The adoption of AI in businesses doubles each year in France, but the majority of SMEs have still not structured their uses. According to Insee (Insee Première n° 2120, July 21, 2026), 18% of French companies with at least 10 employees used AI technology in 2025, compared to 10% in 2024 and 6% in 2023. Behind this progress, a gap persists between companies with 10 to 49 employees and those with 250 employees or more.
This observation changes the perspective on business trends for leaders who want to act on concrete levers.
Data Governance and AI in Business: The Real Bottleneck
Experimentation is no longer the issue. Most teams have tested a generative AI tool, whether for content creation, customer data analysis, or task automation. The blockage now lies upstream: who validates the authorized tools, what data can transit through them, and how to ensure compliance.
We observe that companies making the fastest progress in this area have appointed an internal referent, often linked to management, responsible for mapping existing uses and establishing a framework. This is not a data scientist position, but a coordination role between departments, IT, and legal management.
The stakes of privacy, cybersecurity, and regulatory compliance have become prerequisites for deployment. Without a clear policy on the processing of customer data by a third-party tool, the legal and reputational risk far exceeds the expected productivity gains. Recent analyses, particularly those from Bpifrance Le Lab and Insee, converge on this point: profitable AI in business first requires solid governance.
Several insights on these topics can be found on Actualité Premium, with operational angles tailored to SME and mid-sized company leaders.
Marketing Strategy and Customer Personalization: What Works Beyond the Discourse
Personalizing the customer experience remains the most cited trend, but its actual implementation is stagnating in many organizations. The problem is not technological. Segmentation, marketing automation, and behavioral scoring tools have existed for years. The barrier is organizational.
Personalization requires connecting purchase data, web browsing, customer service, and social media into a single repository. However, in most SMEs, this data remains siloed between CRM, e-commerce platforms, and email marketing tools.
Three Conditions for Personalization that Generates Sales
- A unique customer identifier shared across all channels (online store, point of sale, after-sales service), otherwise segmentation produces duplicates and inconsistencies
- A clear rule on solicitation frequency: too high a cadence degrades the contact base in the medium term due to accumulated unsubscribes
- Management by margin rather than sales volume: personalizing product recommendations towards high-margin references instead of discounted best-sellers changes the profitability of each campaign
We recommend starting with a single customer journey (for example, cart abandonment) before deploying a global personalization strategy. This sequencing avoids mobilizing resources on complex scenarios whose return is not measurable.
Installment Payments and Purchase Journey: An Underestimated Business Lever
Installment payments are no longer reserved for large e-commerce baskets. Their adoption has extended to B2B services, software subscriptions, and consulting services. For a company selling online, offering payment in installments reduces the abandonment rate at checkout.
The technical challenge lies in integration. Installment payment solutions (Alma, Pledg, or native options from Stripe) must fit into the purchase funnel without adding an extra step. Each additional click before payment validation decreases conversion.
On the management side, the point of caution concerns the actual cost of the service. Commissions vary based on the number of installments and the customer risk profile. We find that many merchants activate three-installment payments without modeling the impact on their net margin. A simple calculation: if the commission represents more than half of the gross margin on a product, the system destroys value instead of creating it.
Content and B2B Social Media: Produce Less, Distribute Better
The production of marketing content has exploded with generative AI tools. The attention of B2B decision-makers has not increased proportionally, creating a growing imbalance between the supply of content and the absorption capacity of target audiences.
The result: engagement rates are mechanically declining. Publishing three posts per week on social media is no longer very effective if the content does not target a specific segment with a fresh angle.
What We Recommend to B2B Marketing Teams
Reduce the publication cadence and invest the time saved in distribution. A well-optimized article, shared in a segmented newsletter and commented on in third-party posts with a large audience, generates more leads than a series of generic publications.
The long format (case studies, industry benchmarks, quantified feedback) outperforms the short format in B2B, provided it is distributed in the right place. Content management tools today allow for planning this multichannel distribution without multiplying resources.
The underlying trend for the coming months will be neither the miracle tool nor the trendy channel. Companies that progress will be those that have structured their data governance, targeted their marketing investments, and measured each action by its impact on margin. The rest is just noise.
