From artificial intelligence to automation, these innovations are not only optimising efficiency but also enhancing safety, sustainability, and profitability in an industry critical to global trade and environmental preservation.

Danny Peachey (pictured), Manager Great Yarmouth from HTL Group, a leading provider of hydraulic torque wrenches, explores five key digital trends that are revolutionising the marine sector and reshaping the way we navigate and manage the world’s oceans.

Artificial Intelligence (AI) and Big Data Analytics

One of the most significant trends shaping the marine industry is the increasing adoption of AI and Big Data analytics. In fact, the Maritime AI market has seen an explosive expansion over the last year, nearly tripling in size, according to the new Thetius report commissioned by Lloyd’s Register. By analysing this data, AI systems can predict optimal routes and speeds, forecast maintenance needs, and reduce the likelihood of breakdowns. This proactive approach, called “predictive maintenance”, helps minimise vessel downtime. For example, the Danish company Maersk has implemented AI algorithms to predict machinery failures and optimise fuel usage, leading to substantial cost reductions.

The potential for AI goes beyond efficiency. Safety is a key benefit as AI-driven systems can monitor maritime conditions and forecast hazards such as piracy, extreme weather, or equipment failure, ensuring the safety of both ships and crews.

Autonomous Shipping and Robotics

Autonomous ships and robotics are redefining the future of the maritime sector. According to a study by Allied Market Research, the global market for autonomous ships is expected to reach £126,63 billion by 2030, with a compound annual growth rate (CAGR) of 6.8% from 2020 to 2030.

Autonomous ships reduce the need for large crews, which lowers labour costs and the risk of human error. They are equipped with advanced sensors, GPS technology, and AI, enabling them to navigate oceans efficiently. For example, Yara Birkeland, the world’s first autonomous, zero-emission container vessel, successfully completed its maiden voyage in 2022. This vessel operates with minimal human oversight and relies on a combination of onboard AI and remote operations.

Robotics are also making waves in the industry. Remotely Operated Vehicles (ROVs) and underwater drones are increasingly used for inspecting and repairing underwater infrastructure such as oil rigs and pipelines. These robots can perform tasks that would be dangerous or expensive for human divers, significantly reducing operational risks.

Blockchain Technology

The marine sector relies on complex supply chains, making Blockchain technology a game-changer. The global supply chain can involve multiple entities, ranging from shipping lines to customs authorities, creating opportunities for miscommunication, lost cargo, and fraud.

Blockchain’s decentralised, immutable ledger provides an unparalleled level of transparency, allowing all parties involved—shipowners, port authorities, customs agents, and freight companies—to have real-time access to data about cargo shipments and transactions

Furthermore, blockchain can facilitate the automation of contract execution through smart contracts, which automatically trigger payments, inspections, or approvals when certain conditions are met. By increasing trust and reducing delays, blockchain technology is helping the marine sector run more smoothly and cost-effectively.

The Internet of Things (IoT) and Smart Shipping

The Internet of Things (IoT) is creating an interconnected ecosystem in the marine industry, revolutionising everything from shipbuilding to operations and safety. By embedding sensors and communication devices into ships, engines, containers, and ports, IoT enables real-time monitoring of vessel conditions, cargo status, and environmental factors.

For instance, IoT can monitor a ship’s engine performance, detect wear and tear, and alert operators to potential mechanical failures before they become serious issues. It can also track cargo conditions—such as temperature, humidity, or pressure—ensuring that perishable goods like food or pharmaceuticals are transported safely and efficiently.

Danny Peachey, HTL Group

IoT is also revolutionising ports. Smart Ports use IoT systems to automate loading and unloading processes, manage energy consumption, and reduce bottlenecks. Ports such as Hamburg and Rotterdam are already implementing smart solutions that reduce port congestion and improve the flow of goods.

Sustainability and Green Shipping

As concerns over climate change grow, the marine sector is embracing sustainability and green shipping. The International Maritime Organization (IMO) has set ambitious targets to reduce the carbon intensity of international shipping by 40% by 2030 and 70% by 2050.

Digital technologies, such as AI and IoT, play a vital role in helping the industry meet these targets. For example, AI tools can optimise fuel consumption by adjusting ship speeds and routes based on real-time data. Moreover, the use of digital twin technology—a virtual replica of a physical ship—enables companies to simulate different designs and operational conditions, identifying the most energy-efficient options before they are implemented.

Low-carbon fuels, electric propulsion systems, and onboard energy management systems are increasingly being adopted, and digital platforms are being used to track carbon emissions, making compliance with environmental regulations easier and more transparent.

The marine industry is undergoing a significant digital transformation, driven by advances in AI, robotics, blockchain, IoT, and sustainability initiatives. These technologies are not only improving operational efficiency and safety but also helping the industry reduce its environmental impact. As these trends continue to evolve, the marine sector is set to become more agile, cost-effective, and sustainable, positioning itself for future growth in an increasingly digital world.

The post Digital Technologies Reshaping Shipping Industry appeared first on Logistics Business.

How do you decarbonise an industry built on movement? Freight alone is responsible for an estimated 7% of global greenhouse gas emissions: a stark reminder of the sector’s environmental footprint. The cost of inefficiency is simply too big to ignore. As supply chains stretch and demand for fast, flexible delivery keeps rising, the pressure is only mounting. From underserviced fleets to empty mileage and poor routing, the industry suffers from breakdowns in planning and execution that don’t just drive up emissions — it also chips away at profits. But these challenges can be tackled.

Driving sustainable change with AI

AI is already delivering real sustainability gains across two critical areas that one wouldn’t necessarily consider at first sight: fleet maintenance and transport operations. By enabling faster decisions, streamlined processes and smarter systems, it’s allowing logistics to move cleaner, without compromising performance.

The stakes are high. According to Siemens, the world’s 500 biggest companies lose almost $1.4 trillion annually through unplanned downtime. This is equivalent to a staggering 11% of their revenues. Logistics operations, with their tight delivery windows and high asset utilisation, acutely feel this impact.

Fleet maintenance is often overlooked in the sustainability conversation, but it’s a critical area for impact. Vehicles that are overserviced waste resources — not just materials but time. Those underserviced are prone to breakdowns, costly repairs and early replacement. Either way, it’s bad news for both business and the environment.

Smart AI-enabled maintenance to extend asset life

AI offers a better way forward, starting with standardised maintenance. Predictive and optimised maintenance are gaining traction, particularly in North America, where new industry standards are pushing AI-driven approaches to the forefront. At the heart of this evolution is the need for standardised data. Without it, fleets rely on inconsistent or proprietary codes to track service intervals, making it almost impossible to train AI models at scale or share insights across systems.

Philipp Pfister, Transporeon

New frameworks like the Vehicle Maintenance Reporting Standards (VMRS), developed through the American Trucking Association’s Technology and Maintenance Council, are changing that. By creating a universal language for tracking maintenance items, they lay the foundation for adaptive, AI-powered decisions, such as when to change oil based on real-world engine load and usage, not arbitrary intervals.

While VMRS is a strong step forward in North America, there’s still a long way to go globally, where much of today’s maintenance data remains fragmented. To unlock AI’s full potential, the industry needs a shared data foundation: code key standards that act as a common language across fleets, platforms and regions. Some platforms are already building toward that future by developing open, interoperable data models designed for global adoption.

The impact is tangible. AI can identify the ‘sweet spot’ for servicing, reducing waste from premature oil changes while avoiding unnecessary wear and tear. Today, maintenance often relies on a dashboard light, but AI enables a future where the vehicle doesn’t just alert the driver. It books its own appointment, sends performance data to a third party and rolls into the shop at exactly the right moment.

Optimising operations for fewer empty miles

Beyond the vehicle itself, AI is transforming how freight is planned, routed and executed. One of the biggest challenges in logistics today is empty mileage: trucks that travel without cargo, burning fuel and time. While some inefficiencies are structural — rooted in geography or how the freight network is organised — many can be addressed with the right technology. AI-powered systems now analyse real-time and historical data to recommend the most efficient routes, plan multi-stop loads and continuously recalculate in transit to adapt to delays, traffic or weather.

AI in load planning, procurement and visibility

Cloud-based platforms are already putting these capabilities into practice, using AI to dynamically match loads with carriers and minimise waiting times at docks. They’re also reducing the strain of just-in-time logistics, where tight delivery windows leave little room for error. Autonomous procurement tools can now handle transport sourcing with minimal human input, using statistical and symbolic AI to analyse unstructured requests, identify suitable partners and select the best fit across time, cost and environmental criteria. Combined with intelligent load planning tools that maximise truck space and reduce the total number of journeys required, these systems help cut emissions across every kilometre travelled.

The future is collaborative and AI-enabled

When applied across maintenance, execution and operational processes, AI can help drive significant sustainability gains in the logistics sector. While AI does consume considerable energy, particularly in generative AI (GenAI) models, the types of applications used in transportation and logistics are far less compute-intensive. The efficiency gains and emissions reductions they enable usually outweigh their footprint. It’s the net effect that matters. And in this context, AI is already showing transformative potential in building a more sustainable future for the industry.

However, sustainability in logistics depends on shared data, interoperable systems and collaboration between carriers, shippers, OEMs and tech providers. Whether it’s maintenance schedules or routing algorithms, AI only works when it can access reliable data and apply it across a broad enough sample to generate meaningful insights. That’s why standardisation is so important. We’re not just building tools. We’re shaping a smarter ecosystem, one where every decision, whether on the road or in the yard, contributes to a more efficient and sustainable whole. AI won’t transform logistics in a single leap. But by focusing on the fundamentals, it’s already reshaping how goods move, how fleets are managed and how sustainability goals are met. Because when the industry moves together, we lay the groundwork for a cleaner, more resilient future.

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Limited visibility with Blind warehouses

Blind warehouses are characterised by limited visibility into operations. Inventory counts may be outdated, workflows are manual, and decisions rely on human guesswork or historical trends rather than real-time insights. Why Blind warehouses fall behind:

Inventory inaccuracies: 46% of small to medium sized warehouses report that inaccurate inventory counts cause major fulfilment delays.
Lost productivity: Employees spend unnecessary hours locating stock or manually inputting data.
Delayed decisions: Without a clear operational picture, response times to disruptions are slow.
Cost inefficiencies: Overstocking or stockouts often occur due to poor forecasting and limited data.
Fragmented data: Warehouses often gather data in pieces, leading to disconnected insights that fail to represent the full picture.

The reality is clear: a lack of visibility is no longer sustainable. As customer expectations around speed and accuracy rise, blind decision-making becomes a liability.

What does it mean to become an Observable warehouse?

An Observable warehouse collects and records real-time data from all parts of its operations. This includes: Inventory movement and placement; Autonomous robot paths and performance; Warehouse environmental conditions; Inbound/outbound logistics and cycle times; Labour allocation and productivity.

Being observable doesn’t require full automation overnight. It means implementing systems that can provide visibility through sensors, IoT devices, AMRs (Autonomous Mobile Robots), computer vision, or digital twin platforms. For example, Ziegler selected Dexory to provide a scalable, reliable solution capable of operating seamlessly within the warehouse’s existing infrastructure. The deployment of DexoryView has delivered rapid and measurable value for Ziegler’s UK operations, including:

Faster stock recovery and fewer errors: The team is now able to quickly locate missing pallets, detect mispicks early, and address labelling or placement errors in real time – without halting operations. End of costly shutdowns for stock takes: Where full stock takes once required four days and weekend shifts, inventory is now continuously monitored – eliminating the need for disruptive audits and manual reconciliations.

‍The benefits of visibility

Becoming an Observable warehouse is the foundation for all other advancements. Here are several benefits:

Faster, smarter decisions: Managers gain immediate insights to prioritise tasks or reroute workflows.
Increased productivity: Time spent searching, scanning, and checking can be replaced with actionable data.
Reduced waste and errors: Real-time data reduces the risk of duplication, overstocking, or misplaced inventory.
Foundation for AI and automation: Visibility enables the implementation of intelligent systems that require real-time data to operate effectively.

For example, DCL Logistics has realized significant operational gains since deploying DexoryView:

14% increase in pallet location accuracy: With more precise data, the company has improved inventory reliability, reducing errors and improving fulfillment speed.
10x faster inventory counting: Compared to previously trialled drone-based systems, DexoryView delivers a tenfold increase in the speed of inventory counts – without disruption or downtime.
16 hours of labour saved per day: Eliminating manual inventory checks has freed up staff to focus on high-value strategic initiatives, such as warehouse space optimization and customized projects for clients.

Industry trends driving the need for observability

A few big changes in the industry are driving the move toward more Observable warehouses:

E-commerce growth: Faster delivery expectations mean warehouses must be more agile.
Labour shortages: Observable warehouses help optimise limited human resources.
Supply chain volatility: Data visibility enables real-time responsiveness.

According to a 2025 McKinsey report, companies that invested in real-time warehouse visibility were 33% more likely to exceed customer expectations and reduce fulfilment costs.

‍Don’t let lack of visibility hold you back

Warehouses can no longer afford to operate without clarity. The first step toward transformation is simple: see clearly. When you do, every other improvement becomes not just possible, but inevitable. Dexory is already helping warehouses across industries make this critical shift. The journey from blind to observable isn’t just a technology upgrade – it’s a mindset shift toward continuous improvement.

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Using AI-powered insights, Kallikor’s Adaption platform models and simulates complex operational scenarios to enable businesses to adopt new technologies and rehearse the transformation of their supply chains, so they can implement change and optimise their operations with confidence.

Using the Adaption platform, Morrisons is creating a comprehensive digital twin of its end-to-end supply chain, a fully interactive model that mirrors the complexity, scale, and pace of its national network. This transformational capability provides a powerful design space where Morrisons’ teams can experiment, test, and optimise decisions with unprecedented speed and precision, from warehouse operations to network-wide flows. More than a model, it becomes the environment where supply chain reality and strategic intent meet, aligning decisions, testing trade-offs, and unlocking gains in efficiency, resilience, and customer responsiveness.

As the partnership scales, Morrisons will operate with a living digital model fully integrated into its day-to-day operations, enabling continuous optimisation and proactive adaptation to market shifts. This strategic collaboration will position Morrisons at the forefront of supply chain innovation, enabling the delivery of sustained growth, operational excellence, and market-leading customer experiences through faster, smarter, and more agile decision-making across its business.

Ross Eggleton, Group Director: Logistics, Supply Chain & Technology at Morrisons, said: “Partnering with Kallikor will help us make better decisions faster. By using AI to bring the real and synthetic worlds together, we can design and evaluate changes across our entire supply chain. That means we can move quickly, solve the right problems, and ensure that every supply chain decision supports the bigger picture, delivering greater value and availability for customers while improving our efficiency and resilience.”

Jonathan Barrett, Kallikor

Jonathan Barrett (pictured, above), Kallikor CEO, said: “We’re witnessing a fundamental shift in supply chain strategy. Organisations that can redesign their networks dynamically, test multiple scenarios, and make evidence-backed decisions at speed will define tomorrow’s competitive landscape. This partnership positions Morrisons to turn market volatility into a competitive advantage through faster delivery, optimised cost structures, and complete alignment between operational execution and strategic vision.”

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“Transportation is the backbone of supply chains, essential to ensuring goods are delivered on time to meet customer expectations,” commented Bryant Smith, director, Transportation Management Systems (TMS) at Manhattan Associates. “Yet, managing transportation is becoming increasingly complex, pressured by demands on shorter fulfilment times, capacity and cost efficiencies, tighter sustainability regulations and the growing necessity for access to end-to-end visibility across all operations,” Smith added.

Fragmented systems: operational visibility and efficiency still challenging

The true value of visibility extends beyond simply accessing operational data: it lies in the ability to address issues highlighted by this information and action operational improvements more quickly and efficiently. Beyond disruptions however, 60% of organisations say that enhancing visibility leads to greater customer satisfaction, through more accurate and timely updates, while 50% cite reductions in transportation costs as a key benefit increased operational visibility.

The AI revolution: excitement but readiness challenges

61% of organisations anticipate fully autonomous Agentic AI, capable of acting independently to achieve specific goals within the next five years, however, only 37% have deeply integrated AI and machine learning in their TMS today.

While many might view five years in the AI space like an eon, the gap between future expectations and current usage is noteworthy given adoption is rarely straightforward: although almost half (48%) said that they already feel very prepared for autonomous agents by 2030, practically every organisation (99%) reported facing, or expecting to face, hurdles, with concerns including skill shortages (49%), integration difficulties (44%) and data quality and availability issues (44%).

With many organisations seemingly well-placed to take advantage of the cost, efficiency and scalability gains afforded by autonomous agents, those organisations on the other side need to rethink their AI strategies otherwise they risk losing significant (and possibly irretrievable) market share to rivals.

Sustainability compliance: a priority and significant pain point

The push for more sustainable transportation is widespread. 69% of organisations say sustainability is either a global mandate or an area of significant pressure, with 62% already implementing Corporate Sustainability Reporting Directive reporting. Navigating complex and shifting compliance requirements remains a global challenge, with sustainability compliance most frequently cited as a constraint expected to impact organisational performance over the next five years. A modern TMS can help to deliver the data visibility and functionality needed to measure progress and demonstrate compliance, vital to ensuring sustainability remains at the forefront of organisational thinking.

Smith summarised: “Modern transportation management demands organisations balance a range of competing priorities and the research clearly illustrates many organisations are still unprepared to meet the challenges of evolving sustainability mandates, expectations around AI and the need for more visible, actionable data insights. Looking ahead to 2030, these demands will intensify, increasing the pressure on organisations to operate transportation operations in smarter more intuitive ways.

“87% of respondents anticipate that challenges in areas such as operational visibility, AI adoption and sustainability compliance will intensify, leaving their current Transportation Management Systems struggling to keep pace. Failure to act now will expose organisations to rising costs, questions over long-term efficacy and the risk of falling short of customer promises,” Smith finished.

Additional stats:
• 48% of organisations spend more than 10% of their transportation logistics budget on errors and disruptions
• 78% view transportation management as a strategic imperative for success and this figure rises to 86% by 2030
• 61% are anticipating fully autonomous Agentic AI, capable of acting independently to achieve specific goals, or minimal human oversight within the next five years for TMS
• 50% report challenges in proactively rerouting shipments, while 49% struggle with optimising dock and warehouse labour scheduling
• 82% express strong confidence that advances in planning, forecasting and modelling will reduce freight costs by at least 5% within the next five years.
• Organisations are still struggling to operationalise sustainability: only 34% say they’ve factored sustainability into operational planning, 30% into procurement decisions and just 31% offer carbon-friendly fuel solutions.
• While a majority have integrated their TMS with Sales and Operations Planning systems (60%) and are utilising predictive analytics or AI (56%), far fewer are capitalising on key enablers such as historical trend analysis (38%), automated booking and tendering (36%), or real-time demand sensing (35%).

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How is the maritime sector navigating the twin pressures of decarbonisation and digitalisation? What role do regulation, education, and innovation play in steering global shipping toward a greener future?

In this edition of Logistics Business Conversations, host Peter MacLeod, editor of Logistics Business Magazine, welcomes Anna Kaparaki – senior solicitor, DBA researcher in maritime decarbonisation, and Course Director for the MSc Sustainable Maritime Operations at Liverpool John Moores University.
Together, they explore the seismic shift taking place across the maritime industry as it races to meet net-zero targets, comply with evolving international regulations, and embrace the circular economy.

In this episode, you’ll discover:

• How emerging technologies like AI, IoT, and digital twins are enabling greener, more efficient maritime operations
• The growing complexity of global and regional sustainability regulations — from IMO frameworks to the EU ETS and FuelEU Maritime
• Why education and training are critical to preparing the next generation of maritime professionals
• Real-world decarbonisation case studies, from wind-assisted propulsion to methanol-fueled container ships
• Strategies for implementing circular economy principles and sustainable ship recycling
• The impact of international maritime law and insurance on green compliance
• Career opportunities in ESG compliance, green finance, and maritime sustainability management
• The role of ports, intermodal systems, and digital platforms in building more resilient, lower-carbon supply chains

As Anna says, “Technology alone won’t solve these challenges. We need professionals who can integrate technical, legal and commercial knowledge to lead maritime’s sustainable transition.”
Whether you’re a maritime professional, policy expert, student, or logistics leader, this conversation offers practical insights into the challenges and opportunities shaping the shipping industry’s net-zero journey.

Listen now: Logistics Business Conversations – The Logistics Podcast

This episode is in partnership with Lloyd’s Maritime Academy and Liverpool John Moores University

The post Podcast: Sailing Towards Net Zero – Maritime Operations appeared first on Logistics Business.

Synopsis:

In this webinar Steven Timberlake of Infios discusses how you can measure your organisation’s level of supply chain maturity and the steps involved in developing greater efficiency and resilience in today’s challenging environment. Together with Peter MacLeod, Steven will explore topics including artificial intelligence, automation and system modernisation and outline how they form part of the practical steps that any organisation can implement today to relentlessly improve supply chain performance tomorrow.

Steven Timberlake, Infios

Steven Timberlake provides thought leadership and strategic challenge around supply chain execution as the Vice President of Sales Northern Europe at Infios. In his role, Steven plays a pivotal role in consulting businesses on transforming their supply chain execution, leveraging his extensive experience to drive strategic initiatives and foster growth opportunities. With over two decades of experience in technology and supply chain, Steven has established himself as a strategic leader adept at driving growth for his customers. His innovative approach to enterprise engagement has enabled organisations to navigate complex challenges and achieve sustainable success in today’s dynamic supply chain environment.

Register to watch it here now

The name Infios draws inspiration from the concept of infinity, representing the vast, interconnected global marketplace and the limitless opportunities to help businesses create their future. Infios is built on the belief that supply chains should be agile, intelligent, and constantly evolving to meet the demands of a changing world. By leveraging advanced technologies, data-driven insights, and a deep understanding of customer needs, Infios delivers innovative solutions that drive efficiency, lower costs, and empower businesses to succeed in an increasingly competitive marketplace.

“Supply chains are the backbone of modern business and global progress. And when they work better — simpler, faster, smarter — businesses thrive, people benefit, and communities become stronger. We believe that the future is better when supply chains work better,” said Ed Auriemma, CEO of Infios. “Our goal at Infios is to work alongside our customers to provide solutions that meet today’s challenges while thinking ahead to solve tomorrow’s problems.”

Infios integrates order management, warehousing and fulfillment and transportation management into a comprehensive suite of solutions, equipping businesses with the tools they need to navigate today’s complex supply chain landscape. Infios is dedicated to its customers, evolving with them to provide scalable, adaptable solutions that meet their changing needs. This flexibility enables customers to optimize every aspect of their operations with versatile, scalable, and future-ready capabilities. With a thoughtful approach to innovation, the company integrates data, predictive analytics, and AI-driven insights to help businesses stay ahead, anticipating challenges and opportunities before they arise.

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Billions of letters, parcels, and shipments are delivered each year. They cross international borders and state lines, spanning languages, cultures, and time zones. These are truly global operations. A melting pot of variables at an almost unimaginable scale. Providing consistently strong customer support under these conditions is extremely challenging. As well as acute seasonal peaks in volumes, there are unpredictable spikes in demand. When even 99.8% of transactions go smoothly, companies still face millions of potential inquiries.

Compounding these challenges, labour shortages in contact centres, alongside rising expectations for rapid, digital-first services, are straining customer service teams. Fragmented TMS, WMS, ERP, and CRM systems hinder end-to-end visibility, slowing time to resolution and frustrating customers and staff alike.

AI helping hand

Multinational shipping firms like DHL are turning to the latest generation of AI assistance for support. With human-like interactions in multiple languages, the ability to complete entire workflows, and the reasoning and autonomy to do so, agentic AI is quickly proving to be an invaluable tool in customer service and support.

Not your everyday chatbot

Agentic AI differs from conventional chatbots in almost every way. Where chatbots run off scripts and keyword identification, the AI agents truly understand language and can readily switch between languages. They accurately identify and respond to key information, even when it’s phrased unusually. For example, a customer might say, “I’m expecting a parcel, and so is my housemate,” to which the agent would confirm, “So, we’re talking about two parcels? Please can you confirm the shipment number or numbers if these were two separate orders?”

But the differences between bots and AI agents don’t just stop there. As well as language comprehension, agents have reason and logic. They apply context and variables to their responses, accounting for things like delivery windows or temporary routing conditions. They hold on to this context, even across long and complex interactions, and can work across channels (chat, voice, messaging apps), ensuring customers get the help where and when they need it.

This logic and reasoning shines when we consider agents are integrated with back-end systems and given executional permissions. Not only do they understand the customer’s goal and have access to their profile and account history, but they can also analyze multiple systems at once, deduce the actions needed to resolve the issue, and then see them through – all autonomously. This is incredibly useful for actions like shipment tracking, delivery changes, and pickup requests.

Seb Glock, Cognigy

Agents are, in fact, proactive in their operations. They actively start and complete workflows without direct human prompting, provided it helps them achieve their goal. So, should a delay in shipping arise, for example, agents could proactively inform customers, confirm new delivery windows, and attempt to find the appropriate workaround. Likewise, they can chase up late payments or send reminders.

Supporting DHL internationally

You can begin to see why DHL adopted such a powerful tool to support its customer service teams. Processing over 15 billion letters and parcels annually, the company’s 0.2% inquiry rate means it still handles over 30 million customer service interactions each year. With an increasingly international customer base with a preference for phone interactions, DHL needed multilingual support across time zones that could handle its colossal scale.

The deployment of its AI voice agent, Paula, has helped the company maintain a high customer satisfaction score of over 80%, lowered operational costs, and reduced response times. Fully integrated with their CRM, SAP, and Salesforce, and providing multichannel, multilingual support, Paula has relieved a significant amount of strain on DHL’s customer service teams. And when inquiries sometimes prove too complex, Paula seamlessly hands over to a human agent.

Benefits at scale

Agentic AI presents a new chapter in customer support services. Offering demonstrable value at scale, shipping and logistics companies are becoming more resilient, efficient, and cost-effective as they continue to deploy AI agents. Human workforces are relieved of repetitive, high-volume inquiries and are able to focus on higher-value interactions. And customers continue to enjoy satisfying interactions, with faster resolution times and fully digital support. The future is agentic.

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Jonah challenges the misconception that AI must be fed a company’s proprietary data to be useful. Instead, he explains that modern generative AI systems can thrive even in messy, incomplete environments, learning patterns and improving performance with limited structure. These AI systems function less like traditional software and more like digital colleagues—adaptive, communicative, and capable of learning from real-world complexity.

This transport management podcast conversation, delves into Trimble’s Transport platform, a multi-party ecosystem connecting shippers, carriers, and retailers. AI plays a pivotal role in helping these parties work together more efficiently, solving shared problems like real-time ETA prediction, theft detection, and enhanced visibility. Jonah offers a compelling example: onboarding new users to the platform, a process that previously required a large team, is now being handled autonomously by AI agents, speeding up operations and freeing up human talent for strategic tasks.

Jonah also outlines a future where logistics professionals evolve into managers of AI teams—overseeing intelligent agents that handle tactical execution while humans guide direction and decision-making. Rather than replacing workers, AI is augmenting their capabilities, enabling smarter decision-making and greater resilience across the supply chain.

This transport management podcast episode offers a realistic and optimistic view of AI’s role in logistics, showing how it’s not only improving business performance but also redefining how people work within the industry. A must-listen for logistics professionals looking to understand how to harness AI for smarter, faster, and more collaborative operations.

Click here to listen

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The partnership, which uses Dexory’s autonomous robot and AI-driven platform, is delivering transformational results across CSG’s Barnsley, South Yorkshire warehouse, which holds a wide range of surplus stock across food, homeware, personal, and pet categories.

Due to the fast-paced nature of surplus redistribution, accurate and timely stock processing is critical. Historically, inaccuracies in stock levels have led to some picking and dispatch delays. By deploying Dexory’s real-time data and automation solution, CSG is now able to track stock with a level of accuracy and speed not previously possible – with an increase of over 300 pallets added to the warehouse management system (WMS) during the trial period alone.

AI-Powered Robotics

“The Dexory solution stood out as the most effective and least disruptive option after reviewing several providers,” said Martin Upton, Operations Director, Company Shop Group. “It’s fast, flexible, and has integrated seamlessly with our existing warehouse management system. The system has also significantly increased visibility into our Dispatch area – something we had limited access to before. This has dramatically increased efficiency and enabled smoother product flow throughout our operation.”

Dexory’s solution is now used not only for stock integrity – ensuring stock is stored in the right location and allowing for rapid issue resolution – but also to support dispatch operations by providing by-date priority lists and real-time views of dispatch pallets. The robot’s ability to perform multiple autonomous scans per day empowers operational teams to act quickly, identify root causes of issues, and implement targeted training and continuous improvement efforts.

“We’re proud to support a mission-led business that is tackling waste reduction across the industry,” said Oana Jinga, Chief Commercial & Product Officer and Co-founder of Dexory. “By combining our AI-powered robotics and real-time data platform, we’re enabling their team to spot issues sooner, react faster, and ultimately deliver a more effective and efficient end-to-end process – turning warehouse visibility into tangible operational and environmental impact.”

Oana Jinga, Dexory

The project has already freed up valuable time for the client’s stock control team, enabling them to focus on wider efficiency initiatives across operations. With the proven benefits in inventory control and process flow, Company Shop Group sees this partnership as a key pillar in achieving its long-term goal: creating a world where no surplus product goes to waste.

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