AI, a new performance driver for the Supply Chain
Faced with market volatility, ESG issues and pressure on costs, artificial intelligence is emerging as a key lever for digitizing and optimizing the supply chain. From forecasting to automation, it is redefining how businesses manage their operations.
1. The rise of AI in the Supply Chain
According to The Business Research Company (2024), the global market for AI applied to logistics will reach $5.7 billion in 2025, with an annual growth of more than 40%.
This acceleration is based on four major levers:
- Demand forecasting Thanks to machine learning,
- Automation logistical processes,
- Traceability in real time flows,
- Optimization stocks via connected and no-code platforms.
For Supply Chain Managers and CIOs, AI is becoming the basis for a Proactive management, able to anticipate rather than suffer from hazards.
2. Concrete and measurable use cases
Businesses that have integrated AI models into their processes are seeing:
- +70% accuracy On demand forecasts (WifiTalents, 2024),
- — 20% stock level And — 12% logistics costs (AllAboutai, 2024),
- A significant reduction in delays and breakdowns thanks to the Automated Anomaly Detection.
AI also makes it possible to Strengthening sustainable logistics : optimization of routes, reduction of distances traveled and better valuation of product returns (Arxiv, 2025).
3. The keys to a successful deployment
To move from experimentation to measurable value, some best practices:
- Set a clear objective (forecasting, traceability, automation).
- Ensuring data quality : an AI model is only efficient if the data is reliable.
- Involve Business Teams to facilitate adoption.
- Measuring gains : cost reduction, improved service rate, time savings on workflows.
A BCG study (2025) recalls that only 5% of businesses Take full advantage of AI in the absence of governance and project management.
4. The balance between automation and sustainability
If AI increases flexibility and performance, it must also be integrated into logic ESG : measure its energy impact, while promoting More responsible and circular supply chains.
The most mature companies are already adopting a hybrid approach: AI to optimize, human to decide.
Conclusion
Artificial intelligence is no longer an option, but a Natural Evolution of the Supply Chain.
It is transforming operations management, traceability and automation, while offering greater flexibility. Organizations that are able to integrate AI into their workflows will see their Agility and Their Performance Are Sustainably Strengthened.
FAQS
Q: Where do you start with AI in the supply chain?
→ Start with a measurable use case: forecasting, replenishment, or flow automation.
Q: Is AI replacing human control?
→ No. It assists, makes reliable and accelerates decision-making, but control remains human.
Q: What indicators should you monitor?
→ Accuracy of forecasts, shortage rates, stock levels, processing times, logistics costs.
Q: Can AI and sustainability be combined?
→ Yes. AI reduces trips, optimizes flows and limits waste, provided you control your energy footprint.
