A small industrial company in the North lost three months of productivity in 2024 because its automated quote generation tool, based on an AI model, produced errors that no one internally knew how to detect. The problem was not technological; it was human: no employee had been trained to understand the system’s limitations.
This type of situation illustrates a concrete shift for French companies, where regulatory compliance on AI is becoming an operational issue on par with accounting or workplace safety.
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AI Literacy Requirement: What the AI Act Changes on the Ground
Since February 2, 2025, the European regulation on artificial intelligence (AI Act, Regulation (EU) 2024/1689) requires companies to ensure a sufficient level of AI literacy for personnel who design or use AI systems. Articles 4 and 5 are enforceable, with possible sanctions in case of non-compliance.
In practice, this means a skills enhancement plan tailored to profiles and actual uses. A marketing manager using a writing assistance tool does not need the same training as a developer integrating a predictive model into an ERP.
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Two dates structure the timeline for French SMEs: February 2025 for AI training and transparency, and then August 2026 for strengthened obligations regarding generated content. Companies that regularly publish analyses and insights on these topics, as can be read on the Expertise Entreprise website, help track these deadlines without falling behind.
Organizing an AI training plan is no longer a strategic choice; it is a legal obligation. Ignoring this constraint exposes companies to sanctions, but also to a loss of competitiveness against competitors already in compliance.
Recruitment and Skills: The Gap Between Discourse and Ground Practices
Everywhere you hear that soft skills and adaptability are the most sought-after competencies. On the ground, the reality is more nuanced. Companies hiring in 2024 are looking for profiles capable of combining precise technical know-how with the ability to use everyday digital tools.
The concrete problem: many micro and small businesses do not have a dedicated HR department. The manager writes the job offer, sorts the CVs, and conducts interviews. In this context, relying on overly abstract competency grids wastes time.
Three Operational Criteria to Filter Applications
- The actual mastery of the tools used in the company (not a generic list of software on a CV, but a practical demonstration during the interview)
- The ability to document one’s work, a reliable indicator of rigor and knowledge transfer in small structures
- Autonomy in facing a new technical problem, verifiable through an open-ended question about a past incident
These three filters help reduce recruitment errors without multiplying steps. A failed hire costs much more than a twenty-minute extended interview.
Hybrid Work in 2024: Beyond Telecommuting, the Concrete Organization
Hybrid work is not just about allowing two days of telecommuting per week. Companies that derive real benefits from it have revised their coordination processes, not just their HR agreements.
A common example: a sales team of eight people split between the office and home. Without clear rules on synchronous availability slots, meetings multiply to compensate for the lack of visibility. The result is more time in video conferences and less actual working time.
Structuring Hybrid Work Without Bureaucratizing
The key is to set a minimal framework and stick to it. It has been observed that teams that function well in a hybrid model share three simple practices:
- A daily common availability slot (even if short), known to all and respected
- A single task tracking tool, accessible in real-time, that replaces reminder emails
- An explicit rule on decisions made synchronously (meeting) and those resolved asynchronously (written message with a defined response time)
The problem with hybrid work is never the workplace; it is the absence of shared rules. Feedback on this point varies according to team size, but the principle remains the same: without an explicit framework, telecommuting generates more friction than it eliminates.
Technologies and AI in Business: Investing in the Right Place
Adopting AI does not mean stacking subscriptions to tools. In 2024, companies that achieve measurable benefits are those that have targeted a specific process to automate, rather than deploying a generic solution.
Let’s take a concrete case: a service company that automates the writing of meeting minutes using a transcription tool. The gain is immediate, quantifiable, and does not require restructuring. In contrast, investing in an AI-enhanced CRM without having cleaned up its customer database is like putting a new engine in a car without wheels.
Before investing in an AI tool, one maps the target process and its pain points. If the process is poorly defined upfront, the tool will only accelerate the disorder.
Prioritizing High-Return Use Cases
Repetitive tasks with low added value are the first candidates: client follow-ups, document sorting, generating standard reports. These automations free up time for activities that require human judgment, such as commercial negotiation or dispute management.
The upskilling of teams on these tools remains the limiting factor. A high-performing software in the hands of an untrained user produces mediocre, even dangerous results. This is exactly what the framework of the AI Act aims to regulate, and companies that anticipate this training gain a real competitive advantage.
The French entrepreneurial landscape in 2024 is less about grand strategic declarations and more about the ability to execute the fundamentals correctly: recruiting the right people, organizing hybrid work with clear rules, and training teams on the tools they use every day. The obligations related to the AI Act, with their deadlines in 2025 and 2026, add an additional constraint that leaders would do well to address now rather than in urgency.