AI in Last-Mile Delivery: 7 Cost-Cutting Strategies for 2025

The most expensive part of logistics, last-mile delivery, is being transformed by AI. This comes as no surprise when the last mile can account for over 50% of total shipping costs. This final step of the logistics journey has always been notoriously expensive and complex.

As we look ahead to 2025, businesses are increasingly turning to AI-driven technologies to streamline last-mile delivery, cut rising costs, and keep customers satisfied. From advanced route optimization to autonomous delivery vehicles, AI is transforming the most challenging segment of logistics. In this post, we’ll explore seven ways AI is tackling last-mile deliveries head-on, and how your business can leverage these innovations to stay competitive and cost-effective.

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1. Route Optimization

AI-powered route optimization analyzes multiple factors, like traffic patterns, weather forecasts, and delivery data, to create the most efficient routes in real time. Unlike traditional GPS systems that give you static directions, AI solutions can handle complex multi-stop deliveries and adapt quickly to changing conditions.

Key Benefits

• Fuel Savings: Better routing minimizes unnecessary travel, cutting fuel expenses.
  
• Lower Labor Costs: More efficient routes reduce driver overtime and help complete deliveries faster.
  
• Reduced Vehicle Wear and Tear: Smarter routing means fewer miles driven, extending vehicle lifespans.
  
• Improved Delivery Accuracy: Fewer missed delivery windows and fewer reattempts.

Case in Point

Companies like UniUni use AI to optimize gig-economy driver routes, boosting delivery performance for major eCommerce clients in North America. By factoring in traffic congestion and road closures in real time, AI-driven routing ensures on-time deliveries—even in densely populated urban areas.

Pro Tip

Use predictive analytics to forecast upcoming delivery surges. That way, you can plan routes and resources before the rush hits.

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2. Demand Forecasting

Accurate demand forecasting is key to reducing wasted resources and cutting last-mile delivery costs. AI systems analyze historical trends, seasonal fluctuations, economic indicators, and even local events to predict delivery volumes with high precision.

Why It Matters

• Better Resource Management: Perfectly match staffing and vehicle availability to actual demand, lowering overheads.
  
• Reduced Inventory Expenses: Businesses can see a 10-20% reduction in inventory holding costs by aligning stock levels with forecasted demand.
  
• Faster Delivery Times: Accurate predictions allow you to pre-plan your routes and assign drivers efficiently, slashing lead times.

Real-World Example

By integrating AI-driven predictive analytics, UniUni helped Shein shorten North American delivery times from 10-14 days to 4-5 days. Similarly, Bettermile’s coordination tools streamline driver-recipient communication, saving both time and money.

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3. Autonomous Delivery Vehicles (ADVs)

Autonomous Delivery Vehicles are no longer a futuristic concept; they’re shaping up to be a viable solution for 24/7 last-mile deliveries. Equipped with advanced AI and machine learning, ADVs can navigate busy streets and make deliveries without human drivers.

Benefits

• Eliminated Driver Costs: Remove a significant labor expense from the equation.
  
• Round-the-Clock Operations: ADVs don’t need breaks, enabling continuous delivery schedules.
  
• Consistent Driving Patterns: Lower maintenance expenses due to regulated driving styles and fewer human errors.

Implementation Tips

1. Start Small: Launch a pilot program in a controlled environment, like a college campus or business park.
   
2. Partner Up: Work with established tech providers to ensure you have the right hardware and software.
   
3. Scale Gradually: Use data from pilot programs to guide your larger rollout strategy.

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4. Real-Time Tracking

Real-time tracking goes beyond “out for delivery” notifications. AI systems integrate GPS, IoT sensors, and intelligent algorithms to provide precise, up-to-the-minute tracking for each package.

How It Reduces Costs

• Avoid Delays and Disruptions: Route adjustments happen instantly when traffic or weather changes.
  
• Lower Fuel Use: Shorter, more direct routes are automatically recommended.
  
• Cut Labor & Maintenance Costs: Improved task management ensures each driver’s time is used efficiently.

Steps to Implement

1. Assess Current Infrastructure: Identify gaps in your existing tracking systems.
   
2. Run a Pilot: Implement real-time tracking for a small set of deliveries to measure ROI.
   
3. Train Your Team: Ensure staff understand how to interpret and act on real-time data.
   
4. Scale Up: Once the pilot is successful, expand coverage across your fleet.

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5. AI Fleet Management

Fleet management powered by AI replaces outdated manual methods with data-driven insights. By continuously analyzing historical and live data, AI can optimize everything from vehicle assignments to maintenance schedules.

Focus Areas

• Load Efficiency: Match the right vehicle size and capacity to each delivery load.
  
• Driver Scheduling: Automated scheduling reduces overtime and absenteeism.
  
• Preventive Maintenance: Predictive analytics can anticipate breakdowns before they happen.
  
• On-Demand Allocation: Scale your fleet quickly for peak seasons without long-term overhead.

Implementation Steps

1. Data Integration: Bring all fleet-related metrics into one AI platform.
   
2. Pilot and Test: Start with a small subset of vehicles to gauge ROI.
   
3. Expand & Train: Roll out platform-wide once you confirm results, and invest in training drivers and dispatchers.

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6. Improved Customer Service

AI-driven customer service tools help businesses proactively communicate with customers and reduce the need for repeated delivery attempts or support inquiries.

Key Features

• Accurate Delivery Estimates: Customers receive real-time ETAs, minimizing anxiety and missed deliveries.
  
• Automated Notifications: Systems can alert customers and drivers instantly about changes or delays.
  
• Predictive Issue Resolution: AI can flag potential problems (e.g., bad weather, road closures) and offer immediate solutions.

Cost Savings

• Lower Support Costs: Fewer inbound calls and emails.
  
• Reduced Redelivery Expenses: Accurate ETAs and proactive comms mean packages are more likely to be delivered on the first try.

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7. System Integration

Integration ties all AI tools—route optimization, demand forecasting, fleet management, and more—into a seamless system. This holistic approach eliminates data silos and ensures every department is aligned on delivery goals.

Cost-Saving Advantages

• Fewer Errors: Automated data synchronization reduces manual entry mistakes.
  
• Labor Efficiency: Workers can move smoothly between tasks without juggling multiple platforms.
  
• Real-Time Analytics: Quick, data-backed decisions help cut costs and boost performance.

Implementation Steps

1. Infrastructure Review: Map out existing tools and identify integration points.
   
2. Pilot Test: Choose a specific area—like route planning or fleet tracking—to integrate first.
   
3. Staff Training: Equip your team with the necessary skills to use integrated platforms effectively.
   
4. Modular Expansion: Platforms like Locus offer modular solutions, letting you scale integration step by step.

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Conclusion

Last-mile delivery remains the most complex and costly segment in logistics. By 2025, AI isn’t just a nice-to-have tool; it’s essential for staying competitive. Whether it’s route optimization, demand forecasting, or autonomous vehicles, AI solutions can dramatically cut costs while meeting ever-rising customer expectations. Embracing these technologies now will position your business to thrive, ensuring you’re ready for whatever challenges the logistics landscape brings next.

Bibliography:

UniUni. (n.d.). Enhanced customer service & UniUni’s new driver app. Retrieved from https://www.uniuni.com/enhanced-customer-service-uniunis-new-driver-app-is-here/

Contimod. (n.d.). Last-mile delivery statistics and trends. Retrieved from https://www.contimod.com/last-mile-statistics/