The role of AI in the new Supply Chain for 2025

By 2025, approximately 80% of new technological solutions for supply chain management will utilise artificial intelligence. In fact, AI in the supply chain is already demonstrating its transformative value, with significant improvements in logistics costs by 15%, stock levels by 35%, and service levels by 65%.

The revolution of AI supply chain management is accelerating, with a global market growing at an annual rate of 15.8% and expected to reach $3.8 billion by 2025. In particular, process automation through AI is redefining inventory management, delivery optimisation, and production planning, offering companies new opportunities to enhance operational efficiency.

In this guide, we will explore how artificial intelligence is transforming the supply chain, analysing key technologies, tangible benefits, and practical strategies for implementing AI solutions in your supply chain.

The Current State of AI in the Supply Chain

The global artificial intelligence market in the supply chain reached $5.05 billion in 2023 and is projected to grow at an annual rate of 38.9% until 2030. This significant increase reflects the widespread adoption of AI technologies in supply chain operations.

Key Technologies in Use

Artificial intelligence is redefining supply chain management through several key technologies.  Machine learning analyses historical data, sales trends, and external factors to improve demand forecasting accuracy.  Additionally, natural language processing (NLP) systems automatically classify goods for import/export and monitor online publications to identify potential supply chain disruptions.

Reinforcement learning enables drones to enhance inventory accuracy in warehouses by recognising shelves, pallets, and boxes to scan barcodes.  At the same time, SLAM (Simultaneous Localisation and Mapping) technology allows mobile robots to move autonomously within warehouses, building and updating maps in real time.

Key Industry Statistics

North America currently dominates the AI market in the supply chain, with a 38.4% share in 2023.  One significant insight emerges from AI implementation in quality control: 82% of organisations using AI solutions have recorded an 18% reduction in product defects.

Statistics show that 68% of supply chain organisations have integrated AI to improve traceability and operational visibility.  In the manufacturing sector, around 70% of companies adopted AI for predictive maintenance in 2023.

Realised Benefits

Early adopters of AI in supply chain management have achieved remarkable results.  Companies have reported a 15% reduction in logistics costs, a 35% improvement in inventory levels, and a 65% increase in service levels.

AI implementation has led to significant improvements in operational efficiency. Specifically:

• Automation of routine tasks has reduced the time required for operations management
• Predictive maintenance has improved equipment reliability, reducing downtime
• Real-time analytics has enhanced decision-making, enabling rapid responses to market conditions

Moreover, AI has proven effective in warehouse optimisation, analysing material flows to improve layout and reduce picking times.  Technology has also refined supplier management, automating performance analysis and streamlining procurement processes.

A particularly relevant aspect concerns sustainability: AI enables companies to monitor the environmental impact of their supply chain and take measures to reduce it, contributing to sustainability goals and regulatory compliance.

AI Application Areas

The application of artificial intelligence in the supply chain is revolutionising four key areas, offering significant advantages for companies adopting these innovative technologies.

Warehouse Management

Modern warehouses use AI to optimise operations through advanced robotic systems.  Robots equipped with computer vision autonomously recognise previously unseen objects, organising them efficiently for order fulfilment.  Additionally, autonomous mobile robots (AMRs) move freely within the warehouse without requiring predefined paths.

AI also analyses customer order data, inventory levels, and product movements to ensure optimal stock levels.  This technology allows for warehouse layout reorganisation to maximise space efficiency and reduce picking times.

Demand Forecasting

Machine learning algorithms analyse a wide range of data, including historical sales, market trends, and external factors such as weather conditions and economic indicators.  For example, a biotech company uses AI to run “what-if” scenarios on the availability of specific chemicals and assess the impact of potential global shocks.

A notable case is Gaviota, a manufacturer of automated sun protection systems, which achieved a 43% reduction in stock levels, decreasing inventory from 61 to 35 days.

Transport Optimisation

AI is transforming transport management by analysing data such as package information, delivery locations, traffic patterns, and weather conditions to identify the most efficient routes in real time. This approach enables:

• Reduction in fuel and operational costs
• Improved delivery time reliability
• Lower environmental impact through load optimisation

A major automotive manufacturer is testing the RoboDispatch solution, which uses AI to match delivery resources with demand in real time.

Predictive Maintenance

AI systems continuously monitor operational conditions by analysing data from sensors installed on critical equipment. These systems can:

• Detect anomalies indicating potential failures
• Schedule maintenance interventions during non-peak periods
• Extend the lifespan of equipment

According to a Deloitte 2022 study, AI-driven predictive maintenance tools can increase workforce productivity by 5% to 20% and reduce downtime by up to 15%.  A real-world example is GE Aviation, which uses sensors on 44,000 engines to predict maintenance needs before issues arise.

The Future of AI in the Supply Chain

By 2025, global supply chains will undergo significant changes thanks to the evolution of artificial intelligence.  According to the World Economic Forum, 86% of companies expect AI to radically transform their operations by 2030.

Emerging Trends for 2025

Supply chain automation is rapidly accelerating, primarily through:

• Advanced cognitive AI systems: Companies are adopting solutions that can make autonomous decisions, reducing the need for human intervention in 60-80% of planning actions.
• Edge computing and 5G technologies: These advancements will enable real-time decision-making based on data from sensors and IoT devices distributed throughout the supply chain.
• Digital Twin and Augmented Reality: Implementing digital twins will allow companies to test strategies without physical trials, optimising efficiency and sustainability.

As the sector continues to evolve, AI-driven innovations will position companies to build more resilient, efficient, and sustainable supply chains.