Artificial intelligence (AI) is transforming scientific research, with deep learning methods playing a central role in data analysis, simulations, and signal detection across particle, nuclear, and astroparticle physics. Within the JENA communities-ECFA, NuPECC, and APPEC-and as part of the EuCAIF initiative, AI integration is advancing steadily. However, broader adoption remains constrained by challenges such as limited computational resources, a lack of expertise, and difficulties in transitioning from research and development (R&D) to production. This white paper provides a strategic roadmap, informed by a community survey, to address these barriers. It outlines critical infrastructure requirements, prioritizes training initiatives, and proposes funding strategies to scale AI capabilities across fundamental physics over the next five years.

翻译：人工智能（AI）正在变革科学研究，其中深度学习方法在粒子物理、核物理与天体粒子物理领域的数据分析、模拟与信号检测中发挥着核心作用。在JENA联盟（包括ECFA、NuPECC与APPEC）内部以及作为EuCAIF倡议的一部分，AI技术的整合正在稳步推进。然而，更广泛的采用仍受限于计算资源不足、专业人才缺乏以及从研发到生产环境转换困难等挑战。本白皮书基于一项社区调查，提出了应对这些障碍的战略路线图。文中明确了关键的基础设施需求，优先规划了培训计划，并为未来五年内在基础物理学领域规模化扩展AI能力提出了资金支持策略。