AI and skills-based management at an international level: feedback and insights

Technological acculturation, AI ethics and compliance, skills-based management: these three challenges take on a new dimension at an international level. How can organisations successfully drive these transformations without limiting local initiatives?

This was the central question of our Learning & Development Breakfast Session held on 24 March 2026. It brought together L&D Directors from major organisations alongside Cegos experts: Grégory Gallic, L&D Project Director, and Jonathan Mohadeb Lysobycki, Head of International Business.

The session sparked particularly rich discussions. The depth of insights shared and the enthusiasm of participants highlighted the importance of these topics for organisations. Here is a summary of the key takeaways.

AI acculturation at an international level

AI is impacting all international organisations. However, levels of technological maturity, infrastructure and usage vary significantly across countries. How can organisations ensure upskilling while taking local realities into account?

Defining a global framework while enabling local flexibility

All L&D Directors present at the session began their AI deployment with a common core driven by headquarters. They established a global framework to reduce disparities in maturity across employees and countries.

At this initial stage, remote learning formats enable rapid and large-scale dissemination of foundational knowledge. However, some organisations choose face-to-face formats to create stronger impact and highlight the human skills required to work effectively with AI. Senior leadership sponsors the initiative to reinforce its importance and drive engagement.

Following the acculturation phase, a second stage focuses on encouraging practical use. This involves appointing ambassadors to share best practices, with segmentation by country, role and/or function.

This phase requires tailored support anchored in real work situations, with a strong focus on the value AI brings to each individual.

Successfully embedding AI into daily operations

While the initial awareness phase is often successful, many L&D Directors report that the adoption phase is more challenging.

Transparency remains the primary success factor. Leadership must address employees’ concerns regarding the impact of AI and the evolution of their roles. This helps reduce anxiety.

Simplicity also drives sustainable adoption. Tools must be presented in a clear and accessible way. Very short tutorials focused on first use or simple actions help prevent discouragement. Creating a repository of best practices enables organisations to centralise and share successes globally.

To ensure widespread adoption, some forward-thinking organisations have integrated AI usage into annual bonus criteria. This significantly accelerates adoption.

Finally, organisations rely on managers and peers to build trust. Managers encourage daily use, while more confident employees act as ambassadors for their colleagues. Some companies deploy AI using only internal and local resources, through “train the trainer” approaches.

AI compliance in the face of diverse regulatory constraints

AI deployment takes place within highly diverse regulatory and cultural environments. How can organisations establish global governance without hindering local innovation, while respecting regional specificities?

Balancing global standards and local flexibility

Should organisations apply the strictest rule everywhere, or adapt to local flexibility? This decision impacts both legal security and the organisation’s ability to innovate in local markets.

Access policies vary widely between organisations. Some allow the use of public tools such as Gemini, Copilot or Claude. Others strictly prohibit them and develop internal solutions, considered more secure.

Some international organisations have chosen not to create a dedicated AI usage policy. Their current priority is addressing data leaks and cyber threats, perceived as more immediate risks. By embedding AI within these broader topics, they strengthen risk awareness across the workforce and reduce overall digital vulnerability.

Promoting transparency to foster accountability

It is unrealistic to expect responsible use without first raising awareness of algorithmic bias and potential errors. This transparency leads to critical use rather than blind trust in AI outputs.

One challenge is staying aligned with local regulations. For example, organisations can appoint regional representatives responsible for monitoring regulatory developments and reporting key changes. This approach enables rapid adaptation without overhauling the entire global governance model.

It is also essential to define and communicate prohibited or strictly regulated use cases to avoid major ethical issues. Recruitment is a key example. As language models may reproduce biases, human oversight must remain systematic to ensure fairness.

Encouraging responsible and sustainable use

The environmental impact of AI is becoming a key decision factor in regions where natural resources are under pressure. Organisations must communicate on AI’s environmental footprint and raise awareness of digital sobriety. This ethical stance strongly resonates with employees, who are increasingly concerned about sustainability. It may translate into simple guidelines such as limiting unnecessary queries or avoiding image generation.

The emergence of agentic AI, capable of acting autonomously, further reinforces the need for safeguards. Today’s AI deployments provide a foundation for future automation.

The international "skills-based organisation"

AI is reshaping job roles. This is driving organisations towards skills-based management. At an international level, implementation can vary significantly depending on cultural contexts. How can organisations place skills at the centre of L&D processes to enhance both global and local performance?

An ideal tested by reality

The skills-based organisation is a popular concept, but it faces practical challenges. In reality, it does not replace role-based structures but complements them. L&D Directors observe that the skills-based model works well for managing horizontal mobility. However, roles remain essential for strategic positions and vertical progression.

One major challenge is scalability. The success of the model depends on skills mapping, yet in a rapidly changing world, these maps become outdated almost as soon as they are completed. As a result, organisations tend to test the approach on limited scopes, such as transversal skills or high-demand roles.

Accurately identifying skills gaps

For adoption to succeed, the approach must address concrete operational challenges. This is why many organisations favour bottom-up approaches.

Some identify skills gaps by analysing customer complaints or production incidents. This directly links skills development to service quality and customer satisfaction.

Others conduct annual strategic reviews with business experts. This connection between operations and strategy helps anticipate changes across job families. These insights are sometimes combined with workforce demographics to adjust development plans before critical gaps emerge.

The use of skills matrices in production environments illustrates this approach effectively. These visual tools map who can do what within a workshop. At a glance, managers can identify critical skills held by a single individual. If that person is absent or leaves, operations may stop, making training a priority.

Empowering employees to drive their own development

The skills-based model provides employees with clear visibility of the skills required for each role. They can then build their own learning paths based on their career aspirations, strengthening individual engagement.

To support implementation, organisations may rely on employee self-assessment. This must take cultural differences into account. Some environments encourage individuals to present their skills confidently, which may introduce bias, while others favour more cautious approaches, making managerial validation essential.

Finally, linking these initiatives to a job observatory facilitates dialogue with social partners on long-term employability. Employee representatives and management can align on development programmes before skills shortages become critical.

This session highlighted that there is no single model for international learning. Each organisation must explore its own path. We are entering an era of experimentation, where agility and the sharing of experiences become our most valuable guides.

Which topics would you like us to explore in a future international L&D session?

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