A small business that spends two hours a day re-entering invoices into a spreadsheet does not solve its growth problem by adding a salesperson. It solves it by eliminating the re-entry. This type of on-the-ground diagnosis separates companies that progress from those that merely fidget. Boosting your company’s performance in 2024 relies less on grand strategic plans and more on concrete decisions regarding three or four specific projects.
Electronic invoicing: a cybersecurity project, not just a formality
Electronic invoicing is often reduced to an administrative constraint. In practice, it is a project that involves the IT department as much as accounting. Each invoice flow becomes a potential attack vector: supplier identity theft, interception of bank details, injection of fraudulent data into the payment chain.
Before choosing a platform, three points should be checked to avoid unpleasant surprises:
- The provider’s compliance with the French regulatory framework (registration as a partner dematerialization platform, secure transmission protocols).
- The actual integration with your existing management software, not just a makeshift CSV export.
- The traceability of access: who consults what, from which workstation, with what level of authorization.
Many small businesses discover these constraints at the time of deployment. Anticipating this project as an IT security initiative, rather than just a simple file format change, can save several weeks of production time. Companies that follow regulatory news on the atlanticnews.fr site for businesses identify deadlines and obligations that concern them earlier.
AI literacy and European regulation: how compliance changes daily operations
As of February 2, 2025, the European regulation on artificial intelligence imposes a requirement for AI literacy on organizations deploying these systems. In practical terms, every employee using an AI tool must have a sufficient level of understanding to evaluate its results and limitations.
This is no longer an optional lever for performance. It is a compliance issue, just like GDPR. A company that uses a chatbot for customer service or a scoring algorithm for financial management without training its teams exposes itself to real legal risks.
Training without paralyzing productivity
We are not talking about sending the entire team to pursue a master’s in data science. It involves short, job-oriented sessions. A salesperson learns to verify the suggestions of an automated prospecting tool. An accountant learns to spot an anomaly in an AI-assisted bank reconciliation.
Measuring the actual yield of AI requires integrating the cost of training and human oversight, not just the price of the license. Companies that omit these items from their calculations systematically overestimate their return on investment.
Cybersecurity for SMEs: protecting daily management
Cyberattacks no longer solely target large corporations. SMEs represent a prime target precisely because their protection systems are often under-resourced. A ransomware attack that blocks access to customer files for a week can jeopardize the cash flow of a small business.
The problem is not always technical. The attacker often knows the system better than the victim. We observe intrusions that exploit poorly configured VPN access, shared passwords among employees, or backups stored on the same network as production data.
Three concrete low-cost actions
- Physically or logically separate backups from the main network, so that ransomware cannot encrypt copies at the same time as the originals.
- Enable two-factor authentication on all remote access (email, ERP, cloud tools).
- Organize an internal phishing test once a quarter to identify the most exposed employees and adapt awareness training.
These measures do not require a significant budget. They require a management decision and regular monitoring. Most SMEs that suffer an attack had identified the vulnerability beforehand without correcting it.
Adoption of AI in SMEs: going beyond the showcase effect
The adoption of AI is progressing in French companies, but the gap remains significant between large structures and small businesses. Very small enterprises and SMEs rarely lack interest in these tools. They lack the time to sift through the offerings, test, compare, and especially to verify that the tool integrates into their existing processes.
A common scenario: a small business subscribes to a marketing content generation tool, uses it intensively for two months, then abandons it due to a lack of measurable results. The problem does not lie with the tool. It stems from the absence of initial framing regarding what is specifically expected and how results are measured.
Frame before deploying
Before investing, identify a repetitive, quantifiable task whose result can be verified by a human. Chasing unpaid invoices, sorting applications based on objective criteria, detecting anomalies in bank statements: these uses produce visible productivity gains within weeks.
A technological deployment does not guarantee a productivity gain if the input data is poorly structured or if no one verifies the outputs. Feedback on this point varies by sector, but the observation is consistent everywhere: without clean data, AI amplifies disorder instead of reducing it.
A company’s performance in 2024 hinges on projects that are anything but spectacular: securing invoicing flows, training teams on the tools they use, locking down remote access, framing AI projects around measurable use cases. These are management decisions, not technological bets.
