The strategic adoption of generative AI in the French Tech: a major lever for innovation

In 2024, generative AI (GenAI) is establishing itself as a key driver of transformation within the French technology ecosystem, particularly among the startups and scale-ups of the Next40 and French Tech 120. Far from being a mere technological advance, it is redefining internal processes and extending its impact to user experience and product innovation. According to the study conducted by Mozza, although 96% of companies consider generative AI to be strategic, only 37% have integrated it into their operations. This gap highlights an untapped potential and organizational barriers yet to be overcome.

 

A driver of innovation within the French Tech ecosystem

The adoption of generative AI stands out for its ambition: more than just an optimization of operations, it represents a means of differentiation for startups. Unlike large companies that often leverage AI for efficiency purposes, French scale-ups integrate this technology at the heart of their value proposition. One of the key findings of the study reveals that 60% of companies use generative AI to personalize the customer experience, a key indicator of its role in transforming business models.

However, challenges remain. The majority of SMEs, in particular, lack the resources to experiment and implement solutions at scale. This reality hinders the emergence of widespread adoption across the entrepreneurial fabric.

 

Use cases and operational impact

The study identifies several areas of application for generative AI, ranging from the automation of business processes to the creation of new products and services. Here are some concrete examples of implementation:

  1. Improving the customer experience (PayFit)
  • Approach: Progressive development of an AI pipeline for customer support.
  • Results: Thanks to a conversational assistant and an intelligent ticket routing system, PayFit has achieved a ticket deflection rate of 20%, with adoption by 40% of users. This has enabled a notable increase in support agent productivity (+23%).
  1. Optimized product navigation (Ankorstore)
  • Feature: Standardization of product descriptions and personalization of search filters.
  • Impact: A 28% increase in cart additions thanks to better item categorization. The strategic use of models such as GPT-3.5 and GPT-4 has reduced operating costs while maximizing the relevance of the results.
  1. Transforming legal services (Doctrine)
  • Innovation: Chatbot enabling conversational search in natural language.
  • Advantage: Drastic reduction in research time for legal professionals, with weekly adoption by 15% of platform users.
  1. Simplifying financial management (Agicap)
  • Solution: Conversational AI assistant for the analysis and export of personalized data.
  • Performance: AI response satisfaction rate between 70 and 90%, consolidating Agicap’s position in the market.
  1. Creation of training content (360Learning)
  • Initiative: Automatic generation of training modules from simple prompts.
  • Results: More than 16% of courses created via generative AI in 2024, with the ambition to reach 100% integration in the medium term.

 

Barriers to the adoption of generative AI

Despite these promising examples, several obstacles are hindering the widespread adoption of generative AI in French companies. The Mozza study highlights the main challenges:

  1. Lack of specialized skills: 35% report a shortage of AI experts. Self-training dominates, leaving little room for structured knowledge and the emergence of a cross-functional AI culture.
  2. Lack of clear governance: 32% of them do not have a dedicated AI manager, which leads to fragmented adoption and initiatives limited to certain departments.
  3. Data privacy concerns: 27% of respondents express concerns about data security, particularly in regulated sectors such as fintech and healthcare.
  4. Difficulty identifying relevant use cases: Although process automation is commonly leveraged, only 15% of respondents explore more advanced applications such as product innovation.

 

Outlook for the future

The future of generative AI in the French Tech relies on better structuring efforts and greater democratization of its uses. To meet these challenges, several strategic avenues are emerging:

  1. Strengthening internal skills: Implementing continuous training and awareness programs will enable companies to better harness the potential of generative AI.
  2. Centralizing AI initiatives: Clear governance and dedicated teams are essential to coordinate and maximize organizational impact.
  3. Transparency and education: As Doctrine points out, it is crucial to reassure users about the reliability of AI models, particularly in sensitive sectors.
  4. Focus on product innovation: To stand out, companies must go beyond automation and explore disruptive use cases that transform their value proposition.

 

Conclusion

Generative AI offers unprecedented opportunities for French startups and scale-ups. However, for it to become a true lever of differentiation, the ecosystem must overcome its organizational and technological barriers. With strategic and coordinated adoption, generative AI could well become the spearhead of French innovation, consolidating the country’s position on the global technology stage.

 

Sources Mozza.io