In a few years, working without artificial intelligence will probably seem as anachronistic as running a business today without email or management software.
France has just announced a new investment of 655 million euros in the development of artificial intelligence. A strong signal which confirms an underlying trend: AI is gradually establishing itself in all sectors of the economy. Agri-food distribution cannot be an exception.
In recent years, the sector has slowly been moving towards a more digital world, sometimes with enthusiasm, sometimes at a forced pace. Professionals know that they are entering a new productivity battle: inflation, rising operational costs, intensifying competition… Margins have never been under so much pressure. To succeed, the new competitive advantage is no longer just price, but speed of execution.
Prevent the productivity gap from turning into a competitive dropout
In the food supply chain, every minute counts. The products are fragile and perishable: wholesalers work in tight flow to meet the daily orders of their restaurant customers. Result: orders which arrive late in the evening, after the service, and which the teams must prepare and deliver first thing in the morning.
This sustained pace generates errors, but above all a considerable waste of time. Every minute spent re-entering an order, correcting an error or transferring information is a minute not spent on business development or customer service.
The big groups have understood this well. Faced with labor shortages and pressure on margins, they are investing heavily in automation. For SMEs, the real risk is no longer in adopting artificial intelligence, but in letting their competitors get several years ahead.
AI is not a project, it’s a journey
Many imagine AI as a revolution that will immediately disrupt their entire organization. In reality, the most successful companies generally follow a step-by-step progression.
The first consists of digitizing flows. Orders received by telephone, SMS, WhatsApp, e-mail or voicemail are automatically centralized and integrated into business tools. Teams spend less time entering information and finally have reliable and structured data. It is the essential base.
The second step is to use this data to develop the activity. Once orders are digitalized, it becomes possible to better understand purchasing habits, recommend complementary products, personalize offers or help salespeople identify new opportunities. The objective is no longer just to save time, but also to generate more turnover.
Then comes a third phase: improving profitability. Data makes it possible to direct customers towards more profitable products, optimize assortments, adjust prices more finely and reduce costs linked to errors or shortages. Data then becomes a real margin lever.
Finally, the most advanced companies are entering a fourth stage: intelligent automation. Artificial intelligence no longer just analyzes data; it helps teams take action. It prepares quotes, suggests next commercial actions, detects anomalies, anticipates certain customer needs or facilitates operational planning. Employees keep the decision, but work with an assistant capable of processing thousands of pieces of information in a few seconds.
Data becomes the strategic asset of distributors
This progression highlights a reality that is often underestimated: there is no effective artificial intelligence without quality data.
Companies that continue to operate with information scattered between phone calls, Excel sheets, emails or WhatsApp messages are depriving themselves of the raw material essential for future uses of AI. Conversely, those who structure their data today are building a lasting competitive advantage that is difficult to catch up with.
The challenge therefore goes far beyond the automation of a few administrative tasks. This involves gradually building up a data base that will enable us to make better decisions, offer better service and gain competitiveness in the future.
The risk is no longer in adopting AI, but in ignoring it
Artificial intelligence will not replace the know-how of the sector. A salesperson who has known his customers for twenty years, understands their constraints and anticipates their needs will always retain irreplaceable value. On the other hand, there is no reason for this same salesperson to still spend several hours a day re-entering orders.
AI is not a magic wand. It is an industrial tool, just like an ERP twenty years ago or a CRM fifteen years ago. In a few years, working without artificial intelligence will probably seem as anachronistic as running a business today without email or management software.
SMEs today have a rare opportunity: access to technologies previously reserved for very large groups. The tools already exist. Adoption costs are falling rapidly. The gap is now widening less between large and small companies than between those who are experimenting today and those who are waiting.
The companies that succeed tomorrow will not be those that have replaced their employees with AI, but those that have learned to make them more efficient thanks to it.
