Artificial Intelligence
Drive innovation in AI for fundamental research while promoting open, collaborative, safe, and compliant use and development of technology
AI and CERN
Since the first use of neural networks in the late 1980’s and early 1990’s (1st International Workshop on Software Engineering, Artificial Intelligence and Expert Systems in High-energy and Nuclear Physics, CERN 1990), Artificial Intelligence and Machine Learning have become essential enablers for CERN and its physics experiments, allowing the community to cope with unprecedented data volumes, complexity, and performance requirements. From real-time event selection and trigger systems to offline reconstruction, simulation, and detector operations, ML techniques are now embedded across the full data lifecycle, significantly improving efficiency, precision, and scalability.
Beyond performance gains, AI is also reshaping how experiments are designed and operated, enabling more adaptive systems, better use of computing resources, and faster scientific insight, thereby strengthening CERN’s capacity to fully exploit current and future accelerator and detector programmes.
CERN’s strategic approach to AI identifies it as a core organisational capability with relevance extending to the full lifetime of the HL-LHC and the preparation of future facilities such as the FCC. We consider AI technology within the wider scientific and organisational CERN strategy, so that CERN can develop and use AI to safeguard and extend its scientific leadership, ensure sustainable and reliable operations, and remain an attractive and effective organisation.
AI for Physics, Accelerators, Operations and Positive Impact on Society
CERN’s strategic objectives for AI are aligned with the main priorities the Organization is defining for the next decade of operations:
Strengthen scientific discovery through AI-enabled analysis, data processing, simulation, and design, enabling both measurable gains in physics reach, sensitivity, and time-to-result, and the exploration of new discovery regimes and scientific questions, support theoretical work by enabling new forms of model exploration, interpretation, and hypothesis testing.
Increase operational reliability, efficiency, and sustainability by embedding AI in accelerator, detector, and infrastructure operations as well as administrative processes, thus reducing unplanned downtime, energy consumption, and manual intervention.
Build and retain critical AI-related skills across CERN, ensuring ubiquitous access for all personnel so that they can effectively and responsibly use AI in scientific, technical, and administrative roles. This requires proactive talent acquisition and retention, and strengthening CERN’s role as an environment that attracts, develops, and inspires future generations of scientists, engineers, and innovators aligned with its mission.
Position CERN as a reliable and effective partner in the European AI-for-science landscape, enabling access to shared infrastructures, funding, and expertise while contributing to societal and industrial impact. This includes contributing knowledge, reference use cases, and expertise that support wider scientific, societal, and industrial benefit, consistent with CERN’s role and mandate.
More Information, Initiatives and Projects
AI Strategy
AI Implementation Plan
AI Programme Committee
