AI amplifies the digital talent shortage and affects all professions. Faced with this challenge, companies must focus on their existing employees rather than on recruitment alone.
L’artificial intelligence (AI) did not create the global digital skills shortage, certainly, but it highlighted it. Demand for specialists in AI, cybersecurity and cloud engineering continues to outstrip available supply. France Stratégie and Dares anticipate strong growth in digital professions in the years to come, the sector will be among those where recruitment tensions are the most marked. For many organizations, relying on external recruitment to fill this gap becomes both costly and structurally limiting.
But the challenge goes well beyond specialized positions. As AI becomes integrated into almost every organizational function, the skills gap is spreading into professions that would not have traditionally been considered “digital.” From communication to finance to operations, the requirement to master AI tools and be able to exploit data is quickly spreading across all business functions. Mastery of digital tools is becoming a basic requirement, and no longer just the prerogative of specialists.
In France, this development is already perceptible. Initiatives such as French Tech regional campuses, second chance schools, technical bootcamps and continuing education programs funded by France Travail demonstrate a growing national effort to strengthen the talent pool. Recent developments in the Personal Training Account (CPF), with new courses dedicated to digital and AI, as well as the development of apprenticeships in these sectors, offer more flexibility to employers.
However, national measures will not be enough to fill the deficit. Digital resilience is ultimately built within companies themselves, through the way skills are developed, shared and put into practice. Investment in technology and investment in employee training are inseparable: without the right skills, even the most advanced AI systems struggle to produce operational value.
Technology depends on human capabilities
This observation influences the way companies approach the technologies they adopt. Open source is a telling example. Beyond the operational advantages linked to flexibility and interoperability, open ecosystems actively promote skills development. Working in open source environments promotes collaborative problem solving, community development practices, and the sharing of technical skills, reducing the risk of expertise becoming confined to a single vendor’s tools or roadmap.
This dynamic becomes even more important as agentic AI enters businesses. AI-powered tools are already accelerating productivity and lowering the barriers to entry for technical work, enabling collaborators to build, test, and iterate faster than traditional development cycles allowed.
But it also raises the demands on what companies expect from their teams. Agentic AI can generate results and quickly identify lessons learned. But it cannot guarantee that these results are accurate, contextually relevant or rooted in quality data. Without the human skills to question and question the results produced by AI, in other words to add intelligence, companies risk getting their employees used to relying on AI, without understanding its limitations.
Employees who master data management (the way information is structured, governed, retrieved and secured) will be the ones who are able to work effectively with AI. Businesses still need people who can validate results, identify weak or misleading data, and exercise judgment where AI falls short. Otherwise, an over-reliance on AI tools undermines the very learning and critical thinking capabilities that businesses seek to develop.
Competence: the first strategic asset
Ultimately, the organizations that succeed in the next decade will be those that view competence as a core strategic asset.
Developing internal skills, strengthening collaboration and investing in digital savvy will not be enough to eliminate global talent shortages, but it will determine which companies are able to continue operating and adapt despite them. This increasingly involves being specific not just about how employees learn, but what they learn, while ensuring that technology choices help transfer skills, infrastructure-wide.
In France, developments in the CPF and the national strategy around AI are a sign of a desire to develop more responsive training models. However, public policy alone is not enough.
Strengthening internal capacities, in the public and private sectors, will be essential to France’s ambitions for technological sovereignty, economic growth and national resilience. This work begins with the talent already in the room.
