Artificial intelligence in last-mile logistics: real cases and KPIs

Artificial intelligence in last-mile logistics is transforming the way companies manage their operations. From reducing costs to route optimization, AI has become a key driver of efficiency, customer satisfaction, and sustainability.

In this article, we’ll explore how major companies already leverage AI, what KPIs demonstrate its impact, and which tools are shaping the future of last-mile delivery.

Benefits of artificial intelligence applied to last-mile delivery

The adoption of artificial intelligence in last-mile logistics brings measurable benefits:

• Route optimization in real time, reducing fuel consumption.
  
• Demand prediction through machine learning models.
  
• Reduced delivery times, improving customer experience.
  
• Proactive issue management, anticipating delays or cancellations.
  

Companies like Amazon and DHL are already leading the way with remarkable results.

Real-world implementation cases

Amazon and predictive automation

Amazon uses AI to forecast package locations even before customers place an order, cutting delivery times by up to 35%.

DHL and route optimization

DHL applies AI algorithms in more than 50 countries, achieving 10% savings in logistics costs and improving on-time deliveries by 15%.

Startups in Latin America

Startups like CargoApp and Nowports are implementing AI solutions to improve real-time tracking and supply chain visibility across LATAM.

KPIs that prove the impact

To measure AI’s impact in logistics, companies track KPIs such as:

• On-Time Delivery Rate (OTD): percentage of successful on-time deliveries.
  
• Cost per Delivery: reduction of operational expenses per route.
  
• Net Promoter Score (NPS): customer satisfaction linked to delivery experience.
  
• CO₂ Reduction Metrics: sustainability improvements and lower carbon footprint.
  

Example: According to McKinsey, AI implementation can boost last-mile efficiency by 20–25%.

Tools and frameworks driving AI in logistics

Organizations can deploy AI solutions using:

• Google Vertex AI for predictive modeling.
  
• AWS Machine Learning to integrate with logistics systems.
  
• Microsoft Azure AI for scalability and big data management.
  
• Open-source frameworks like TensorFlow or PyTorch for tailored solutions.
  

These platforms allow companies of all sizes to embrace automation without the need for costly custom development.

Conclusion: the future of logistics with AI

The use of artificial intelligence in last-mile logistics is no longer futuristic—it’s already delivering measurable outcomes in costs, delivery times, and customer satisfaction.

If your company aims to stay competitive, now is the time to integrate AI into your value chain.

Ready to take your logistics to the next level with AI? At NativApps, we build customized technology solutions that drive your business forward.
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