AI also has the power to optimize customer communication through chatbots and virtual assistants . These will free up team members to perform more strategic tasks and improve the customer experience by providing proactive updates , resolving customer inquiries in real-time , and even anticipating potential delivery delays .
This technology can also automate the process of matching delivery data with financial records , reducing errors and speeding up billing reconciliation . Furthermore , AI and machine learning ( ML ) algorithms can even be used for loss prevention by detecting anomalies in the supply chain and automatically flagging potential issues before they lead to financial losses .
Last-mile carriers that embrace AI and ML will have a competitive advantage , especially those who invest in technologies with self-healing or self-learning capabilities . These technologies can process large amounts of data and learn to adapt over time . They can refine their outputs based on real-world performance or challenges without the need for human intervention . These technologies also enable carriers to go beyond data visualization by automatically providing actionable insights without manually inputting or interpreting data .
Carriers adopting AI can easily understand and access critical insights through AI-driven dashboards , enabling them to take immediate action through simple commands or automated workflows . This will dramatically reduce operational bottlenecks , improve decision-making and speed-to-decision , and allow for a more agile , responsive last-mile ecosystem .
CLDA Mag : Where will AI have its most significant impact on last-mile providers , and why ?
Jagad : Last-mile providers serve shippers who send their orders through diverse sources like BOL documents , emails , and customer calls . All this data needs to be digested into a structured form that can be fed into a delivery management system for visibility and execution . Generative AI technologies can interpret order information from varied sources and convert them into structured formats readable by downstream systems . This will save a lot of manual processing time that providers currently dedicate to order creation .
Similarly , AI-based technology can provide information about the progress of orders to end customers through automated customer service digital agents . These reduce the burden of customer inquiries on customer support desks . Machine learning AI algorithms can automatically detect deliveries dropped off at the wrong locations and analyze mis-scans to track down missing packages .
AI-based algorithms can also improve traditional route optimization methodologies by identifying the
... AI-based technology can provide information about the progress of orders to end customers through automated customer service digital agents . These reduce the burden of customer inquiries on customer support desks .
32 customized logistics & delivery Magazine I fall / winter 2024