatory approach:

• “Light-touch” deregulation vs. “risk-based” regulation: The clearest contrast is the U.S. plan’s anti-regulatory stance versus the EU’s inclination to regulate. President Trump’s AI Action Plan pointedly rolls back or avoids new regulations at the federal level, arguing that AI is “far too important to smother in bureaucracy at this early stage”. It instructs agencies to dismantle “unnecessary” regulatory barriers and even disincentivises U.S. states from enacting strict AI rules. In effect, the U.S. is embracing a market-driven, innovation-first strategy, with the government as an enabler (through funding, deregulation, and procurement) rather than a strict regulator. Europe’s approach is fundamentally different: the EU has crafted the world’s first broad AI law – the EU Artificial Intelligence Act – which takes a precautionary risk-based regulatory approach. The AI Act will classify AI systems by risk (unacceptable, high, limited, minimal) and impose binding legal requirements on developers and users of higher-risk AI (for example, strict data governance, transparency, human oversight, and conformity assessments for “high-risk” systems in domains like healthcare, finance, employment, policing, etc.). The EU believes that clear rules are needed to ensure trust in AI, even if that means more upfront compliance costs. This is almost the mirror image of the U.S. plan, which explicitly seeks to delay or avoid heavy regulation to not “unduly restrain innovation”. As a result, the EU’s framework is more restrictive and enforcement-focused, while the U.S. is currently favouring voluntary guidelines and removing hurdles. For instance, where the EU AI Act will legally ban certain AI practices outright (e.g. social scoring, some uses of biometrics), the U.S. plan does not institute new bans (it rhetorically warns against “Orwellian” uses but does not create prohibitions in law). Instead, the U.S. emphasises not purchasing or supporting AI that conflicts with American principles (like free expression) and using market pressure (export controls, procurement choices) rather than blanket bans.

  
  

• Protecting fundamental rights vs. free market & free speech emphasis: EU AI policy is deeply rooted in fundamental rights (privacy, non-discrimination, human dignity, etc.), reflecting European societal values and legal norms. The GDPR, for example, provides a strict baseline for data protection – any AI system in Europe that processes personal data must comply with GDPR’s requirements for lawfulness, transparency, data minimisation, and security. GDPR Article 22 also gives individuals the right not to be subject to purely automated decisions with significant effects, or to at least have a human review, which puts a check on unchecked algorithmic decisions. The upcoming AI Act builds on this rights-centric ethos: the European Parliament insisted that AI systems in the EU be “safe, transparent, traceable, non-discriminatory and environmentally friendly,” and subject to human oversight. In practical terms, EU regulations will force companies to address issues like bias (with obligations to use representative, bias-tested data for high-risk AI) and transparency (users must be informed when they are interacting with an AI, etc.). By contrast, the U.S. Action Plan, under the Trump administration, pivots away from some of the ethical and rights-focused language that had been present in prior U.S. initiatives (such as the OSTP’s 2022 AI “Bill of Rights” blueprint, which emphasised privacy, civil rights, and democratic values). The 2025 Plan instead stresses free speech and ideological neutrality in AI above other concerns. It actually directs the removal of references to “misinformation” or “DEI (diversity, equity, inclusion)” in federal AI risk management guidelines, signalling a deprioritisation of those social concerns. The emphasis is on preventing what it calls “top-down ideological biases” – essentially ensuring AI systems (like large language models) do not implement content moderation or policies that the administration views as biased censorship. This is a significant divergence from the EU, where there is concern that AI might produce too much harmful content (hate speech, disinformation) and thus calls for stricter oversight and limits on AI outputs (the EU AI Act, for instance, will require generative AI to be designed to prevent unlawful content and to disclose AI-generated content).

In sum, the EU prioritises protection from AI harms via regulation, whereas the current U.S. approach prioritises unfettered innovation and freedom from regulation, trusting that a combination of market forces and targeted government action (infrastructure, security) will suffice.

• Comprehensive framework vs. fragmented governance: The EU is enacting a uniform, binding legal framework (AI Act) that will apply across all member states and even extraterritorially to providers outside the EU offering AI in Europe. This comprehensive approach aims for legal certainty and a single set of rules for the EU’s single market. By contrast, the U.S. currently lacks a single federal AI law – governance is fragmented between state laws, sectoral regulations, and federal agency guidelines. Prior to Trump’s Action Plan, U.S. efforts were piecemeal: e.g., New York City’s Bias Audit Law requires bias audits for hiring algorithms, some states like Colorado introduced AI accountability laws, and agencies like the FTC have warned against unfair AI practices. The Biden Administration had relied on frameworks like the voluntary AI Bill of Rights and NIST’s AI Risk Management Framework – non-binding guidelines encouraging ethical AI. The US AI Action Plan does not propose a new binding federal law, but it does assert federal preemption in spirit (seeking to prevent stricter state-by-state AI rules).

Thus, a divergence is that the EU will have a legally enforceable regime by 2026 (with fines, conformity assessments, and an EU AI Office to oversee implementation), whereas the U.S. is currently avoiding such blanket rules, preferring flexibility. This could lead to tension for companies operating transatlantically: the same AI product might face heavy documentation and human-rights assessment in the EU but encounter a more permissive environment in the U.S.

• Scope of Ethical Considerations:The EU frameworks take a broad view of AI’s impact – including ethical and societal dimensions like privacy (GDPR), consumer protection, environmental impact, etc. For instance, the European Parliament pushed for AI systems to be environmentally friendly and energy-efficient as part of the AI Act’s principles. The U.S. plan, however, notably omits certain topics. As noted in industry analyses, America’s AI Action Plan is silent on issues like AI and intellectual property (copyright) and data privacy. The EU, in contrast, has been grappling with these issues: the AI Act will require transparency about copyrighted data used in training generative models, and the EU’s broader digital policy includes the Digital Services Act (DSA) and Digital Markets Act (DMA) which regulate online content and competition (affecting AI-driven platforms). The U.S. plan’s omission of a stance on training data legality (e.g., fair use vs. copyright) and privacy suggests a looser ethical regulatory framework, whereas the EU tends to preemptively legislate these matters. Additionally, when it comes to bias and nondiscrimination, the EU directly legislates it (requiring algorithms, especially in “high-risk” areas like employment or credit, to be designed to minimise bias). The U.S. acknowledges bias as a concern, but the Action Plan’s remedy leans more on industry self-correction and removing government rules that might inadvertently cause bias (the Plan even reviews past FTC enforcement to ensure it doesn’t “unduly burden AI innovation”). In short, the EU uses prescriptive rules to ensure AI is trustworthy, while the U.S. currently favours ex post enforcement or voluntary measures, fearing that strict rules could stifle innovation early on.

  
  

Export controls, compute power, and ideological AI: The U.S. plan the EU did not write

The U.S. AI Action Plan introduces or emphasises certain approaches that either go beyond current EU policies or, conversely, highlight areas where the EU is more proactive. Key points include:

• Strategic Export of AI Technology (“AI Diplomacy”): The U.S. Plan’s idea of assembling “full-stack” AI export packages for allies is a novel geopolitical-economic tool not explicitly mirrored in EU policy. While the EU certainly cooperates with partners (e.g., through research partnerships and global forums), it has not framed its AI strategy in terms of exporting European AI systems wholesale to allied countries. The U.S. is effectively leveraging AI for diplomatic influence (similar to defence exports) and aiming to set de facto standards abroad. The EU’s focus, in contrast, has been on setting regulatory standards globally via the “Brussels effect” – i.e., making its AI rules and ethical approach a global benchmark. The U.S. approach could complement EU efforts if aligned (e.g., Western allies sharing AI solutions), but it could also create friction if U.S.-exported AI systems do not meet EU requirements.

Gap/Opportunity: Luxembourg and the EU might consider developing their own strategy for promoting trusted AI exports (for example, AI solutions that adhere to EU values) to friendly nations, to both spread ethical AI and support European industry.

• Regulatory simplification: Interestingly, the EU in 2025 has acknowledged the need to simplify and speed up AI-related processes – one of the pillars of the AI Continent Action Plan is “regulatory simplification”. This suggests the EU is aware that overly cumbersome rules could hinder AI uptake. However, the U.S. plan goes further in practice: it actively seeks out rules to abolish and even ties federal funding to a state’s regulatory friendliness. In areas like infrastructure, the U.S. plan mandates swift environmental permitting for AI projects, whereas EU projects often face lengthy permit processes. The EU is beginning to address this (e.g., proposing streamlined permitting for green tech and presumably for data centers through initiatives like the upcoming Cloud and AI Development Act). Still, the U.S. sense of urgency and “full steam ahead” deregulation is more extreme. Gap: The EU could lag in deployment speed. On the other hand, the EU’s careful approach might avoid pitfalls (such as environmental harm or untested systems causing damage). This divergence presents Luxembourg with an opportunity to strike a balance—implementing EU standards efficiently without unnecessary bureaucracy, potentially by pioneering faster approval processes or sandboxes nationwide.

  
  

• Values and content moderation: A novel element in the U.S. Plan is the requirement that government-contracted AI models be ideologically “neutral” and protective of free speech. This reflects a domestic political stance (concern that AI like chatbots could be biased or censorious). The EU’s AI Act and related policies do not have an equivalent notion; instead, EU concerns about AI output focus on preventing illegal content (hate speech, disinformation) and bias against protected groups. This difference could lead to transatlantic policy tension: for instance, if a U.S. AI model is designed to not filter certain extreme content in the name of neutrality, that might clash with EU laws (e.g., the DSA’s requirements to remove illegal hate speech or the AI Act’s mandate to prevent the generation of illegal content).

Novel Approach: The U.S. framing of “AI and free speech” is relatively novel on the government policy level and not present in EU frameworks, which are more about safeguarding users than protecting AI’s right to output anything. This could be an area where Luxembourg and EU might diverge from the U.S., maintaining that some content moderation in AI is necessary to protect citizens (e.g., against AI-generated defamation or extremist propaganda). However, the U.S. emphasis on avoiding centralized bias could spark discussion in Europe about how to ensure AI systems are pluralistic and free from undue private control, an angle the EU has not explicitly legislated on.

• Open-Source AI and access to compute: The U.S. plan explicitly encourages open-source AI models and open weight sharing as a driver of innovation. It recognises that many users (including small businesses and researchers) need access to models they can inspect and run locally. While the EU has funded open-source AI research, its regulations apply regardless of open or closed source (with debates during AI Act drafting on how to treat open-source developers). The U.S. push for openness includes exploring ways to provide startups and academia with easier access to large-scale compute power (possibly through novel financing or compute-sharing programs). The EU’s AI Innovation Package (2024) similarly aimed to improve access to resources for AI startups, including compute and data. However, the scale and directness of U.S. actions (e.g., potentially government-brokered cloud capacity deals or compute credit programs) may differ. Opportunity: Luxembourg could capitalize on this by creating a national compute resource hub or partnerships to ensure local AI developers (especially SMEs and public researchers) have the infrastructure to experiment, complementing EU-level resources. Aligning with the open-source ethos could also mean supporting local open AI initiatives (which would differentiate Luxembourg as an innovation-friendly environment within the EU).

  
  

• Omissions – Data privacy and liability: As noted, the U.S. plan is largely silent on data privacy, whereas the EU’s GDPR is a foundational pillar for any AI involving personal data. The absence of a U.S. federal privacy law means the Action Plan doesn’t directly address handling personal data in AI (apart from general calls to remove “unnecessary” rules, which could imply a more lenient stance). The EU likely views robust privacy protections as non-negotiable – this is a gap in the U.S. strategy from a European perspective. Additionally, the EU is working on an AI Liability Directive (to make it easier for individuals harmed by AI to seek redress), which has no equivalent in the U.S. plan. The U.S. focus is more on shielding innovators from regulation rather than creating new consumer rights or liabilities.

Over time, this could result in differences in public trust – Europeans might trust AI more knowing there are legal safeguards, whereas the U.S. hopes that rapid innovation benefits will outweigh the downsides. Luxembourg, given its strong rule-of-law and consumer protection culture, may lean towards the EU approach here, but could also explore creative liability-safe sandboxes (where companies that test AI under regulator oversight get some liability protection as long as they are transparent and fix issues).

In summary, the EU and U.S. approaches to AI share a common vision of leadership and responsible innovation but differ in regulatory intensity and value prioritisation. The U.S. 2025 Action Plan marks a shift toward a more laissez-faire, innovation-driven policy, contrasting with the EU’s more precautionary, rights-focused framework. These differences offer valuable insights for Luxembourg, demonstrating a range of policy options from which Luxembourg can develop a balanced, forward-thinking national AI strategy. Leveraging the alignments (shared objectives) while addressing the differences will be essential for positioning Luxembourg as an AI leader that is both EU-compliant and innovation-friendly.

Strategic choices for Luxembourg’s AI policy

Luxembourg can create a national AI strategy that is both innovative and forward-thinking, drawing inspiration from the dynamism of the U.S. Action Plan and the robust governance frameworks of the EU. The following suggests a draft strategy for Luxembourg designed to help Luxembourg proactively address emerging trends, mitigate risks, and capitalise on opportunities in AI, while remaining compliant with EU laws and surpassing them to position Luxembourg as a leader in responsible, future-ready AI.

Each guideline targets specific focus areas, proposes actionable steps, and considers potential challenges and opportunities, including the involvement of private sector and civil society stakeholders.

1. Balancing AI innovation ecosystem (combine agility with trust)

Luxembourg should promote AI innovation aggressively while upholding the high standards of trust and safety expected in Europe. A balanced approach can be achieved by borrowing the U.S. emphasis on reducing unnecessary barriers and the EU commitment to fundamental rights:

• Streamline regulations and encourage sandboxes: Ensure that Luxembourg’s implementation of the EU AI Act is business-friendly and clear. Establish a national AI regulatory sandbox programme in coordination with the EU AI Act’s provisions, where companies (especially startups and SMEs) can develop and test AI systems with supervisory guidance but minimal legal risk. This allows experimentation (similar to the U.S. “try-first” culture) without compromising eventual compliance. For example, Luxembourg’s financial regulator (CSSF) could run a sandbox for AI in fintech, given the country’s large financial sector, to let banks and fintech startups pilot AI-driven services (like automated investment advice or fraud detection) under oversight. The government should also review existing national laws and administrative processes to eliminate any unnecessary red tape that slows down AI projects (much as the U.S. plan does at the federal level), provided those changes don’t conflict with EU directives. One actionable step could be creating a fast-track approval process for AI research projects or AI-driven pilot programmes in public services, with quick ethics reviews and temporary authorisations.

  
  

• Soft law and standards: Involves creating guidelines and voluntary standards in collaboration with industry and academia to complement formal legislation. For example, Luxembourg’s government, possibly through its national innovation agency (such as Luxinnovation), can release an AI Ethics and Risk Management Best-Practices guide for businesses. This guide would convert EU principles (such as transparency and non-discrimination) into practical checklists that companies can easily implement. This approach positions Luxembourg as a facilitator rather than merely an enforcer. Ensure these guidelines align with international standards (ISO/IEC AI standards and NIST’s AI Risk Management Framework, excluding U.S. political redactions). This provides companies with clarity and assists them in meeting EU requirements while also aligning with U.S. expectations, bridging the gap between the two systems.

  
  

• Support open innovation and open data: Embrace the U.S. Plan’s insight that open-source AI can accelerate adoption. Luxembourg can spearhead the creation of an “AI open innovation hub” – possibly an expansion of initiatives like Digital Luxembourg – where open-source AI models and datasets are made available to local startups and researchers. The government could provide grants or cloud credits for projects that develop open AI solutions addressing Luxembourg’s needs (e.g., natural language processing for Luxembourgish and other local languages). This aligns with EU open-data efforts and the European Data Strategy, while also reflecting the U.S. view that sharing models fuels progress. By nurturing a local community of developers around open AI (through hackathons, challenges, and support for participation in open-source projects), Luxembourg builds expertise and a reputation as an AI innovation sandbox within Europe.

  
  

• Challenges: Maintaining this balance will be challenging. There is a risk of either slipping into a lax regime that violates EU rules or overcompensating with bureaucracy. Coordination with EU authorities is crucial to ensure that any national flexibility (like sandboxes or funding incentives) is compliant and perhaps even sets examples for EU-wide practices. Also, resource constraints are an issue – Luxembourg’s regulators will need enough expertise to supervise novel AI activities in sandboxes and to engage with industry quickly. Capacity-building within government (training regulators on AI) is necessary.

  
  

If successful, Luxembourg can benefit immensely. A reputation for efficient yet responsible AI regulation can attract AI startups and investment to the country, much as its financial stability attracted banks. It can become a preferred location to pilot new AI solutions for the European market. Ultimately, this supports Luxembourg’s economic development, creating high-skilled jobs and diversifying its tech sector, while safeguarding citizens with early oversight. By fostering innovation in a principled way, Luxembourg strengthens both its economy and the trust of society in AI.

2. World-class AI infrastructure and data ecosystems.

To maintain a leading position in AI, Luxembourg must ensure that computing power, data availability, and connectivity are not obstacles. Due to its limited size, Luxembourg is unable to outspend larger countries, but it can strategically focus on niching and partnering to develop a strong AI infrastructure.

• High-performance computing (HPC) and cloud infrastructure: Expand on Luxembourg’s existing investments like the MeluXina supercomputer (which is part of the EU’s EuroHPC network) to provide accessible computing power for AI developers. The government should evaluate the need for additional AI-dedicated computing resources – for instance, a national AI computing cluster with GPUs/TPUs that startups and research institutions can use on demand. If budgets are limited, Luxembourg can partner with EU programmes or even U.S. initiatives: for example, if the U.S. implements its plan to improve access to AI compute for academia, Luxembourg’s universities could participate in such programmes or form alliances with U.S. cloud providers to gain favourable terms. Domestically, ensuring affordable cloud services (possibly via public-private cloud initiatives) will encourage local AI experimentation. The AI Continent Action Plan pillar on computing infrastructure suggests EU funding may be available to support this – Luxembourg should actively tap into those funds and possibly host one of the EU’s “AI Gigafactories” or data centre projects (the Commission has calls for interest for such projects).

  
  

• Data availability and sharing: Data is the fuel for AI, and Luxembourg can innovate in enabling data-driven AI while respecting privacy. Building on the EU’s Data Governance Act and Data Act, Luxembourg can create a national framework for data sharing and data trusts focusing on key domains. For example, in the financial sector, encourage banks and fintech firms to share anonymised datasets for AI innovation (fraud patterns, credit risk data) in a secure data trust, perhaps facilitated by the government or a neutral industry association. Similarly, for public sector data, adopt an open-by-default approach: publish high-quality open datasets (in transportation, health stats, environmental data, etc.) that entrepreneurs and researchers can use to develop AI solutions. Luxembourg’s multilingual environment (Luxembourgish, French, German, and generally accepted English) is an opportunity – by curating multilingual datasets (like parliamentary records and public service information in multiple languages), Luxembourg can attract AI researchers working on language models and translation AI for low-resource languages. This complements EU efforts to build common European data spaces for various sectors, but Luxembourg can be an early mover by launching its own sectoral data sandbox initiatives. In healthcare, for example, work with hospitals and patient groups to enable privacy-compliant data sharing for AI research (perhaps through a trusted third party that manages consent and anonymisation). Strong GDPR compliance will be non-negotiable here – Luxembourg can turn GDPR into an advantage by pioneering techniques like privacy-preserving data analytics (e.g., federated learning, where AI models train across datasets without raw data leaving secure enclaves).

  
  

• Digital Infrastructure and 5G/6G: Ensure that Luxembourg’s digital backbone (broadband, 5G networks) stays top-tier. AI applications (from autonomous vehicles to smart city sensors) will generate and rely on fast communications. Luxembourg should continue its investments in 5G and look ahead to 6G, possibly partnering in EU’s joint initiatives for next-gen networks. A concrete project could be making Luxembourg City a “smart city AI lab”, outfitted with IoT sensors and edge computing nodes to trial AI in traffic management, energy use optimisation, etc. This would not only improve city services but also provide a live testbed for AI companies (with appropriate safeguards and resident involvement).

  
  

• Sustainable Energy for AI: Recognising that AI computing is energy-intensive, Luxembourg should integrate its AI and green energy strategies. This could mean incentivising data centres (existing and new) to run on renewable energy and use waste-heat recovery (practices already encouraged in Luxembourg’s data center sector). Also, explore small-scale nuclear or geothermal projects as stable power sources, in line with U.S. Pillar II’s nod to new energy sources, albeit scaled to Luxembourg’s context. Ensuring energy supply for AI growth will protect Luxembourg from the risk of energy bottlenecks as AI usage soars.

  
  

• Challenges: Luxembourg’s small size means it must be selective – it cannot build everything domestically. International cooperation is vital. There is a risk of dependence on foreign providers for cloud and compute (many AI companies use U.S. cloud platforms). To mitigate this, Luxembourg should diversify and also contribute to EU strategic tech autonomy where possible (like supporting European cloud initiatives such as Gaia-X). Another challenge is ensuring any data sharing does not spook privacy concerns; strong anonymisation and stakeholder engagement (see Guideline 5 on civil society) will be needed to build trust in data initiatives.

  
  

• Opportunities: By bolstering infrastructure, Luxembourg makes itself an attractive location for AI R&D centres and startups. If computing resources and rich datasets are readily available in a supportive environment, companies will come to Luxembourg to utilise them. Moreover, focusing on areas like multilingual AI and financial AI could carve out niches where Luxembourg leads in expertise. This strengthens the country’s international branding as a high-tech hub (beyond its finance reputation) and can yield spinoff benefits for the broader economy (startups, academic collaborations, etc.). In international collaboration, Luxembourg can offer to host EU-wide AI resources – for example, expanding the supercomputing centre – which enhances its standing and fosters alliances (with both EU members and potentially U.S. researchers who might collaborate using these resources).

  
  

3. Skills, talent, and multilingual AI competence

People are at the heart of any AI strategy. Luxembourg should aim to develop, attract, and retain top AI talent, while also ensuring its workforce and society are prepared for AI-driven changes. Additionally, Luxembourg’s multilingual character can be turned into an asset in AI development:

• Education and workforce development: Launch a “Luxembourg AI Skills Initiative” that spans from schools to continuing education. This could include integrating basic AI and coding curricula in secondary schools (to prepare the next generation early), offering incentives for students to pursue STEM and AI-related degrees (scholarships, grants, or guaranteed internships in AI labs/companies), and expanding programmes at the University of Luxembourg and local research institutes (like LIST, Luxembourg Institute of Science and Technology) for AI specialisations (e.g., master’s and PhD programmes in AI, data science, and machine learning). The U.S. plan’s focus on not displacing workers but empowering them through AI is pertinent – Luxembourg can similarly emphasise upskilling the current workforce: for example, partner with industry to provide short AI training courses for professionals in finance, healthcare, and public administration to learn how to use AI tools effectively in their jobs. Encourage apprenticeships in tech (leveraging the national apprenticeship programmes) for roles like data technicians or AI model testers, echoing the U.S. idea of focusing on high-demand AI-era occupations.

  
  

• Attracting global talent: Position Luxembourg as an appealing destination for AI researchers, engineers, and entrepreneurs. This might involve creating a fast-track visa or immigration scheme for AI talent, similar to tech visa programmes in other countries. Additionally, build on Luxembourg’s high quality of life and international environment to market itself, e.g., a campaign highlighting successful AI projects or startups in Luxembourg and the opportunity to work in a multilingual, cosmopolitan setting at the heart of Europe. Partner with Luxembourg’s financial industry and European institutions located in Luxembourg to create fellowship programmes (where, for instance, an AI researcher can get funding to work on an AI solution for sustainable finance or for EU public services). By offering attractive research grants or startup incubation specifically in AI (perhaps a dedicated AI track in the Fit4Start startup accelerator programme), Luxembourg can draw in entrepreneurs who might otherwise go to bigger hubs. International collaboration can be key here: consider joint programmes with U.S. universities or tech firms (e.g., an exchange where U.S. AI experts spend a sabbatical in Luxembourg to help kickstart projects, and vice versa, akin to a “Tech Fulbright” idea).

  
  

• Multilingual and multicultural AI: Luxembourg’s linguistic diversity (Luxembourgish, plus many residents speaking French, German, English, Portuguese, etc.) is a unique strength. The government should champion AI projects that cater to multilingual and multicultural contexts. For instance, support the development of language technologies (speech recognition, translation, conversational AI) for less-resourced European languages – making Luxembourg a hub for AI that serves diverse European populations. This aligns well with EU interests (the EU has programmes for language technology and cultural diversity in AI) and addresses a gap where big tech often focuses on English or major languages. Luxembourg could fund a project to create a Luxembourgish GPT or a multilingual public service chatbot that can seamlessly switch languages based on the user – demonstrating cutting-edge NLP (Natural Language Processing) while serving citizens better. Moreover, Luxembourg can offer itself as a test market for AI solutions that need to operate in multilingual settings (a microcosm of the EU market). This would attract companies needing to prove their AI can handle such complexity. Culturally, Luxembourg can encourage AI datasets and algorithms that respect European multicultural values – e.g., avoiding biases against any community – leveraging its own societal mix as feedback in development.

  
  

• Preventing brain drain and inclusion: It’s not enough to train talent; Luxembourg must also keep talent. That means providing career and research opportunities domestically. The state could co-invest with industry in establishing AI Centers of Excellence in key domains (for example, FinTech AI, AI for Logistics, and AI for Space – given Luxembourg’s interest in space mining and satellite tech, an AI centre for space data analytics could be envisioned). Each centre would employ top researchers and engineers, run projects and spin off startups. With these centres, local AI graduates have places to work and grow without leaving the country. Simultaneously, ensure inclusivity in AI education and jobs: promote diversity by encouraging women and under-represented groups in tech to participate (through scholarships and mentorship programs). Engage civil society groups to help reach communities that might be left behind in the AI boom, offering training programmes for digital skills to all segments of the population (so that AI doesn’t widen social inequalities). A strong talent base is arguably the most sustainable advantage in the AI era. By investing in people, Luxembourg ensures it can adapt to and create new technologies rather than just import them. Skilled professionals will contribute to the economy (through innovations, startups, and increased productivity in established firms) and can help the government address societal challenges with AI. A multilingual AI specialisation can make Luxembourg the go-to place for companies that need European language solutions, once again attracting investment and partnerships. Moreover, a populace that is AI-skilled and AI-aware will be more resilient to the disruptions AI may bring (less fear, more ability to shift roles or use AI tools productively), ensuring social stability and inclusive growth in the face of technological change.

  
  

4. Governance, ethical oversight, and anticipatory regulation

While fostering innovation, Luxembourg should also aim to be at the forefront of ethical AI governance – not merely complying with EU rules, but shaping and even exceeding them in a smart way. This guideline focuses on governance structures, anticipatory policymaking, and positioning Luxembourg as a thought leader in AI ethics and regulation:

• Early implementation of the EU AI Act and beyond:Treat the EU AI Act not as a compliance burden but as a framework to build on. Luxembourg should move early to set up the necessary national supervisory authority for AI (potentially expanding the mandate of the National Data Protection Commission or creating a new dedicated AI regulator). By being ahead of schedule in implementing the Act (which fully applies in 2026), Luxembourg can guide its businesses through compliance smoothly and avoid last-minute scrambles. Moreover, Luxembourg could voluntarily adopt higher standards or additional guidance on top of the Act for domains that merit it. For example, while the EU Act provides basic transparency requirements, Luxembourg might develop a voluntary “AI Transparency Label” that companies can earn by disclosing even more information about their AI systems (such as detailed explanations of algorithms to users or publishing ethical impact assessments). This kind of soft certification could appeal to consumers and business partners, giving Luxembourg-based companies a reputational edge for trustworthiness.

  
  

• Adaptive and anticipatory regulation: AI technology evolves rapidly (think of how fast generative AI grew). Luxembourg can institute an “AI Foresight and Audit” unit within its government or digital agency to continuously monitor emerging AI trends (like AI general systems, autonomous weapons, etc.) and anticipate regulatory needs. This unit would collaborate with international experts and bodies (like the EU’s AI Office or OECD AI Policy Observatory) to update national guidelines. If, for instance, new risks emerge (say an influx of deepfake content or advanced AI cyberattacks), Luxembourg could be the first to craft targeted policies or strategies to address them, thus staying ahead of the curve. One idea is to establish a standing multi-stakeholder AI Ethics Committee that meets regularly to review how AI is being used in Luxembourg (in government and industry) and to issue recommendations. Involve ethicists, technologists, civil society, and industry in this committee. This proactive governance is in line with the spirit of the EU’s human-centric approach, but it could be more agile and less formal than EU-wide processes, thanks to Luxembourg’s small scale (it’s easier to convene key players).

  
  

• Enforcement and accountability mechanisms: As AI deployments grow in Luxembourg, it is essential to implement proper accountability measures. For example, entities deploying high-risk AI (as defined by the EU Act) should be encouraged or required to register these systems with the national authority, even before the EU database is fully operational. Additionally, the concept of an AI “algorithmic register” could be voluntarily extended to other areas, such as cataloguing and publicly describing public sector algorithms for transparency. Concurrently, the capacity to audit AI systems should be strengthened: Luxembourg could establish a specialised AI audit team (either within the regulator or as an independent entity) to evaluate algorithms for bias, security, or compliance. This team could assist both regulators and companies seeking external audits, similar to financial audits. By developing such expertise early, Luxembourg can swiftly and credibly address controversies or incidents (such as AI system malfunctions or discrimination), thereby maintaining public trust.

  
  

• Aligning with “American values-based” vs “European values-based” AI:  As highlighted in the comparison, the U.S. and EU place emphasis on slightly different values. Luxembourg should clearly reaffirm European values—such as ensuring that AI in Luxembourg respects privacy, equality, and democracy—while also acknowledging a valid concern from the U.S.: that AI should not be subject to central censorship or politicisation. Practically, this means Luxembourg can advocate for pluralism and fairness in AI algorithms. For instance, it should be ensured that any AI employed by the government (such as in content filtering or decision support) undergoes bias checks for both protected characteristics and viewpoint diversity where relevant. Luxembourg could lead initiatives within EU forums to establish standards for AI impartiality and quality of information, potentially bridging transatlantic perspectives (balancing the fight against disinformation with the avoidance of undue censorship). This forward-thinking approach could position Luxembourg to influence EU discussions on future amendments or guidance for the AI Act (as the Act may undergo updates or delegated acts—Luxembourg should be actively contributing proposals).

  
  

• International ethical leadership: Luxembourg might be small, but it can still lead by example or convene. Consider hosting an annual International Conference on AI Ethics and Governance in Luxembourg, bringing together policymakers from the EU, U.S., and beyond (including voices from smaller states which often get overlooked in big power talks). This can bolster Luxembourg’s profile as a mediator and leader in the global conversation on AI norms. Also, Luxembourg could join or form international working groups on specific issues like AI in finance (perhaps via the Financial Stability Board or OECD) or AI and multilingualism, where it can inject its expertise and values.

  
  

• Challenges: One challenge is avoiding overregulation or creating fear among businesses that Luxembourg is adding extra rules. To mitigate this, keep additional requirements voluntary or incentive-based (like the transparency label being voluntary but encouraged). Also, resources are a constraint: high-quality AI auditing and oversight require experts who are in short supply. Luxembourg might need to pool resources with other EU countries or hire international experts for its audits and foresight activities. As a small country, another challenge is ensuring you don’t get ignored at the big table – hence the need to punch above your weight by being proactive and innovative in proposals.

  
  

• Opportunities: By establishing itself as a model of thoughtful AI governance, Luxembourg can attract companies that actually welcome clarity and ethics (many companies prefer operating where rules are clear and reputation risks are low). It could become the jurisdiction of choice for AI companies aiming to prove they are “trustworthy AI” providers. Additionally, effective governance will protect citizens from harms and thus maintain social licence for AI – people will be more open to AI adoption (in healthcare, transport, etc.) if they see the government is vigilant and responsive on their behalf. Internationally, Luxembourg’s forward-leaning governance contributions (like the conference or participating in EU policymaking actively) will enhance its diplomatic standing and network, potentially opening doors to collaboration and influence that benefit the country’s broader interests.

  
  

5. Private sector and civil society in a multi-stakeholder approach

A robust AI strategy for Luxembourg should be inclusive, involving not just the government but also the private sector (industries, startups) and civil society (academia, NGOs, the general public). This ensures well-rounded policy, public acceptance, and shared responsibility in AI development:

• Encouraging collaboration among government entities, the corporate sector, and startups on AI initiatives that align with national priorities can be beneficial. For instance, in the financial sector, the government might consider establishing an AI innovation hub for fintech in partnership with major banks. This hub could facilitate funding and mentorship for AI startups focused on solutions for regulatory compliance (RegTech), fraud prevention, or enhanced customer service. Such an arrangement could offer private stakeholders early access to innovations while supporting public objectives by reinforcing the finance industry and ensuring that new technologies comply with necessary standards. Similar partnerships could be envisioned in healthcare, such as a consortium of hospitals and AI companies working together to develop medical diagnostic AI under the guidance of health regulators. In logistics, given Luxembourg’s role in freight and logistics, collaboration with cargo companies and universities could help optimise routing through AI. The emphasis should be on aligning these partnerships with Luxembourg’s unique sectors and strengths, fostering mutual benefit and knowledge transfer. In this context, the government might act as a convener and occasional co-funder, which could help mitigate risks for private entities exploring advanced AI solutions.

  
  

• Consultation and Co-Creation of Policy: When developing AI-related policies or regulations at the national level, Luxembourg should continue its practice of consulting a diverse array of stakeholders. However, this could be expanded beyond formal consultations by creating a permanent “AI Forum Luxembourg.” This forum would unite representatives from tech companies (both large and small), financial institutions, startups, trade unions, consumer rights groups, and academia to engage regularly with policymakers. It would serve as a platform for discussing emerging trends, voicing concerns (such as the industry pointing out if a proposed regulation is overly burdensome or civil society raising ethical issues), and collaboratively crafting solutions. By institutionalizing this dialogue, policies are more likely to be balanced and widely supported. For example, if Luxembourg were to develop specific guidance on using AI in employment (such as hiring algorithms), involving employers, tech providers, and worker representatives would result in a more practical and fair outcome.

  
  

• Civil society and public engagement:  Engaging the public in the AI journey is essential. Luxembourg can launch public awareness campaigns about AI, emphasizing both its advantages (such as efficiency, new services, and economic growth) and its risks (like bias and privacy concerns) to educate citizens. Consider establishing an online portal or helpdesk for AI-related inquiries, potentially through the proposed EU AI Office or on a national level, where individuals can ask questions like “Is this AI system legal?” or “What are my rights if an algorithm makes a decision about me?” and receive guidance. Additionally, involve civil society organizations in oversight. For example, consumer protection groups could monitor AI applications in consumer finance or e-commerce, while human rights NGOs could audit AI use in the public sector for rights implications. Luxembourg could also support community-driven AI projects, such as citizen science initiatives where individuals contribute data or feedback to enhance public AIs (imagine a project where citizens assist local authorities in training an AI to detect potholes or monitor air quality using a smartphone app, directly involving them in creating AI solutions). The aim is to prevent AI from being perceived as an exclusive or opaque field; instead, make it a national effort where everyone's voice is valued.

  
  

• Private sector responsibility and incentives: While regulations will require companies to adhere to certain standards (especially under EU law), Luxembourg can motivate its private sector to exceed basic compliance. For instance, a voluntary "AI Trust Mark" certification could be established for companies in Luxembourg that achieve high standards in ethical AI, such as transparency, fairness, and security. This initiative could be developed in partnership with the industry and marketed to consumers and investors as a mark of distinction, encouraging companies to pursue it. Another strategy is to link incentives to ethical conduct: companies that clearly integrate ethics, like having an internal AI ethics board or publishing impact assessments, could receive preferential access to certain grants or public contracts. This approach mirrors the U.S. plan's use of procurement power but focuses on ethical quality.

  
  

• International collaboration for private and civil sectors: Luxembourg could encourage private companies and research institutions to actively participate in European and international AI partnerships. This includes EU’s initiatives (like the European AI Lighthouse projects or joint research programmes) and transatlantic ones (for instance, the EU-US Trade and Technology Council working group on AI, where industry input is often sought). Luxembourg could become a bridge or test site for such collaborations. Furthermore, civil society in Luxembourg can connect with European networks, such as the European Digital Rights group, to ensure that Luxembourg's viewpoint is included in wider discussions about the societal impact of AI.

  
  

• Challenges: Involving a diverse range of stakeholders can delay decision-making and occasionally result in conflicts, such as differing priorities between industry and NGOs. The government must act as an impartial mediator and sometimes make difficult decisions. To ensure civil society can effectively participate—considering AI's technical nature and potential lack of expertise among NGOs—it may be necessary to provide them with resources or training, which the government should consider funding. Another challenge is overcoming scepticism: some in the private sector may initially fear that engaging with civil society exposes them to criticism, while NGOs might distrust corporate intentions. Fostering a culture of constructive dialogue will require effort and leadership.

  
  

• Benefits: Involving multiple stakeholders will result in stronger and more widely accepted AI policies. When everyone participates, the solutions developed are more likely to be balanced, being both business-friendly and protective of citizens. This inclusive approach increases the likelihood of support and implementation, as people feel heard. As for Luxembourg's progress, such collaboration minimises unintended consequences and public resistance, preventing situations where a new AI system is introduced and met with public backlash due to a lack of understanding or input. By the time of implementation, the public is informed and may have even contributed to its design or regulations. Engaging stakeholders also brings forth local knowledge and innovation: civil society can point out niche issues that need attention, while businesses might suggest innovative self-regulation that could be expanded. Ultimately, this strategy will leverage collective intelligence in AI governance—essential given AI's extensive impacts—and strengthen Luxembourg's democratic and consensus-driven values in the digital era.

  
  

6. International collaboration and leadership opportunities

Luxembourg's AI strategy must incorporate a robust international aspect. Despite its small size, Luxembourg can have a significant impact by actively participating as a principled player on the global AI stage. This involves collaborating within the EU, engaging with transatlantic partners such as the U.S., and participating in broader multilateral forums to influence the future of AI governance in accordance with its values and interests.

• Active role in EU AI initiatives: involves fully participating in the EU Commission’s AI strategic programmes to ensure Luxembourg gains the greatest advantage. If the Commission seeks member states to host or test initiatives such as “AI sandboxes” or lead an “AI lighthouse” project in a specific sector, Luxembourg can volunteer, demonstrating its preparedness through previously outlined steps. Additionally, as the EU AI Act is implemented, Luxembourg can lead joint enforcement cooperation—collaborating with regulators from other member states and the future European AI Office to ensure consistent interpretation. By being proactive, Luxembourg can influence how the regulations are understood, such as by contributing to the guidelines for General Purpose AI that the Commission is developing. The goal is not only to follow EU policies but also to shape them in areas like defining “high-risk” or operationalising requirements. This requires aligning Luxembourg’s anticipatory regulation (Guideline 4) with the EU’s horizon scanning—for instance, if the EU establishes expert groups on future AI topics such as AI liability or AI for climate, Luxembourg should ensure representation.

  
  

• Transatlantic and like-minded collaboration: Opportunities exist to build bridges with the U.S. and other AI-leading nations (Canada, UK, Japan, etc.) to exchange best practices and potentially coordinate strategies. The EU-U.S. Trade and Technology Council (TTC) already serves as a platform for discussing AI policy; Luxembourg can contribute to the EU's stance through its government or experts to ensure its voice is included in these discussions. There may be opportunities for more direct collaboration with the U.S. on specific projects: for example, Luxembourg could participate in an “AI for Good” project co-led by U.S. and EU institutions (consider a transatlantic project using AI for climate change mitigation or pandemic response, with Luxembourg providing data or a pilot environment). With the U.S. Action Plan emphasising collaboration with allies, Luxembourg could aim to become a demonstration site for safe and effective AI developed in the U.S. For instance, if a U.S. company has a powerful AI tool that needs adaptation to meet EU standards, Luxembourg could offer to host a pilot of that adaptation, effectively acting as a gateway for U.S. AI into Europe, under appropriate oversight. This could attract investment and facilitate knowledge transfer. Additionally, Luxembourg could strengthen ties with nearby like-minded countries: the Benelux cooperation could be expanded to include AI governance (joint AI testbeds with Belgium and the Netherlands, knowledge exchange, etc.), and collaboration with Nordic countries or others known for tech governance to jointly advocate for specific approaches in the EU (such as sandboxes or ethical frameworks).

  
  

• Global Governance and Standards: Luxembourg could actively engage more in international discussions on AI norms, whether at the United Nations (such as UNESCO’s AI ethics initiative), the OECD, or upcoming Global Partnership on AI (GPAI) events. By offering its unique perspective as a small, multilingual, finance-focused, democratic nation, Luxembourg can help ensure that global AI governance is not solely influenced by superpowers. It can advocate for topics like AI in small societies (ensuring global norms consider the needs of smaller states or languages) and human-centric AI. Additionally, Luxembourg can support the concept of an “AI Ethics Treaty” or back the creation of global agreements on AI safety (some propose a global framework similar to climate accords for AI – Luxembourg can be an early advocate). Regarding technical standards (ISO, IEEE), Luxembourg should encourage participation from local experts in standardisation committees to ensure standards reflect European values and practical realities. Conversely, it should monitor efforts by the U.S. and others regarding standards – the U.S. aims to promote American standards globally – Luxembourg/EU must ensure that international standards remain open and not dominated by any single country’s agenda, and active participation in these bodies is essential to achieve this.

  
  

• Security and defence collaboration: Given the U.S. Plan’s security angle (countering adversaries, military AI), Luxembourg, as a NATO ally, can also consider the defence dimension of AI. While Luxembourg’s military is small, it can focus on niche contributions – for instance, investing in cybersecurity AI that could benefit NATO operations or secure communications, or participating in NATO’s discussions on AI ethics in warfare. Ensuring compatibility and dialogue between EU and NATO (where the U.S. is key) on AI use will be increasingly important, and Luxembourg could serve as a facilitator (especially since it hosts important EU institutions; it could host NATO-EU workshops on AI security). This way, Luxembourg helps bridge any transatlantic policy gap between the U.S. drive for dominance and EU’s cautious approach by finding common ground on preventing malicious use of AI (like joint stances against authoritarian uses of AI for repression or against autonomous weapons proliferation).

  
  

• Challenges:  Luxembourg's international influence is often constrained by its size, necessitating a strategic approach in selecting issues to advocate where it holds credibility or interest. As an EU member, Luxembourg must align with the EU position and cannot independently negotiate AI regulations with the U.S., but it can exert influence on the EU’s internal stance. Balancing national interests, such as attracting investment, with EU solidarity—ensuring not to undermine EU regulations when dealing with foreign partners—demands diplomacy. Additionally, the complexity of various forums makes maintaining consistency challenging; Luxembourg needs a clear internal stance on key principles to ensure a unified voice whether at the EU, UN, or NATO.

  
  

• Opportunities: By engaging in active collaboration, Luxembourg enhances its influence and can shape outcomes that are advantageous for the country. For example, if Luxembourg contributes to forming an EU-U.S. agreement on AI interoperability or standards, its businesses will gain easier access to both markets. Moreover, international collaboration creates opportunities for Luxembourg’s researchers and companies, such as joint ventures, funded projects, and talent exchange, which might not occur if Luxembourg remained low-profile. Being recognized as a leader in responsible AI can also boost Luxembourg’s international reputation, complementing its status as a financial hub with that of an innovation and ethics center. This can lead to additional benefits in diplomacy and trade. Ultimately, by assisting in predicting how the U.S. plan’s implementation might align with EU policies (e.g., if the U.S. begins exporting AI technology with specific values, Luxembourg, through the EU, can respond with its own frameworks), Luxembourg ensures it is not surprised by global developments but is actively influencing them—an essential aspect of a proactive strategy.

  
  

The strategy merges the agility and boldness typical of the U.S. approach with the EU's precautionary and human-focused ethos. This enables Luxembourg to establish itself as a European and global leader in responsible AI, enhance its economic influence by attracting AI innovation, and protect its society from AI-related risks through strong governance. Importantly, this draft strategy capitalises on Luxembourg’s distinctive context—its advanced digital infrastructure, financial expertise, multilingual population, and collaborative spirit—to not only implement existing EU directives but to exceed them, ensuring Luxembourg stays at the forefront of both AI development and AI governance.

Sources:

• White House, “Winning the AI Race: America’s AI Action Plan,” July 2025.

• Skadden Arps (Stuart D. Levi et al.), “White House Releases AI Action Plan: Key Takeaways,” July 30, 2025.

• European Commission, “AI Continent Action Plan,” April 2025 – five pillars for EU AI strategy.

• European Parliament, “EU AI Act: first regulation on artificial intelligence,” updated Feb 2025 – summary of the AI Act’s risk framework and requirements.

• Kennedys Law, “Key insights into AI regulations in the EU and the US,” Jan 21, 2025 – comparison of EU AI Act and emerging US approach.

• White House OSTP, “Blueprint for an AI Bill of Rights,” Oct 2022 – (contextual reference for prior US policy focus on rights).

• Official Journal of the EU, General Data Protection Regulation (GDPR), 2016 – Article 22 on automated decisions (providing rights against solely automated profiling).

• Additional EU strategic documents: “Artificial Intelligence for Europe” (European Commission, 2018); Coordinated Plan on AI (2018, updated 2021); “White Paper on AI: A European approach to excellence and trust,” 2020; AI Innovation Package, 2024. These laid the groundwork for current EU policies and are referenced for context.