The year 2020 has been a year of supply chain disruptions worldwide that have significantly accelerated the adoption of emerging and advanced technologies across the industry. How to future-proof your business against disruptions and make supply chains resilient have remained the focus of companies this year. With the growing need for digitization, Artificial Intelligence finds multiple usages in the shipping and logistics industry that can deliver various benefits from automation to enhanced efficiencies to cost savings.
McKinsey’s Global AI Survey in 2019 suggested that there has been a 25% year-on-year increase in the usage of AI in business processes. 44% of respondents who employed AI in their business processes have reported sizable cost reductions. Artificial Intelligence has found its use in several applications throughout the supply chain, enabling mass personalization, the rise of deliveries made through automated vehicles, and sustainable logistics. From Computer Vision to Natural Language Processing, personalizing conversations with customers through chatbots has all been in the limelight. The trends are most likely to continue and further advance in the coming years.
What is Artificial Intelligence?
In simple terms, Artificial Intelligence is a machine’s ability to think and act like humans. Artificial Intelligence enables machines to display intelligence mimicking the human way of thinking, working, responding, or solving real-life problems. The outcome of using Artificial Intelligence could be improved automation of business processes, enhanced responsiveness and swifter delivery of results, better service levels, and enhanced customer satisfaction.
The adoption of Artificial Intelligence in shipping and logistics has its share of benefits. For any business, an AI-powered supply chain can mean a competitive advantage through data-driven decision making. Evident cost reduction is a natural outcome of employing advanced technologies in logistics and supply chain that enhance the efficiency and effectiveness of operational activities. AI has a proven track record of elevating the end-user experience of digital platforms through more human-like interactions.
While the benefits are many, the large scale adoption of Artificial Intelligence comes with its own share of challenges. Technology is expensive, high capital costs and infrastructural requirements for AI implementation can be a significant bottleneck for small and medium-sized businesses. There is an evident resistance from regulatory bodies and workforces towards the concept of automation. Ethical concerns regarding the relevance and control of Artificial Intelligence are some challenges that can pose roadblocks towards a large scale adoption of emerging technologies. However, the applications of AI in shipping and logistics is quite lucrative and can do wonders towards the digitalization of supply chains.
Applications of AI in Shipping and Logistics
- Demand Forecasting: Demand forecasting depends on historical data, and using AI can further enhance analyzing historical and real-time data to provide precise demand forecasts. With more accurate demand forecasts, shippers can optimize inventory management, dispatches, and workforce planning, thereby increasing service levels. McKinsey stated in a report that AI-powered forecasting methods could reduce errors by 30-50% in supply chain networks.
- Supply Planning: Supply planning is an essential part of logistics. Artificial Intelligence can aid in demand analysis based on real-time data. Businesses can dynamically adjust their supply planning parameters to optimize supply chain flow, increase efficiencies, and increase profitability.
- Automation in Warehousing: The rising need for contactless processes in supply chains due to the current global situations seem to have propelled the necessity of advanced automated business processes. AI has the potential to revolutionize automation in the warehousing scenario. Combining robotics with AI, robots are equipped to track and locate inventory and perform pick and pack functions that usually require an additional workforce to do the job. With automation comes efficient resource allocation that enables assigning the workforce to do more value-added activities rather than manual chores. Deep learning further facilitates the learning in these robots, which allows them to make autonomous decisions regarding activities within the scenario they are deployed in.
- Intelligent Computer Vision: Deep learning and AI have enabled advanced scanning, surveillance, and automation to visualize many logistics scenarios through images and videos and direct operations accordingly. This has changed how shipments are dimensioned or inspected for damage, labeling, and stacking arrangements while loading. Computer Vision, combined with Deep Learning in self-driving vehicles for automated and smart navigation, is now a reality.
- Workflow automation: Workflow Automation is the utilization of Artificial Intelligence to streamline complex and manual back-office operations. Documentation in freight forwarding is a tedious task and has immense potential for automation using Robotic Process Automation (RPA) and Optical Character Recognition (OCR). Shipping documents are all not in a standard format, and this is where technologies like these can automate reading and understanding documents that are printed or handwritten with utmost accuracy. Such workflow automation can free up significant work-hours of the logistics personnel and assign them to do more value-added activities.
- Predictive logistics: Different touch points across a supply chain generate extensive data. Better Machine Learning algorithms can extract predictive insights in logistics that are critical to decision-making. Artificial Intelligence can aid decisions related to capacity planning, forecasting, and network optimization, thereby streamlining operations and enhancing overall supply chain performance. AI is finding extensive use in dynamic route optimization, managing delivery time windows, optimize fuel consumption, and load capacity utilization, among many other activities in last-mile deliveries thereby propelling the digitization of supply chains.
- Enhanced Shipment Tracking: Shipment visibility data is of critical importance to overall supply chain performance. AI-powered tracking and tracing capabilities help accurate prediction of ETAs and ETDs. Furthermore, the ability to alert on supply chain disruptions, delays, and risks in shipping routes can help businesses increase agility and employ backup measures to avoid significant losses. Machine Learning can also help analyze historical data to identify shipping patterns considering various factors such as weather conditions, seasonal demand fluctuations, congestion in trade lanes, etc. With extensive use of voice-based assistants or chatbots, customers or customer service personnel can extract the tracking information in seconds.
Artificial Intelligence has penetrated almost every walk of business and our personal lives. The increased use of such advanced technologies enhances the consumer experience, optimizes processes, reduces costs, and derives several other benefits for businesses. From targeted advertising to voice/virtual assistants, Artificial Intelligence is almost everywhere.
AI is solving many complex operational challenges in logistics. Dynamic route optimization, capacity planning, demand forecasts, and automation are all results of using these emerging technologies like AI, ML, NLP, RPA, etc. Workflow automation generates immense value in supply chains and AI combined with RPA, enabling companies to address complex data points and processes to extract critical analytics. Therefore, AI is no longer a novelty but a core-competence for most logistics businesses.
The increased application of AI has great potential in shipping and logistics; however, a large scale adoption across the industry will need a couple of years to materialize. Digitization of supply chains is of utmost importance, and SaaS based digital platforms are working wonderfully to bring about the necessary change. While the widespread application of AI may not yet be a priority among many businesses, using the SaaS-based digital platform to adopt digital transformation in supply chains is an evident trend within the industry. At Ocean Insights, we provide companies with high-end predictive intelligence through the Ocean Freight Tracking System that derives critical visibility analytics for your supply chain. To learn more about the visibility solutions at Ocean Insights, please contact us.