Vanherpe, JozefienJozefienVanherpeDe Bethune Louise2026-05-182026-05-182026-05https://imec-publications.be/handle/20.500.12860/59422This executive summary presents a legal de‑risking analysis of generative AI within the VLAM project, situated in the European regulatory framework. While the EU context provides legal certainty and trust, it also imposes significant requirements related to intellectual property, data protection and the AI Act. The analysis adopts a worst‑case scenario approach to systematically identify risks across the AI lifecycle, from training (input) to deployment and generated content (output), with the aim of enabling informed and responsible innovation rather than discouraging it. Key risks include potential copyright infringement, GDPR non‑compliance during training, liability for AI‑generated output, and restrictions linked to third‑party models. The study demonstrates that these risks can be managed through governance, contractual safeguards and technical measures. It further shows how ongoing and future research projects translate legal challenges into practical solutions, embedding compliance into AI systems by design. Overall, the analysis positions legal risk not as a barrier, but as a driver for building robust, compliant and future‑proof AI innovation in a European context.enReportGenerative AILegal complianceIntellectual propertyCopyrightGDPRAI Act