Related items

The success of the Cloud and AI Development Act (CADA) will depend on whether its sovereignty framework strengthens Europe’s resilience and competitiveness without restricting access to the technologies, providers and operating models needed to support the bloc’s digital transformation. As currently envisaged, several elements of CADA introduce origin-based restrictions that are not necessarily linked to genuine sovereignty, security or resilience risks. These measures could reduce competition, increase costs and slow cloud and AI adoption – ultimately working against CADA’s underlying objectives.

A sovereignty framework built on objective, risk-based criteria will better support Europe’s competitiveness, resilience and digital transformation than one based on origin, ownership or nationality.

The revised Merger Guidelines1 (‘Guidelines’) should ensure that the EU merger control framework supports competitiveness, innovation and investment while preserving legal certainty, predictability and effective competition. The Guidelines should remain firmly anchored in the significant impediment of effective competition (SIEC) test, apply resilience and scale considerations in a headquarters-neutral and effects-based manner, and provide clearer analytical and evidentiary standards for resilience assessments and the new theories of harm.

The Guidelines should recognise the benefits of scale where these deliver demonstrable advantages for EU consumers, apply the innovation shield consistently across all acquirers, maintain appropriate safe harbours and ensure a balanced and symmetrical assessment of harms and benefits. The Guidelines should also strengthen predictability across overlapping transaction review regimes and provide greater certainty for both EU and non-EU investors. Together, these refinements would help ensure that merger control contributes to competitiveness, innovation and economic growth while maintaining a transparent and proportionate enforcement framework.

Meta’s open-source Canopy Height Maps helped the European Commission’s Joint Research Centre improve its 2020 Global Forest Cover map, demonstrating how artificial intelligence can strengthen Europe’s ability to monitor forests and advance climate and biodiversity goals. Developed with the World Resources Institute, the maps use Meta’s DINO self-supervised computer vision model to estimate tree height from satellite imagery. This helped researchers apply the five-metre threshold used in many international forest definitions and better distinguish forests from other tree-covered land, including agricultural tree crops. The resulting product, available through the EU Forest Observatory, provides one of the most comprehensive open views of global forest cover. Read more on Invested in Europe.