Is Artificial Intelligence Really Transforming French Companies in the Same Way?

In France, only 6% of companies used artificial intelligence technologies between 2020 and 2022. However, this adoption remains uneven and reveals marked sectoral and technological dynamics. Certain technologies, such as machine learning data analysis, information extraction from texts, and automation and decision-support tools, stand out for their broader use. These three technologies form the core of the AI system, as they are capable of supporting a variety of functions within companies.

The sectors most advanced in AI adoption are IT services and scientific and technical activities. These fields primarily use AI to optimize their organizational processes and research and development activities. Conversely, sectors such as construction or certain traditional services lag behind, due to a lack of needs or suitable capabilities.

Data analysis shows that companies do not use AI uniformly. Large companies, often younger and better equipped with digital infrastructure, are the most active. However, size is not the only determining factor: language processing technologies, such as text extraction or voice recognition, are accessible even to small businesses. On the other hand, tools requiring complex data or advanced automation, such as image recognition or autonomous systems, remain reserved for companies with significant resources.

AI is not a single technology, but a set of tools with varied applications. Some, like data analysis or automation, have a broad scope and serve as the foundation for other innovations. Others, such as natural language generation, are more specialized and target specific functions, such as commerce or customer service. This diversity explains why some companies focus on one or two technologies, depending on their specific needs.

The use of AI also depends on companies’ digital capabilities. Businesses that have already adopted cloud solutions or integrated management systems are better prepared to integrate AI. These infrastructures enable the collection, storage, and analysis of the data needed for algorithms to function. Without these foundations, even the most accessible technologies struggle to demonstrate their usefulness.

The results of this study highlight that AI is not being deployed uniformly. Its impact varies by sector, company size, and targeted functions. Rather than a uniform revolution, its adoption resembles a gradual evolution, shaped by the needs and resources of each organization. Companies that invest in foundational technologies, such as data analysis or automation, position themselves to gain broader advantages. Others often have to settle for more limited applications, tailored to specific tasks. This reality calls for rethinking diffusion strategies, taking into account the specificities of each technology and sector.

References

Origin of the Study

DOI: https://doi.org/10.1007/s40821-026-00347-9

Title: Decoding AI: an early look at how French firms use AI

Journal: Eurasian Business Review

Publisher: Springer Science and Business Media LLC

Authors: Flavio Calvino; Luca Fontanelli