How is AI Powering Logistics Tech Startups?

How is AI Powering Logistics Tech Startups?

By Logistics Tech Outlook | Thursday, September 19, 2019

Using AIs ability to extract useful insights from massive data sets, logistics tech startups are bringing transparency in their processes.

FREMONT, CA: Industries are striving to include artificial intelligence (AI) into their processes. The ability of the technology to extract insights from massive data sets is leading to an increase in its popularity across the verticals. Logistics and supply chain management is not behind in the AI race. According to research, the AI in supply chain and logistics market is expected to grow at a CAGR of 42.9 percent during 2017-2023 and will touch $6.5 billion by 2023.

The amounts of data generated and complexity in the industry requires a better structure that reflects transparency via digitalization. Apart from operational challenges, people expect faster delivery of the products, whether it’s a customer or a multinational corporation awaiting new equipment. In addition to the speed of delivery, consumers expect pick-ups and deliveries at their desired time slot, putting a layer of complexity along the path to optimization. Pricing is another issue that requires consideration.

Companies are expected to deliver a better quality of service at lower costs in the age of online transparency. It puts pressure on company margins, thereby forcing them toward labor automation. There are numerous moving factors to the industry that is leading it toward AI and the augmentation. With several players operating across various parts of the supply chain, such as operators, subcontractors, airlines, and others, the industry is too large to fail. However, it’s prone to hard losses and economic stagnation if the entire setup does not adapt according to the modern age.

Trends and Major Players

Despite various innovations coming from startups, established players are contributing to disruptions as well. For instance, companies like DHL and FedEx are constantly in the limelight when it comes to incorporating new technologies. DHL has designed a machine learning (ML) based tool that predicts time delays and air freight time delays.

FedEx announced its new FedEx SameDay Bot to enhance the efficiency of the “last mile” deliveries. Most of the big auto players such as Daimler, BMW, Toyota, Ford, and VW are developing autonomous vehicle technologies. Simultaneously, newer players like Tesla, Google, and Waymo are challenging their experienced counterparts by developing their autonomous vehicles using innovative manufacturing techniques and proprietary AI. Mobility platform companies such as Uber and Lyft are also partnering with established automotive companies to enable on-demand rides autonomously. Here are the following categories into which the innovations in logistics can be grouped into:

• Automating the Current Processes

Various companies are automating their processes as they have realized that automation is the first step toward large-scale optimization. Mainly the companies are focused on:

- Automation of redundant tasks such as invoicing, form completion, and inventory check-ups.

- Acceleration of the ambiguous brokerage process which is prone to human error and demands specific knowledge of regulations.

- Automation of customer data collection and storage. It is a challenge for major enterprises that wishes to maintain up-to-date records on their clients.

• Forecasting and Predicting for Process Optimization

Apart from the benefits of automation, AI has massive potential in terms of its predictive power too. Here are some of the potential applications that are either being internalized not explored by major logistics organizations:

- Predicting delivery routes by fostering communication among various participants across the global supply chain to efficiently pick up, transport, and deliver shipments.

- Improving the Overall Equipment Effectiveness index and predicting wear and tear of machinery.

- Forecasting fuel consumption for fleet optimization.

- Forecasting future demand for production.

• Incorporating Technology for Disruptive Innovation

Exploring the wide array of technology will present a sea of possibilities which will lead to more advanced forms of AI. For instance, considering the distance between the applications of Amazon’s fleet of autonomous delivery drones and Boston Dynamics:

- Intelligent robotic sorting will accelerate parcel processing while AI in image recognition will foster inventory management

- Purchasing via AI assistants such as Alexa, Siri, and Google will assist in personalizing the shopping experience and gear up the already breakneck speed of consumerism.

With further advancements in technology, it will be possible to talk through such virtual assistants who will ask the right questions to ensure that the task is completed. It may extend to rolling up of a truck to the front door of an office, picking up the shipments, and moving them along.

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