Digitisation is transforming supply chain management, bringing a new level of intelligence and insight to the logistics sector. Traditionally a manual and labour-intensive industry, logistics has relied on physical processes, paper-based systems, and reactive decision-making. However technology is now at the heart of supply chain operations—driving smarter planning, faster delivery, and more resilient systems.
As global supply chains grow increasingly complex, and customer expectations continue to rise, embracing digitisation is key. In this feature, we explore how intelligent logistics is shaping the future of supply chain management, the technologies making the biggest impact, and the challenges businesses face as they navigate this digital transformation.
Enhancing supply chain efficiency through warehouse automation
The use of warehouse automation is growing by more than 10 per cent per year. With its potential to increase speed, reliability, and productivity, it offers companies a significant competitive advantage. But, with so many automated solutions available, where should companies invest?
Physical warehouse automation leverages technology to streamline key processes such as the handling and movement of goods. This can range from basic systems like carousels and conveyors to fully robotic solutions to automate repetitive tasks such as picking and packing. These technologies not only improve warehouse efficiency by reducing human error but also allow staff to focus on higher-value activities.
Even before goods arrive at a facility, automation is being used to optimise space planning, and create efficient picking routes and warehouse layouts. Automated storage and retrieval systems (AS/RS) use data-driven insights to map optimal storage locations, organising items by type and access frequency. By using robots to move and retrieve goods, they can also make use of vertical stacking methods to significantly improve storage capacity.
As technology becomes more scalable, it’s becoming accessible to a broader range of customers. In our Thought Starters series, Rosalind Shinkle, CEO and Co-founder of Adagy Robotics, notes that this shift creates new opportunities for small and mid-sized logistics companies to grow and leverage robotics in innovative ways.
“In the past, you needed scale to be able to take advantage of this type of automation. In the future, with more flexible robots, you will be able to start with one robot and get value out of that one robot. Then, you can add in another robot when you see the capability coming in for the labour that you need.”
How AI is revolutionising supply chain management
AI and machine learning are transforming demand forecasting, making predictions more accurate and supply chain processes more efficient. With models that can rapidly analyse vast amounts of complex data – including external variables like weather patterns, regional events, and consumer trends – businesses can better anticipate what products will be needed and when, helping to align supply with demand more effectively and fulfil orders at high speed.
But it doesn’t stop there – this technology also plays a crucial role in ongoing supply chain management. AI-powered systems can monitor inventory levels and sales data in real time, enabling smarter decisions about stock allocation. The ability to automate reordering processes reduces the risk of running out of product or overstocking, helping companies lower overheads, reduce delivery delays, and ultimately improve customer satisfaction.
The role of route optimisation in reducing supply chain emissions
Transport alone is responsible for 37% of global carbon emissions. However technology is significantly enhancing route optimisation in supply chain management, a process that traditionally relied on manual planning and often resulted in inefficiency and increased costs. While Global Positioning Systems (GPS) can track movements in real time and respond to changes and potential disruptions, AI is now being used to generate the most efficient delivery routes. By analysing factors such as traffic patterns, road conditions, and fuel consumption, AI is helping to minimise travel time, reduce emissions, and optimise overall fuel efficiency in supply chain operations.
Tackling barriers to the technology transformation
Technology such as AI, machine learning, and warehouse robotics is revolutionising supply chain management, but its adoption does not come without challenges. These include:
- Cost – New automated systems can be expensive to purchase and maintain. However, as technology becomes more accessible, costs are steadily decreasing. AI is also driving the development of multi-purpose robots that can adapt to different tasks, offering a better return on investment.
- Integration – Many logistics businesses already have long-established supply chain management systems and processes in place. As a result, integrating new automated solutions can be complex and requires careful planning and coordination.
- Talent and skills – There is a shortage of skilled professionals in areas like warehouse robotics and machine learning. This requires businesses to invest in specialist training to upskill existing employees if they are to successfully implement and maintain these new technologies.
Building smarter futures
Intelligent logistics is redefining supply chain management. From AI-powered forecasting to automated warehouses, technology is helping businesses become faster, more agile, and better equipped to meet growing consumer demands.
While challenges like cost, integration, and skills gaps remain, the long-term benefits of investing in smart solutions are hard to ignore. As technology continues to evolve and become more accessible, businesses of all sizes have an opportunity to scale at pace and create more resilient and responsive supply chains.
