Discover how AI is changing the way the supply chain works. From route planning to trends in sales, this tool can be used to drive business in turbulent times
The supply chain is the lifeblood of trade. From everyday haulage to global shipping lanes, the systems that connect suppliers to manufacturers, manufacturers to sellers, and sellers to customers are complex and ever present.
This complexity leads to an often conservative approach to change as businesses want to stick with what works, instead of testing out new systems. However, this mindset is one that looks to be changing as more and more businesses experiment with intelligent automation and generative AI to create more sustainable, robust, and efficient systems.
Trade is in transition
The root of this shift lies in what the Economist describes as the ‘new era of globalisation’. In their report titled Trade in Transition 2025: Balancing optimism with caution (led by Economist Impact and supported by DP World); the Economist highlights the way in which the supply chain is bracing itself for more protectionism from nations which may lead to greater turbulence as tariffs, embargos, and other action disrupt activity.
This is leading to businesses changing their businesses in several key ways with respondents to the report citing;
- Increase US sourcing - 40%
- Reduce internal costs - 33%
- Adjust supply-chain networks and strategies - 31%
- Increase advocacy efforts - 26%
- Invest in expanding US manufacturing capacity - 21%
These strategies require a two-fold solution, one that makes their business more resilient to geopolitical change and saves on any excess. Many western firms, as a result, have started to develop dual supply chains that can be increased or decreased depending on which way the wind blows. One supply chain tied to China and her lucrative markets, and one independent supply chain to be used if the tides change.
This has led to more non-aligned countries entering the fray as businesses plan routes, storage, and sources with countries like Mexico, Vietnam, and the UAE. All with the goal of making systems more robust and immune to political shifts.
This change is certainly an interesting one, for politicos, but creates a massive headache for logistics companies who have to navigate uncharted waters. Regulatory inconsistencies, route planning, a maze of shifting routes, the complex digital supply chain has become even more complex, and requires smarter tools to solve issues. This is where AI technology can shine.
Technology as a tool for change
Generative AI is not a new concept and has been the subject of newspaper headlines for the entirety of 2024. However, this technology is still being learned and understood with most people only having a vague understanding of what it can do.
At its core, the excitement around AI and machine learning (ML) is based on its potential, as it highlights the next step in the development of computing. But how does artificial intelligence (AI) work in the supply chain? And what does it mean for SMEs, multinational companies, and consumers?
How does AI in the supply chain work?
Generative AI and automation are currently used in tandem to make smarter decisions and improve efficiency through faster and more intuitive calculations. This means whether in route planning, ordering materials, onboarding new employees, or managing customers, automation tools (powered by AI) are being used in different ways for efficiency, cost, or robustness.
Along with the above areas, the supply chain is also using AI for forecasting and automating equipment maintenance schedules.
Obstacles facing artificial intelligence in the supply chain
However, it is not all plain sailing for anyone considering introducing AI into their operations. Currently, AI is still limited in its functionality and is not the panacea everyone assumes it to be. It is a tool and not a solution.
Next is the cost that comes with implementing change. Digital supply chain technology can often lag behind other industries as the ‘always on’ nature of the supply chain means there is no downtime to change systems. Similarly, the cost of updating legacy systems can be a limiting factor, especially if it needs buy-in from stakeholders.
Finally, AI is a tool and not a solution meaning that businesses need to be wary about overreliance. AI tools are constantly learning and can make mistakes so ensuring human oversight and control is still a key obstacle that needs to be considered.
AI in action
To overcome this, many businesses choose to automate one area of their company first as a test case. Doing so can show how easily systems can be overhauled and lead to further optimisation. Here are a few examples of companies that have successfully used generative AI to make their systems more robust and effective.
BMW - Digital twins
BMW partnered with Nvidia to create an AI-driven solution that simulated aspects of their factory in a virtual model. Doing so, allowed their team to test and augment their production lines changing anything from collaborating on model production to orchestrating robots and machines in their factories.
This freedom to test without affecting real-life systems freed up R&D teams to focus on optimisations and only bring forward changes that could be implemented efficiently and effectively.
Poloplast - Demand planning and forecasting
Poloplast changed the way their team planned and forecasted material orders. Historically, the team would meet once a month with a spreadsheet and toiled to inform how much raw material they needed for the next three months.
This rigidity didn’t allow for smaller fluctuations in the market and had the added issue of fragmenting their resource planning from the demand meeting. To overcome this, Poloplast worked with Microsoft, implementing Microsoft Dynamics 365 Supply Chain Management, to break down the barriers between departments, allowing a more holistic approach to the operation.
This in turn, allows for more agile decision-making as real-time data analysis and AI-driven advice which ultimately led to;
“...less wasteful ordering and less stock, but we are still delivering the same service level to our customers.” Siegfried Wögerbauer, Head of Supply Chain Management and Sales Logistics at Poloplast
Emerson - Supply chain robustness
Finally, we have Emerson who used ““Oracle Transportation Management and Fusion Data Intelligence Platform [to] really helped us with customer service by improving our on-time delivery.”
This came from a direct need for improved control, something that is critical in today’s geo-political climate. This want for control extended from more visibility in which transport providers were carrying more of a certain type of freight to freight consolidation to reduce costs and carbon emissions.
Emerson needed to integrate a lot of raw data into one place and Oracle Transportation Management based on their Fusion Data Intelligence Platform, allowed them to do exactly that. Teams can dig into the data and find solutions quicker. This has been especially useful for issues like natural disasters or global pandemics.
To quote Oracle on the breadth of an intelligent solution;
“This agility proved especially useful during the pandemic, when the company used Oracle Transpiration Management to consolidate freight into charters coming out of China and into the US for domestic distribution. Emerson effectively expanded this consolidation strategy since then. In another instance, it relied on Transportation Management to reroute freight after volcanoes erupted in Iceland, disrupting air transport.”
AI at Multimodal 2025
As you can see, the need for generative AI solutions has grown as the geopolitical landscape shifts. Whether it’s creating multiple supply chains to account for the changing whims of political leaders or a drive to become more competitive and sustainable in modern business, many view AI-powered digital solutions as a must.
For our part, we believe that showcasing AI helps inform and empower you to make the best decisions. That’s why at Multimodal 2025 we are pleased to offer a wide range of talks and presentations on this topic including;
How Artificial Intelligence is transforming Multimodal logistics
In this session, the panel will explore the impact of Artificial Intelligence (AI) on multimodal logistics, focusing on how AI is optimising planning, route selection, real-time tracking, and inventory management.
- Chair: Samantha Brocklehurst, Customer Experience Director – UK & Ireland, Maersk
- Dawn Rasmussen, CEO, Problems Solved
- James Coombes, CEO, Raft
- Eyal Goldberg, CEO, Breeze
- Adnan Zaheer, CEO, iCustoms
Boost your productivity with AI
This course introduces learners to cutting-edge AI tools that are already available from Google and others, to show some of the smartest ways digital-age workers, and small businesses can use them to save time at work and on tasks.
- Kirstie Kavanagh – Upskill Universe Digital Trainer
- Glenn White - Upskill Universe Digital Trainer
AI Agents: The Game-Changer in Trade Compliance
AI agents are transforming trade compliance by automating complex processes, reducing human input, and ensuring faster, more accurate submissions. Learn more about AI and its place in compliance and customs.
Drive your logistics business using Microsoft D365 eco-system and the Power of AI
The presentation will showcase how logistics service providers including 3PL businesses can harness the potential of Microsoft Dynamics 365 eco-system and its powerful suite of products.
- Jay Tahasildar, Founder & Managing Director, Mercurius IT
Sign up for Multimodal 2025 today
These talks along with others are sure to address any concerns or questions you may have about AI in the supply chain. If you’re interested in finding out more, please don’t hesitate to register today for the UK’s premier logistics and supply chain expo.
This event is one of the biggest in the UK and provides a wealth of opportunities to learn, network, and grow your business. Find out more about this year’s event here and get ready to revolutionise the way you do business
