AI Futures for Europe: Four Strategic Scenarios and Opportunities (Part 4)

This is Part 4 of EuroComply's series on the European Commission's futures study on AI and the EU research and innovation ecosystem. Parts 1 through 3 examined the study's baseline findings, infrastructure and talent dimensions, and sector-specific investment trends. Part 4 turns to the study's scenario analysis: four distinct trajectories for AI in Europe through 2035, the policy levers that determine which path is taken, and what businesses should do to position themselves across the full range of possible outcomes.

Why Scenario Planning Matters for AI Compliance

The EU AI Act establishes a regulatory framework whose practical meaning depends substantially on how it is enforced, how it evolves through delegated acts and harmonised standards, and how the competitive landscape for AI develops globally. A compliance strategy calibrated only to current requirements risks being overtaken by events — either by regulatory tightening that makes current preparations insufficient, or by competitive dynamics that make the cost of over-compliance prohibitive.

Scenario planning is the appropriate tool for navigating this uncertainty. The Commission's futures study identifies four scenarios, each representing a coherent and internally consistent account of how key drivers could develop through 2035. Understanding the scenarios, their drivers, and their probabilities helps compliance teams and business strategists allocate preparedness investment efficiently.

Scenario 1: EU as Global AI Leader

In this scenario, European AI achieves genuine global competitiveness by 2035 through a combination of infrastructure investment, coordinated data ecosystems, and the emergence of a trust premium for EU-certified AI in regulated global markets. The EuroHPC AI factory network reaches critical scale, European foundation models achieve performance parity with US counterparts in key vertical domains, and the EU AI Act's conformity assessment regime becomes the de facto global standard for AI in regulated industries.

Key drivers for this scenario include: rapid deployment of compute infrastructure under the AI Strategy 2026–2030, successful mobilisation of the €20 billion annual investment target, breakthrough adoption of European common data spaces in health and mobility, and a geopolitical environment in which AI trustworthiness becomes a decisive procurement criterion for public sector and regulated industry buyers globally.

The probability assigned by the futures study is 15 to 20 percent — achievable but requiring substantial policy execution discipline that has historically been difficult to sustain across the full EU legislative cycle.

For businesses, this scenario represents the highest-reward outcome for early compliance investment. AI Act Article 9 risk management documentation and Article 43 conformity assessment would become commercially valuable differentiators, and the cost of compliance would be amortised across larger addressable markets.

Scenario 2: Fragmented National AI

In this scenario, member states diverge in their interpretation and enforcement of the AI Act, creating a patchwork of de facto national requirements that fragments the single market for AI. Regulatory arbitrage flourishes — companies route their AI development through member states with lighter enforcement postures, and mutual recognition of conformity assessments breaks down in practice even while remaining intact on paper.

Key drivers include: failure to adequately resource national market surveillance authorities, divergent transposition of AI Act provisions that permit member-state discretion, and political pressure in larger member states to protect national AI champions from single-market enforcement actions. The competitive pressure of scenarios 3 and 4 accelerates this fragmentation as member states respond with unilateral industrial policy measures.

The probability is assessed at 25 to 30 percent — a plausible outcome given the structural incentives for regulatory arbitrage and the uneven administrative capacity across EU member states.

For businesses operating cross-border, this scenario is operationally the most complex. Compliance programmes must be designed to accommodate national divergence, meaning that reliance on a single EU-level conformity assessment may not be sufficient for deployment across all member states. The practical advice is to monitor enforcement posture at the national market surveillance authority level, not only at the EU AI Office level.

Scenario 3: US/China Platform Dominance

In this scenario, European enterprises become dependent on non-European AI foundation models, cloud infrastructure, and platform ecosystems for the large majority of their AI capabilities. European AI development activity is squeezed into a narrow band of specialised applications where regulatory or cultural proximity creates defensible niches, but the core value creation in AI — model development, infrastructure, and platform layers — migrates out of Europe.

Key drivers include: continued failure to close the compute gap, inadequate early-stage venture capital for AI foundation model companies, talent outflows that are not offset by inflow policies, and corporate procurement decisions by European enterprises that prioritise capability over provenance. AI Act compliance costs play a role here: if compliance costs for European AI providers are materially higher than for non-EU providers selling into Europe under equivalence arrangements, competitive disadvantage compounds.

The futures study assigns this the highest probability among the four scenarios at 35 to 40 percent, reflecting the current trajectory of investment flows and the structural depth of US and Chinese platform advantages.

For businesses, this scenario does not necessarily imply poor outcomes — European enterprises can build competitive applications on non-European AI foundations — but it does mean that Article 26 of the AI Act, which addresses obligations for deployers who are not the original providers, becomes the central compliance reference point rather than Article 9 or Article 43 which govern providers.

Scenario 4: Regulated-but-Competitive Europe

This is the scenario the futures study identifies as the most strategically coherent and the most consistent with current policy trajectory, at a probability of 25 to 30 percent. In this scenario, Europe does not achieve global leadership in frontier AI but builds a distinctive competitive position in trustworthy, regulated-domain AI — healthcare, finance, public administration, critical infrastructure — where the EU AI Act's compliance infrastructure creates a credibility moat that non-EU providers cannot easily replicate.

Key drivers are: consistent enforcement of the AI Act creating genuine differentiation for compliant AI systems; successful deployment of regulatory sandboxes under Article 57 enabling rapid iteration within defined risk parameters; and strong demand from regulated-industry buyers globally for AI systems that carry EU conformity assessment credentials.

Article 70 of the AI Act, which governs confidentiality in enforcement proceedings, is relevant to this scenario because it shapes how enforcement information flows between authorities and the market. Effective use of Article 70 protections allows market surveillance authorities to pursue enforcement without creating information asymmetries that could chill legitimate innovation — a balance that is essential for the regulated-but-competitive scenario to function.

Policy Levers Across Scenarios

Several policy mechanisms appear in the futures study as cross-scenario levers that shift probabilities in favour of the more desirable outcomes.

Article 57 sandboxes are the most frequently cited. By providing a structured, time-limited environment for AI testing under regulatory supervision, sandboxes reduce the innovation cost of compliance and create feedback loops between regulators and developers that improve the quality of both the AI systems and the regulatory guidance. Expanding sandbox capacity and reducing access barriers for SMEs shifts probability mass from scenarios 2 and 3 toward scenarios 1 and 4.

Harmonised standard development under Article 40 of the AI Act is the second major lever. Delays in developing harmonised standards create legal uncertainty that disproportionately affects companies without in-house legal capacity to interpret ambiguous requirements. The faster CEN/CENELEC and ETSI publish standards that give operational content to the AI Act's requirements, the more predictable the compliance environment becomes.

Practical Steps for Businesses to Hedge Across Scenarios

A compliance and strategy programme that performs reasonably well across all four scenarios should be built on five principles.

First, invest in modular compliance infrastructure. Documentation, risk management systems, and technical files that are built to AI Act standards are valuable in scenarios 1 and 4 and are not wasted in scenarios 2 and 3 — they simply become table stakes rather than differentiators.

Second, diversify AI supplier relationships. Dependence on a single foundation model provider creates scenario 3 exposure; maintaining technical capability to migrate between providers preserves optionality.

Third, engage actively with sandbox programmes. Early participation in Article 57 sandboxes builds relationships with national competent authorities and provides intelligence on enforcement interpretation that is commercially valuable regardless of which scenario materialises.

Fourth, monitor harmonised standard development. Track CEN/CENELEC JTC 21 progress on AI Act standards and engage in public consultation processes. Early knowledge of draft standard requirements allows compliance infrastructure to be built to final rather than transitional specifications.

Fifth, track the Digital Omnibus file. The proposed simplifications to Articles 6 and 43 of the AI Act could materially alter the compliance cost structure, particularly for SMEs. A compliance programme that anticipates both the current text and the amended text reduces the cost of adaptation when the legislative outcome is known.

Frequently Asked Questions

Which of the four scenarios is most likely to materialise by 2035? The futures study assigns the highest probability to Scenario 3 (US/China platform dominance) at 35 to 40 percent, reflecting current investment trajectories. However, probabilities are sensitive to policy decisions in the 2026 to 2028 window, particularly around compute infrastructure deployment and sandbox expansion. Scenario 4 (regulated-but-competitive) is the second most likely outcome and represents a strategically coherent target for EU policy.

How does Article 57 sandbox participation reduce compliance risk? Sandbox participation establishes a formal relationship with the competent authority during development, reducing the risk of regulatory surprise at market launch. The Article 57 framework also provides a documented record of pre-market regulatory engagement that can be referenced in the technical file and conformity assessment declaration, demonstrating good faith compliance effort.

What does Article 70 confidentiality protection mean for enforcement practice? Article 70 prevents market surveillance authorities from disclosing confidential business information obtained during enforcement proceedings. For businesses subject to investigation, this provides protection against competitors accessing technical file information through regulatory disclosure. It also enables authorities to conduct investigations without triggering market-distorting information releases — a design feature that supports the credibility-based competitive model in Scenario 4.

Sources

• European Commission, Futures of Artificial Intelligence: Implications for Europe's R&I Ecosystem, Study Report, 2024
• Regulation (EU) 2024/1689 (EU AI Act), Articles 9, 26, 40, 43, 57, 62, 70, Annex III
• European Commission, Artificial Intelligence Strategy 2026–2030, COM(2025) 400 final (forthcoming reference)
• OECD, OECD AI Policy Observatory: AI Regulation Tracker, 2025
• CEN/CENELEC JTC 21, Standardisation Programme for AI Act Implementation, 2024
• European Commission, Digital Decade Compass Report 2024, SWD(2024)200 final