Strategy
People
The “P” for People, the first P in our sustainable development strategy, focuses on two priorities: protecting our employees and retaining our talents. At LISI, we are deeply committed to workplace safety and employee well-being. We firmly believe that happy and fulfilled employees are the best source of sustainable innovation. This year marks a significant acceleration in our transformation with:
- A skills development program aimed at driving our talent toward excellence.
- An approach to anticipating the jobs of tomorrow, shaped by the challenges of artificial intelligence.
- A strong policy promoting diversity and inclusion, which are true drivers of collective performance.
- The implementation of a dashboard to track and improve our ability to attract and retain top talent.
This comprehensive approach to managing our talent represents a major strategic asset and the foundation for our future growth in a constantly evolving world.
# Challenges & Objectives |
2023 | 2024 | 2025 |
|---|---|---|---|
AXIS 1 : PROTECT OUR EMPLOYEES |
6.7 | 5.7 | 5.8 |
AXIS 2 : RETAIN OUR TALENTS |
28.1 | 28.4 | 28.0 |
AXIS 2 : RETAIN OUR TALENTS |
8.1 | 6.8 | 18.1 |
* SDG: Sustainable development goals / GRI : Global Reporting Initiative.
Beyond these indicators, our transformation is accelerating. Anne-Delphine Beaulieu and Pierre-Emmanuel Kohler explain how Artificial Intelligence is emerging as a major performance driver at LISI, in service of our talent and our operational excellence.
ARTIFICIAL INTELLIGENCE
A NEW FRONTIER FOR LISI
JOINT INTERVIEW
Anne-Delphine Beaulieu
Chief Transformation & AI
Pierre-Emmanuel Kohler
Chief IT Officer
Is AI the next stage in the Group’s digital transformation?
Anne-Delphine Beaulieu : At LISI, artificial intelligence is part of a long-term digital transformation journey while also representing a major technological shift. However, this new industrial chapter would not have been possible without the foundations we have built. In recent years, investments in the digitalization of industrial processes, the structuring of available data, and system interoperability have created the conditions required for the effective deployment of AI, enabling it today to fully realize its potential. AI now makes it possible to leverage industrial data at scale, automate complex decision-making loops, and reach a new level of operational maturity. Rather than a “layer” added on top of existing systems, AI is a true accelerator of our digital excellence.
Pierre-Emmanuel Kohler : AI represents a paradigm shift in our industrial approach. We are progressively moving from controlled systems to systems capable of anticipating and making decisions. Where digitalization enhanced traceability and operational control, AI introduces prediction, simulation, and autonomy. It not only improves operational performance—by anticipating deviations and optimizing real-time decision-making—but also reshapes our design, production, and maintenance processes.
AI is not a mere technological evolution; it opens a new industrial chapter.
What is your vision of AI, and what transformations will it bring to the Group’s functions and roles?
Anne-Delphine Beaulieu : Our conviction is clear: AI amplifies skills, it does not replace them. Machines handle repetition, large-scale analysis, and continuous optimization; humans provide judgment, decision-making, 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 value-added 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).
Pierre-Emmanuel Kohler : 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.
AI 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 |
What is the 2026 deployment timeline?
Anne-Delphine Beaulieu : 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.
Pierre-Emmanuel Kohler : 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.