41 2025 Integrated Report - LISI PERFORMANCE operational performance — by anticipating deviations and optimizing real-time decision-making — but also reshapes our design, production, and maintenance processes. What is your vision of AI, and what transformations will it bring to the Group’s functions and roles? A-D B - Our conviction is clear: AI amplifies skills, it does not replace them. Machines handle repetition, large-scale analysis, and continuous optimization; humans provide judgment, decisionmaking, relationships, and innovation. This human– machine collaboration is reshaping roles across the organization: operators, technicians, engineers, and planners are evolving toward greater analytical responsibility and higher added-value activities. At the same time, new roles are emerging in areas such as data, predictive maintenance, and the ethical governance of AI. This transformation is supported by a structured training policy and will be driven by our corporate university, LKI (LISI Knowledge Institute). P-E K - Operationally, AI strengthens the robustness, performance, and sustainability of operations. It is reshaping certain functions across the value chain while also creating new professional opportunities. The success of this transformation depends on specific conditions: providing a clear direction, investing in skills, co-developing solutions with the field, and enabling workforce mobility. Our responsibility is to manage an inclusive and secure transition in support of collective performance. What is the 2026 deployment timeline? A-D B - The year 2025 was foundational, marked by rapid operational adoption, the establishment of AI governance, and the deployment of initial priority use cases. The next phases will focus on scaling use cases, broadening training initiatives, and embedding AI into the Group’s core processes. IA AND CYBERSECURITY: ENHANCED VIGILANCE The rise of artificial intelligence is profoundly reshaping the cyber risk landscape for industrial companies. The increase in data volumes processed, the growing interconnection of systems, and the use of generative AI models are heightening challenges related to data confidentiality, data integrity, and technological dependence. These risks are addressed in a structured manner through dedicated AI governance that integrates cybersecurity, ethics, and infrastructure sovereignty considerations. Ongoing work is also focused on data hosting strategies and the autonomy of deployed solutions. LISI adopts an approach that combines clear usage frameworks, platform security, and user awareness of cybersecurity threats (including phishing, malware, and reinforced financial control processes). LISI’s AI Charter, drafted in 2024, promotes the prudent and responsible use of these tools. “AI can only create sustainable value if it is built on secure and controlled foundations,” notes Pierre-Emmanuel Kohler. The transformation in numbers Before 2025 2025 Impact Theoretical knowledge + 200 people trained Cross-functional skills development Limited access to AI Deployment across 4 countries Successful operational rollout No AI agent 40 AI agents created Business process automation underway No framework Structured governance Governance and prioritization Passive monitoring Active monitoring Anticipation and agility P-E K - By 2026, the key priority will be strengthening our technological sovereignty and expanding the deployment of AI agents, particularly in predictive maintenance. This phased approach enables us to balance performance, security, and control over our technology choices. AI is not a mere technological evolution; it opens a new industrial chapter. Pierre-Emmanuel Kohler VP Information and Technology LISI.
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