Using AI to Improve Delivery Applications

Businesses are rapidly shifting to e-commerce in today’s complex market structure to maximize sales and expand their customer base. The e-commerce industry is expected to reach USD 120 billion by 2026, according to a report by the industry body. This has resulted in increased demand, making it difficult for businesses to meet customer expectations for timely delivery. Delays in delivery result not only in poor customer satisfaction but also in customer loss – this is simply unaffordable in a highly competitive market.

Recent technological advancements have resulted in the emergence of tech-savvy consumers who expect even faster delivery and support. The traditional delivery model, which entails planning routes, estimating fuel costs, and manually verifying the product and addresses, is insufficient. The traditional model is incapable of analyzing traffic patterns, identifying viable routes, or predicting miscommunication. Due to the fact that everything is done manually, planners are unaware of weather and other route parameters that could cause accidents or delays. Another significant disadvantage is the lack of real-time vehicle tracking. The company is unaware of the driver’s location, which can lead to fraud.

This is where artificial intelligence (AI) enters the picture. Logistics companies are integrating delivery management systems with AI capabilities to keep up with the soaring demand for faster deliveries while ensuring the safety of drivers and goods.

An AI-powered system is an innovative way to enable real-time delivery. Even before the customer places an order, the system uses GPS technology and machine learning (ML) capabilities to provide the best delivery options. According to a McKinsey report, artificial intelligence will usher in a new logistics paradigm by 2030. Many companies, have begun to use AI to enable faster, safer, and more efficient deliveries in order to increase customer satisfaction and retention.

But how does a system like this improve delivery management? The system predicts the best way to fulfill delivery based on various parameters such as weather, previous delivery records, number of deliveries, and inventory. These are some examples:

Route optimization: The system uses GPS technology to determine the shortest and safest route to the customer’s location. The route is chosen after taking into account factors such as traffic, the number of stops, and vehicle capacity. This allows for on-time deliveries and increases revenue.

ETA: Unlike traditional delivery models, the AI-enabled system estimates the arrival time of products. Customers can then reschedule delivery times based on their availability.

Inventory/warehouse management: The system allows companies to keep track of their inventory. It keeps track of every item as it moves through the warehouse, allowing for efficiency at every stage of the process.

Driverless delivery: These systems allow vehicles to manage deliveries automatically without the need for human intervention. Self-driving vehicles powered by LIDAR technology are used for driverless delivery. These electric vehicles reduce transportation costs, ultimately increasing productivity.

Risk detection and fraud prevention: The system assists businesses in detecting and preventing fraud. While planning the route, the system checks the records for anything out of the ordinary that may have occurred during previous deliveries. This greatly reduces the risk to both the driver and the goods.

 

Other Advantages Include:

Anticipatory logistics: It is the process of working on products before an order is placed. The system uses deep learning and machine learning to identify product demand, making it easier for the company to keep track of inventory in demand.

Increases efficiency: The AI analyzes the warehouse dimensions to determine the best location to store an item while taking its size and other safety measures into account.

Operational and fuel costs: When the system takes the shortest and safest route, it reduces vehicle wear and tear and saves fuel. This can be applied to other aspects of the company’s operations.

Increased productivity: AI can significantly boost a company’s productivity by providing the best logistics solutions that save time.

Many industries are incorporating AI into their operations to improve delivery. According to a recent MarketsandMarkets study, the drone logistics and transportation market will grow from USD 534 million in 2022 to USD 17,881 million by 2030, at a CAGR of 55.1% from 2022 to 2030. Healthcare, for example, is using drones to revolutionize the transportation of medicines and vaccines. These drones use AI systems to travel from one location to another in the shortest amount of time possible, with no human intervention. This can be useful in situations such as floods, landslides, and pandemics.

AI is making it easier for businesses to focus on other critical areas by streamlining the delivery process. More companies will incorporate AI into their delivery models as the business and e-commerce landscapes become more complex. Companies are making driverless delivery a reality by using AI as a guiding principle to avoid challenges in the middle-mile and last-mile delivery processes. This will assist businesses in improving their supply chain game.

AI has transformed the dynamics of delivery in healthcare, e-commerce, agriculture, and the military by adapting to the changing business environment. AI aided relief efforts during the COVID-19 pandemic by enabling driverless and drone delivery. In accordance with government guidelines, the collaboration of AI and delivery management systems enabled doctors to provide medicines and vaccines during the lockdowns.

As we move into a digital future, AI will undoubtedly open up new opportunities for businesses to thrive.