As the benefits become clearer, is shipping AI set to revolutionise shipping? We asked the experts on artificial intelligence in logistics for their thoughts.
The integration of artificial intelligence (AI) in logistics promises significant improvements, from enhanced KPIs to cost savings. We delve into how AI is transforming shipping and features expert insights on its future trajectory.
How is AI being used in Maritime?
AI leverages automation and machine learning to perform tasks and gather data without human intervention. By eliminating manual processes, logistics operations achieve greater efficiency, fewer errors, timely data reconciliation, and enhanced real-time accuracy—all while reducing the workload on human employees. A few use cases include:
Fleet Management and Monitoring – AI can be used to optimize shipping routes by analysing data from various sources, such as GPS, weather, and traffic. For example, AI can analyse real-time weather data to reroute ships to avoid storms or optimize routes to minimize fuel consumption and reduce emissions.
Predictive Maintenance – AI can predict when equipment and ships will need maintenance, helping reduce downtime and save costs. For instance, AI can analyse sensor data from ship engines to detect patterns that indicate when maintenance is needed, allowing for proactive repairs and preventing unexpected breakdowns.
Autonomous Ships – AI can be used to develop autonomous ships that can navigate, dock, and make decisions on their own, increasing safety and efficiency in the industry. For instance, autonomous ships equipped with AI can analyse real-time data from sensors to adjust their course and speed to avoid collisions with other vessels, rocks, or other obstacles.
Cargo Optimization – AI can be used to optimize cargo loading and unloading, by analysing data on cargo weight and volume, vessel stability, and port infrastructure. For example, AI can analyse real-time data on cargo volumes and vessel stability to optimize cargo distribution, preventing accidents and increasing efficiency.
Risk Management – AI-based risk management systems can analyse data from various sources to identify and mitigate risks in the shipping industry, such as weather, traffic, and piracy. For instance, AI can analyse real-time data from weather sensors and traffic reports to help ships avoid dangerous weather conditions or high-traffic areas.
Supply Chain Management – AI can help the industry optimize shipping processes, from order management to logistics and inventory management. For example, AI can analyse data on shipping routes, cargo volume, and delivery schedules to optimize the supply chain, reducing delays and increasing efficiency.
Fuel consumption modelling – AI is already contributing a lot to estimating the consumption of vessels. With the improvement of AI technologies, calculating and estimating the consumption of ships in different weather conditions and regions will become more accurate. And will help in choosing more efficient ships and controlling the contractual prerequisites.
AI in Logistics: The Next Phase
We spoke with Greg Kefer from Raft.AI to get his perspective on where we are heading.
“Over 25 years ago, the dot com and Cloud software boom changed the industry. The realisation that online resources had immense advantages over private data servers was slow, yet it became a stark reality over time.
In the supply chain vertical, Cloud was a particularly important innovation because it helped to remove information siloes whilst held back the industry. Although portals, EDIs, and other such integrations were required, the improved connectivity was a huge value proposition.
“We are now entering the next phase of innovation, with AI at the forefront of logistics. The potential impact of shipping AI is even more significant and faster than the cloud revolution, thanks to the already established data networks.
Solving longstanding problems
Logistics AI addresses one of the biggest challenges faced by API users: integration. Even the largest enterprises struggle with data formatting and document updates across their partners, leading to disruptions and costly errors. AI overcomes this by seamlessly converting data between formats, significantly reducing the integration burden.
With much of the infrastructure already in place, refining the system is less cumbersome than during the cloud era, especially with AI leading the way. Human intervention is only needed to correct gaps identified by AI.”
Raft.ai processes over $10 billion in logistics invoices annually. These invoices, which vary in format and come from thousands of partners, are efficiently processed by AI, eliminating the need for tedious manual data entry. This is a development everyone in the industry can support and embrace.
Ultimately, AI in logistics and supply chain networks will solve the longstanding issue of efficiently managing the vast amounts of global freight data.
Traders are already seeing digitalization requests from their partners for better integration. In the near future, instead of requiring specific formats for information and documentation, digital documents will be sent in their original formats, with AI handling the conversions. Imagine not having to manage different formats for every system—yours, your freight partner’s, and your customers’. This is the future we are moving towards.
After decades of doing things the same way (use this API, log in to this portal, connect this EDI, use this standard), it’s time to place AI at the center, enabling seamless operations for all parties involved.
International Cargo Express – powered by Logistics AI
At International Cargo Express, we use Raft.AI to improve our processes whilst saving our operators time. It has helped improve our customs clearance service:
“Before, we would need to create a separate brokerage job for each shipment, then populate it with all the details for every item [HS code] on the declaration” – Alice Farley, Branch Manager.
Now, the shipping AI reads all of the data off the documents, creates that brokerage job for us, and then populates all of the data so that we just need to check it.
For one-line declarations, it’s great. For those shipments we have with over one or two hundred lines, it’s a gamechanger.”
Alice continued with more information about where else we can use artificial intelligence in logistics supplier invoices:
“We receive invoices on a weekly or monthly basis from suppliers, with tens of lines which would normally need to be created as charges and matched to jobs.
Using a similar flow to the customs documents, we can extract all the information, have the charges created and matched, and then only be left with the discrepancies.
Overall using AI in our logistics and customs processes makes us more efficient and means that we can work better with both our customers and suppliers.”
Want to see the efficiency of logistics AI for yourself?
Improved accuracy, more timely processes, and a better use of our experts’ attention to your shipments – these are the things our clients benefit from at ICE thanks to shipping AI.
If you’d like a quote or some more information, get in touch today.
The post Ocean Freight on the Verge of a Revolution? How AI is Transforming Logistics appeared first on International Cargo Express.
