As soon we started rebounding from massive disruptions like the pandemic, geopolitical unrest, and other global events, the focus shifted to standardized ways of reinforcing supply chains. To build into a future-ready ecosystem – intuitive programs and functions that dictate order, yielding real-time power. AI usage excelled, and organizations realized it as a formidable ally heralded for its potential and use cases in other industries.
McKinsey’s findings indicate that AI adoption in logistics slashes costs by 15%, revamps inventory management by 35%, and skyrockets service levels by 65%. The forecast also speculates a staggering $1.3 – $2 trillion annual boost for the next two decades from AI-integrated logistics processes.
Here are the top 11 use cases of AI from 2023:
1. Demand Forecasting
AI transforms forecasting by leveraging real-time data, slashing error rates compared to traditional methods. Enhanced accuracy in demand prediction optimizes dispatches, cuts operational costs, and bolsters customer satisfaction by minimizing stockouts.
Enhanced precision in predicting demand empowers manufacturers to:
- optimize dispatched vehicle numbers to local warehouses
- trim operational expenses and enhance manpower planning
- witness a decline in holding costs, mitigating the opportunity cost of item retention. Ultimately, this contributes to minimizing stockouts, ensuring heightened customer satisfaction
2. Visual Inspection & Damage Control
Computer vision tech identifies damaged products, ensuring quality control and minimizing customer dissatisfaction. Prompt detection and action reduce further losses.
3. Predictive Maintenance for Machinery
AI-enabled predictive maintenance, fueled by real-time IoT data, pre-empts machine failures, minimizing downtime and enhancing reliability.
4. Autonomous Vehicles Redefining Transport
Self-driving vehicles, backed by Tesla, Google, and Mercedes-Benz, are on the cusp of transforming logistics. Though estimated to cover only 10% of light trucks by 2030, these vehicles promise reduced emissions and safer operations.
5. Drone Deliveries for Precision
In scenarios where ground transfer isn’t viable, delivery drones are emerging as game-changers, especially in time-sensitive industries like healthcare.
6. Dynamic Pricing in Real Time
AI-driven dynamic pricing swiftly responds to market fluctuations, aligning product prices with demand and competition.
7. Optimized Routes and Freight Management
AI analyzes routes, slashes shipping costs, and accelerates processes. Technologies like smart road systems or automated lane management augment all this, enhancing traffic management and reducing carbon footprints.
8. Streamlining Document Processing
Automation tech for invoice and document processing boosts efficiency and accuracy, streamlining communications across logistics networks.
9. Hyperautomation & Office Efficiency
Integrating AI, RPA, and process mining streamlines back-office tasks like scheduling, report generation, and email processing.
These technologies enable businesses to automate multiple back-office tasks:
- Scheduling and tracking: AI systems can handle transportation scheduling, cargo pipeline organization, employee assignment and management for specific stations, and package tracking within warehouses.
- Report generation: Logistics companies can utilize RPA tools for the automated creation of regular reports, which is vital for managerial insight and company-wide alignment. These solutions generate reports, analyze content, and email them to pertinent stakeholders.
- Email processing: RPA bots analyze auto-generated report content and dispatch emails to relevant stakeholders based on the information.
10. AI-Powered Customer Service
Chatbots handle low-to-medium call center tasks, from tracking shipments to amending orders, elevating customer service efficiency.
- Requesting a delivery
- Amending an order
- Tracking shipment
- Responding to a FAQ
11. Lead Scoring & Marketing Precision
AI assigns scores to leads, aiding sales reps in targeting the most promising prospects. Routine marketing tasks and sales analytics are also streamlined.
In this era of rapid advancements, AI becomes the cornerstone reshaping logistics, driving efficiency, and propelling the industry towards a more agile and customer-centric future.