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Supply Chain AI: 25 Current Use Cases (and a Handful of Future Ones)

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Supply Chain Ai: 25 Current Use Cases (and A Handful Of Future Ones)

When it came out, ChatGPT seemed like magic. It has led supply chain vendors to discuss how they currently use artificial intelligence. Further, virtually every supplier of supply chain solutions is eager to explain the ongoing investments they are making in artificial intelligence.

Any device that can perceive its environment and can take actions that maximize its chance of success at some goal is engaged in some form of artificial intelligence. AI is not a new technology in the supply chain realm; it has been used in some cases for decades. More recently, many other cases have emerged.

Optimization is used in supply planning, factory scheduling, supply chain design, and transportation planning. In a broad sense, optimization refers to creating plans that help companies achieve service levels and other goals at the lowest cost. In mathematical terms, optimization is a mixed-integer or linear programming approach to finding the best combination of warehouses, factories, transportation flows, and other supply chain resources under real-world constraints.

Machine Learning occurs when a machine takes the output, observes its accuracy, and updates its model so that better outputs will occur. Demand planning engines have natural feedback loops that allow the forecast engine to learn. The forecast can be compared to what actually shipped or sold.

Since ML began being used in demand forecasting in the early 2000s, ML has helped greatly increase the breadth and depth of forecasting. Now, ML forecasting is not just monthly or quarterly; weekly and even daily forecasting is now possible. We have moved from product-level forecasts at a regional level to stock-keeping unit forecasts made at the store level. More recently, demand planning applications based on machine learning have improved forecasting by incorporating competitor pricing data, store traffic, and weather data.

We are no longer just forecasting demand but also when trucks and factory machinery are likely to break down (predictive maintenance), the optimal amount of inventory to hold and where it should be held (inventory optimization), and labor forecasting in the warehouse. This type of forecasting can forecast the number of employees required to perform estimated work down to the day, shift, job, and zone level. ML can also be used to generate labor standards for warehouse workers.

ML techniques like clustering, data similarity, and semantic tagging can automate master data management. Without accurate data, companies face the garbage in, garbage out problem.

In terms of supply planning, if key parameters (like supplier lead times) are no longer correct, then the planning becomes suboptimal. ML is being used to keep key parameters and policies up to date. It is also being used to predict whether an SKU believed to be in stock at a store is actually out of stock.

Supply chain risk solutions use ML and other forms of AI to predict which suppliers are included in a company’s multi-tier supply chain. This is becoming increasingly necessary as customs will hold up shipments at the port if it believes the shipment contains products made with slave labor from China, even if those components came from their supplier’s supplier’s supplier and represent a minuscule portion of the total cost of the product. Shippers’ end-to-end supply chain predictions are based on applying AI to OpenWeb searches, import/export records, data from sourcing platforms like ThomasNet, federal logistics records, and other data. These predictions accelerate a company’s ability to verify how its extended supply chain is constructed. Customs uses the same technology to determine which shipments should be denied entry.

Natural Language Processing is used to classify commodity classification for use in imports and exports and in real-time supply chain risk solutions.

The Harmonized System is a commodity classification coding taxonomy that forms the basis upon which all goods are identified for customs. It is used by customs authorities worldwide. Using the right product classification allows companies to pay the correct tariffs. Paying the right tariffs is necessary to avoid government fines and calculate the true landed cost of products. The problem is that there is an incredible gap between how products are described commercially and how they are expressed in the national customs tariff schedules. This has resulted in error rates as high as 30%. The combination of natural language processing and expert systems has been used to automate and significantly improve the classification process.

Real-time risk solutions also use natural language processing to read online publications and other data sources, make sense of what they read, contextualize the data into information, and report supply chain disruptions caused by weather, geopolitical events, and other hazards in near real-time. Every step in that value chain has search terms associated with it. The names of the suppliers, carriers, logistics service providers become search terms. Those search terms are paired with terms signaling a problem – those terms might be “bankruptcy,” “plant fire,” “port explosion,” “strike”, and many, many other terms. So, the term “Haiphong” when combined in an article with the phrase “port fire” would generate an alert.

Reinforcement Learning is a form of machine learning that lets AI models refine their decision-making process based on positive, neutral, and negative feedback. For example, if you want to train a vision system to recognize a dog’s image, you will start by using humans to look at tens of thousands of images of animals. The humans label the pictures as dog, not dog, or unclear. The computer is then presented with those images. The system would say, “this is a dog” or “this is not a dog” and it learns whether its conclusion was correct.

Drones use this form of AI to improve inventory accuracy in a warehouse. Reinforcement learning allows the drone to recognize warehouse racks, pallets, and cases and get close enough to inventory to scan the barcodes. Similarly, reinforcement learning has been applied to security camera footage in the warehouse to ensure workers are following standard operating procedures.

Simultaneous localization and mapping (SLAM) allows a vehicle to construct and update a map of an unknown environment while simultaneously keeping track of the vehicle’s location within it. This technology allows mobile robots to move autonomously through a warehouse.

Drones and autonomous mobile robots using SLAM are in an early adoption stage for last-mile deliveries. Autonomous trucks will revolutionize logistics.

Autonomous trucks are not yet feasible, but we are probably just a couple of years out from being able to transport goods from a distribution center to a retail facility autonomously.

Causal AI is a technique in artificial intelligence that builds a causal model and can make inferences using causality rather than just correlation. Cause-and-effect relationships in an extended supply chain can be an intricate web that is difficult to unravel, but these relationships govern business operations. A causal model graph represents a network of interconnected entities and relationships, enabling the system to understand how various factors influence each other to create an optimized outcome. By leveraging causal knowledge and data graphs, Causal AI can navigate complex business scenarios, anticipate outcomes, and recommend optimal courses of action. Georgia-Pacific has demonstrated an application of Causal AI to improve touchless commerce dramatically. The solution was used to detect and correct both common and uncommon order errors or discrepancies in near real-time.

GenerativeAI is the new kid on the block. GenAI can generate text, images, videos, or other data using generative models. Some warehouse management suppliers are exploring using GenAI to generate end-of-shift reports or talking points used at standup meetings at the beginning of a shift.

Several supply chain application vendors are investing in GenAI to improve their user interfaces. The idea is that a user will make a request, and the system will take them directly to the answer they seek. GenAI can also help interpret complex charts and planning outputs. If a planning system indicates that a plan shows high costs or an inability to achieve targeted service levels, GenAI can help explain the upstream constraints driving that outcome.

Planning vendors are also interested in using GenAI to solve the black box problem. The black box problem occurs when planners don’t understand how the planning engine produced the plan it did. If they don’t understand it, they don’t trust it, and they then produce a much less optimal plan using Excel.

In the longer term, GenAI will help some planning vendors generate autonomous plans. When disruptions constantly occur, there is no time to constantly create and analyze scenarios on how to react best. Autonomous planning can improve a company’s supply chain agility. However, it is worth noting that a few planning suppliers can already generate autonomous plans based on ML and attribute-based planning rather than having to rely on GenAI.

The post Supply Chain AI: 25 Current Use Cases (and a Handful of Future Ones) appeared first on Logistics Viewpoints.

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What a Return to the Red Sea Could Mean for the Container Market

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What a Return to the Red Sea Could Mean for the Container Market

November 26, 2025

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As the fragile but still-in-place Israel-Hamas ceasefire nears the two-month mark, and with the Houthis declaring an end to attacks on passing vessels, there is more and more anticipation that the long-awaited return of container traffic to the Red Sea may be coming soon.

Though Maersk maintains it has not set a date, the Suez Canal Authority stated that Maersk will resume transits in early December. ZIM’s CEO recently stated that a return in the near future is increasingly likely, and CMA CGM is reportedly preparing for a full return in December.

Operational Impact

The shift of most of the 30% of global container volumes that normally transit the Suez Canal away from the Red Sea and around the Cape of Good Hope almost exactly two years ago added seven to ten days and thousands of nautical miles to Asia – Europe journeys and to some Asia – N. America sailings as well.

The return of container traffic to the shorter Suez route will result in the sudden early arrival of these ships, which will mean significant vessel bunching and congestion at already persistently congested European hubs. This congestion will cause delays and absorb capacity which could push container rates up on the affected lanes, and possibly beyond.

The shift back through the Suez Canal may initially keep some of the typically lower volume ports in Europe that have become transhipment centers during the Red Sea crisis, like Barcelona, busy while carriers may omit port calls at some of the congested major hubs. But after the unwind, these ports, as well as African ports that have been used as refuelling stops during the last two years, will see port calls decline.

Carriers have plans for a gradual phase in of the transition back to the Red Sea, with smaller vessels starting to transit first. This approach would still cause vessel bunching, but would be aimed at minimizing the impact of the reset as much as possible.

But some carriers are skeptical that an orderly phase-in will happen, as they expect pressure from customers who will want a return to the shorter route as quickly as possible. Analysis from Sea Intelligence suggests that the more gradual the transition, the less disruptive it will be, while the faster the return the more disruptive it will be during the up to two months it will take for schedules to return to normal.

Ocean expert Lars Jensen also notes that a return during the lead up to Lunar New Year would coincide with an increase in demand, and would put more pressure on ports and rates than if the transition takes place post-LNY when demand is typically weak. With carriers signalling the shift will begin in December and pre-LNY demand probably picking up in mid-January next year, it seems likely the two will coincide.

Implications for Capacity – and Rates

Red Sea diversions were estimated to have absorbed about 9% of global container capacity by keeping ships at sea for longer and – with longer journeys meaning vessels would arrive back at origins days behind schedule – via carriers adding extra vessels to services in order to maintain planned weekly departures.

This drain on capacity caused Asia – Europe rates to more than triple and transpacific rates to more than double in the two months from the time the diversions began to just before Lunar New Year of 2024. And though rates moved up and down along with seasonal changes in demand, the capacity drain pushed East-West rates up to 2024 highs of $8,000 – $10,000/FEU and set a highly elevated floor of $3,000 – $5,000/FEU during low demand periods that year.

But even with Red Sea diversions continuing to absorb capacity in 2025, continued fleet growth through newly built vessels entering the market has meant that the container trade has already become significantly oversupplied.

As such, rates on these lanes – even before the capacity absorbed by diversions has re-entered the market – have consistently been significantly lower than in 2024 even during months when volumes have been stronger, with prices on some lanes reaching 2023 levels for a span in early October. Recent carrier struggles maintaining transpacific GRIs point to this challenge already.

Even with Red Sea diversions continuing and even during months in 2025 with stronger year on year volumes, capacity growth has meant rates in 2025 have been lower than in 2024.

Yes, the initial congestion and delays caused by the transition back to the Suez Canal will at first put upward pressure on rates for Asia-Europe containers and probably to a lesser degree on the transatlantic lanes as well. If the congestion ties up enough capacity or impacts operations at Far East origins, the rate impact could spread to the transpacific as well. As noted above, if the return coincides with the lead-up to LNY, it will have a stronger impact on rates as there will be pressure from the demand side as well.

But once the congestion unwinds and container flows and schedules stabilize the shift will ultimately release more than two million TEU of container capacity back into the market. This surge will put even more downward pressure on rates and increase the challenge of effectively managing capacity for carriers seeking to keep vessels full and rates profitable in 2026.

Judah Levine

Head of Research, Freightos Group

Judah is an experienced market research manager, using data-driven analytics to deliver market-based insights. Judah produces the Freightos Group’s FBX Weekly Freight Update and other research on what’s happening in the industry from shipper behaviors to the latest in logistics technology and digitization.

Put the Data in Data-Backed Decision Making

Freightos Terminal helps tens of thousands of freight pros stay informed across all their ports and lanes

The post What a Return to the Red Sea Could Mean for the Container Market appeared first on Freightos.

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Transpac ocean rates fizzle; Red Sea return coming soon? – November 25, 2025 Update

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Transpac ocean rates fizzle; Red Sea return coming soon? – November 25, 2025 Update

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November 25, 2025

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Weekly highlights

Ocean rates – Freightos Baltic Index

Asia-US West Coast prices (FBX01 Weekly) decreased 32% to $1,903/FEU.

Asia-US East Coast prices (FBX03 Weekly) decreased 8% to $3,443/FEU.

Asia-N. Europe prices (FBX11 Weekly) decreased 1% to $2,457/FEU.

Asia-Mediterranean prices (FBX13 Weekly) increased 6% to $2,998/FEU.

Air rates – Freightos Air index

China – N. America weekly prices decreased 2% to $6.50/kg.

China – N. Europe weekly prices decreased 1% to $3.97/kg.

N. Europe – N. America weekly prices increased 1% to $2.33/kg.

Analysis

Despite higher tariffs since early this year, US retail sales have proved resilient and are expected to grow through the holiday season. The solidifying tariff landscape is nonetheless facing destabilizing forces like recent China-Japan tensions, and the US Supreme Court’s pending decision on the legality of Trump’s IEEPA-based tariffs.

But the White House is signalling it is already taking steps to ensure that a SCOTUS loss will not open a low tariff window. So, if consumer spending remains strong, and the status quo of the trade war holds up, the US could enter a restocking cycle in 2026 as frontloaded inventories wind down. This restocking could mean stronger freight demand than some have anticipated for next year.

On the freight supply side though, there is more and more discussion of container traffic’s coming return to the Red Sea as the fragile Israel-Hamas ceasefire remains in effect. And while most carriers are not offering a timeline, ZIM’s CEO recently stated that a return in the near future is increasingly likely.

The shift of most of the 30% of global container volumes that normally transit the Suez Canal away from the Red Sea and around the Cape of Good Hope almost exactly two years ago added seven to ten days and thousands of miles to Asia – Europe journeys and to some Asia – N. America sailings as well.

The return of container traffic to the shorter Suez route will result in the sudden early arrival of these ships, which will mean significant vessel bunching and congestion at already persistently congested European hubs. This congestion will cause delays and absorb capacity which could push container rates up on the affected lanes, and possibly beyond.

Carriers have plans for a gradual phase in of the transition back to the Red Sea, with smaller vessels starting to transit first. This approach would still cause vessel bunching, but would be aimed at minimizing the impact of the reset as much as possible.

But some carriers are skeptical that an orderly phase-in will happen, as they expect pressure from customers who will want a return to the shorter route as quickly as possible. Analysis from Sea Intelligence suggests that the more gradual the transition, the less disruptive it will be, while the faster it is the more disruptive it will be, and the more pressure it will put on freight rates during the up to two months it will take for schedules to return to normal.

Ocean expert Lars Jensen also notes that a return during the lead up to Lunar New Year would coincide with an increase in demand, and would put more pressure on ports and rates than if the transition takes place post-LNY when demand is typically weak.

The capacity absorbed through Red Sea diversions pushed East-West rates up to highs of $8,000 – $10,000/FEU in 2024 and set a highly elevated floor of $3,000 – $5,000/FEU during low demand periods that year. But even with Red Sea diversions still in place this year, rates on these lanes have consistently been significantly lower than last year, with prices on some lanes reaching 2023 levels for a span in early October.

The transition back to the Suez Canal – be it more or less chaotic – will ultimately release more than two million TEU of container capacity back into the market. This surge will put even more downward pressure on rates and increase the challenge of effectively managing capacity for carriers seeking to keep vessels full and rates profitable.

The current overcapacity on the East-West lanes is the main reason that carriers’ November transpacific GRIs which had pushed West Coast rates up by $1,000/FEU this month to about $3,000/FEU have now fizzled.

Asia – N. America West Coast prices fell 32% last week to $1,900/FEU with daily rates this week down another $100 so far, but prices remain above the $1,400/FEU low for the year hit in early October. Last week’s vessel fire at the Port of LA does not seem to have had an impact on prices as operations have quickly recovered. Rates to the East Coast fell 8% to $3,400/FEU last week but are at $3,000/FEU so far this week, about even with levels in early October before these set of GRI introductions.

Meanwhile, October and November’s GRIs on Asia-Europe lanes have stuck, with rates to Europe and the Mediterranean both 40% higher than in early October at $2,500/FEU and $3,000/FEU respectively. These rate gains may be surviving on aggressive blanked sailings on these lanes.

Carriers are planning additional GRIs for December aiming for the $3k-$4k/FEU level as they continue to reduce capacity – with an announced labor strike in Belgium likely to help absorb some supply – but there are signs that these increases may not take.

In air cargo, peak season demand is driving rates up and should keep doing so for the next couple weeks. Freightos Air Index data show ex-China rates remaining strong at about $6.50/kg to N. America and $4.00/kg to Europe last week. Demand out of S. East Asia has grown significantly during this year’s trade war, with rates also elevated on these lanes at $5.40/kg to the US and $3.50/kg to Europe.

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Rate, Book, & Manage: Real-time rate comparison, instant booking, and easy tracking at every shipment stage.

Judah Levine

Head of Research, Freightos Group

Judah is an experienced market research manager, using data-driven analytics to deliver market-based insights. Judah produces the Freightos Group’s FBX Weekly Freight Update and other research on what’s happening in the industry from shipper behaviors to the latest in logistics technology and digitization.

Put the Data in Data-Backed Decision Making

Freightos Terminal helps tens of thousands of freight pros stay informed across all their ports and lanes

The post Transpac ocean rates fizzle; Red Sea return coming soon? – November 25, 2025 Update appeared first on Freightos.

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How AI Is Driving the Future of Industrial Operations and the Supply Chain

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How Ai Is Driving The Future Of Industrial Operations And The Supply Chain

ARC Industry Leadership Forum • Orlando, Florida
February 9–12, 2026 • Renaissance Orlando at SeaWorld

Artificial intelligence is reshaping how industrial organizations run their operations and supply chains. The shift is real. The early experiments are gone. Today, companies are redesigning their planning, logistics, reliability, sourcing, and production workflows around systems that can think, react, and coordinate.

At ARC Advisory Group, we’re seeing this change accelerate every quarter. AI is moving from a standalone project to the connective tissue between operational systems. It’s improving how energy is consumed, how materials flow, how assets behave, and how teams respond to uncertainty.

This February, leaders from across the world will gather in Orlando to break down where AI is creating value and what comes next.

Event Details
Renaissance Orlando at SeaWorld
6677 Sea Harbor Drive, Orlando, FL 32821
February 9–12, 2026
Event link: https://www.arcweb.com/events/arc-industry-leadership-forum-orlando

More than 200 colleagues are already registered, including Conrad Hanf and a broad mix of executives, operations leaders, and technologists.

Why AI Matters Right Now

AI gives industrial organizations three capabilities they’ve never had before.

Real-time awareness.
Factories, yards, pipelines, fleets, and distribution nodes are producing enormous amounts of data. AI helps cut through that noise. It identifies what matters, when it matters, and why. The result is faster decisions and fewer surprises.

Coordination across functions.
Production affects logistics. Maintenance affects throughput. Sourcing affects lead time. AI lets these domains share context and act together instead of waiting for a meeting or a spreadsheet adjustment. Decisions that once took a day now happen instantly.

Pattern recognition at scale.
AI sees the earliest signals of asset degradation, demand shifts, port delays, or supply risk. It doesn’t wait for a problem to become a crisis. It alerts teams early and recommends actions with enough lead time to matter.

What Leaders Are Focusing On

Across our research and briefings, the same themes keep rising to the surface.

AI-driven maintenance and reliability.
Predictive models are becoming the default. They diagnose root causes, calculate the impact of failure, and help schedule work when it makes operational sense.

Modern planning and scheduling.
Forecasts now incorporate external signals, real-time plant conditions, and multi-site interactions. Planners are starting to work with continuously updated recommendations instead of static plans.

Autonomous supply chain operations.
AI agents are beginning to negotiate with carriers, re-route shipments, rebalance inventory, and adjust sourcing strategies. This isn’t sci-fi. It’s quietly happening in live networks.

Graph intelligence.
Industrial networks are connected by thousands of relationships. Knowledge-graph models help organizations understand those connections and trace how one event cascades across an entire operation.

Data discipline.
AI’s performance depends on clean, harmonized data across ERP, MES, historians, WMS, TMS, and supplier systems. Many companies are now tackling this foundational work head-on.

Human and AI collaboration.
The most successful organizations aren’t automating people out. They’re giving operators, planners, and engineers AI tools that amplify experience and judgment.

Why Attend the ARC Industry Leadership Forum

The Forum is where these shifts come together. Attendees will see:

• Real-world case studies from global manufacturers, logistics leaders, and utilities
• Demonstrations of AI-enabled control towers and reliability platforms
• Deep-dive sessions on agent-based systems, context management, RAG assistants, and graph reasoning
• Roundtable conversations with peers facing the same operational pressures
• Practical discussions on governance, cybersecurity, workforce roles, and measurable ROI

This event is built for leaders who want clarity, validation, and a realistic roadmap for scaling AI across the industrial value chain.

A Turning Point for Industrial Operations

AI is changing the fundamentals of how materials move, how assets perform, how demand is met, and how decisions get made. The organizations that learn to use this intelligence well will operate with more resilience, more predictability, and less friction.

The ARC Industry Leadership Forum is the best place to understand what this looks like in practice and how to prepare your organization for it.

Join Us in Orlando

If your role touches operations, supply chain, engineering, logistics, maintenance, or industrial strategy, this gathering will be well worth your time.

Reserve your seat:
https://www.arcweb.com/events/arc-industry-leadership-forum-orlando

We hope to see you there.

The post How AI Is Driving the Future of Industrial Operations and the Supply Chain appeared first on Logistics Viewpoints.

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