AI is finally gaining ground in French SMEs

The wave of artificial intelligence sweeping through the French business landscape is no longer an abstraction: a field survey conducted in early 2025 with 1,209 small and medium-sized enterprise (SME) leaders reveals the extent to which this technology is becoming central to strategic decision-making. More than 700 companies have already benefited from structured support, a sign that the experimentation phase is giving way to the search for measurable value.

However, a quarter of business leaders still report feeling "stuck": aware of the challenge, but paralyzed by a lack of skills or internal support. This profile applies to 26% of the SMEs surveyed and represents the primary obstacle to advanced digital transformation.

Among all respondents, process optimization clearly dominates expectations: 90% place operational productivity at the top of their objectives, while barely 30% plan to rethink their business model using AI. AI is therefore still perceived primarily as a lever for efficiency rather than a tool for disruption.

The table of obstacles confirms this interpretation: 88% cite a lack of internal expertise, followed by funding needs (57%) and the absence of a clear strategic assessment (51%). The risk of execution, however, is only a marginal concern (5%). Without trained talent or a precise roadmap, most projects remain stalled.

The initial lag lies in data management: a third of companies still lack any serious data storage or processing systems, their information remaining scattered or not digitized. This gap hinders industrialization, even though AI can act as a catalyst, accelerating the digital modernization of SMEs.

Despite these limitations, each diagnostic reveals an average of fourteen use cases, 93% of which offer direct potential for productivity improvement, primarily in core business functions. The issue, therefore, is not inspiration, but prioritization.

Three categories emerge: "quick wins" account for 60% of priorities, "critical" projects 30%, and truly disruptive initiatives 10%. This ranking reflects a logic of quick wins before tackling more structural projects.

Quick wins almost always rely on generative AI building blocks parameterized on non-critical data; with budgets between €10,000 and €50,000, they offer an express return on investment by automating customer emails, reports or product descriptions.

From a technological standpoint, these choices translate into an overwhelming dominance of generative AI (61%), far ahead of prediction (24%), constrained optimization (18%) or computer vision (9%).

The economic benefit is tangible: 55% of the selected projects require less than €50,000 of investment, but more than two-thirds promise annual savings or additional revenue exceeding €50,000. This creates an ideal dynamic for convincing even the most hesitant boards of directors.

So-called "critical" projects, meanwhile, involve sensitive data and require budgets of €50,000 to €100,000. They transform production or service processes and require prior data qualification work, which explains why they are only highlighted by 30% of managers.

Less common, disruptive initiatives (≥ €100,000) redefine the business model: expert assistants integrated into offerings, automated compliance engines, or unprecedented predictive functionalities in a vertical software application. Only 10% of companies are currently venturing into this high-risk, high-value territory.

Whatever the ambition, success begins with the quality of the data assets. Digitizing, breaking down silos, documenting: without a reliable foundation, even the best algorithms deliver only anecdotal results.

Next comes acculturation: awareness workshops and internal pedagogy remove the fear of the unknown and align stakeholders on the same issues.

Involving teams in the co-design of solutions ensures a strong business focus, while visible sponsorship from senior management and the IT manager secures resources and overall consistency.

Human, budgetary and time resource management must be anticipated from the proof of concept phase to avoid the tunnel effect and maintain the pace until industrialization.

Finally, the issue of sovereignty and security becomes central: choice of suppliers, location of hosting, protection against cyber threats and regulatory compliance require strengthened governance of strategic data.

The year 2025 is shaping up to be pivotal. Falling training costs, the widespread adoption of autonomous agents, and the native integration of AI capabilities into office suites will commoditize low-value-added applications and open up space for innovation in more specific business needs. SMEs that have secured their data, skills, and governance foundations will then be able to capitalize on these new building blocks to create a sustainable competitive advantage.

To learn more: read French SMEs in the era of generative AI et 2025: The decisive rise of AI in French companies.