Clare Bottle, Chief Executive of the UK Warehousing Association (UKWA), was recently a panellist on a webinar, hosted by Linde Material Handling, entitled “Putting the AI into intralogistics’. Here Clare looks at the big prize presented by AI for this pivotal area of the supply chain.

The potential of AI in intralogistics is enormous and will, when it’s adopted universally, change the face of warehouse management through its dramatic impact on areas such as forecasting, routing, maintenance, planning and training – and even the interactivity of the human workforce with their robot colleagues!

Specifically, I see seven big opportunities emerging as follows:

1. Better forecasting in areas such as energy use, consumer demand and labour needs

AI has the ability to greatly enhance forecasting in intralogistics by leveraging machine learning algorithms to analyse historical data, real-time inputs, and market trends. This allows for highly accurate predictions around demand to optimise inventory levels and reduce the risk of stockouts or overstocking; labour resource requirements to ensure there is the right amount of staff to do the job in hand; and energy use to calculate related costs for financial management purposes. AI can detect patterns and issues that traditional methods might miss, enabling proactive adjustments in supply chain and associated operational strategies.

2. Route optimisation - from AI’s ability to come up with the best movement paths around the warehouse; to working out the best routes into and out of the warehouse based on a range of external factors.

AI enhances route optimisation within a warehouse by analysing real-time data on inventory locations, order priorities, and worker or robot movements. Machine learning algorithms determine the most efficient paths for picking, packing, and replenishment tasks, minimising travel distance and time. AI can dynamically adjust routes in response to changing conditions, such as new orders or hindrances, ensuring that operations remain smooth and efficient. By optimising these internal routes, AI reduces internal transportation issues, accelerates order processing, and increases overall productivity, leading to faster fulfilment times and reduced operational costs in warehouse management

In addition, AI supports route optimisation into and out of the warehouse by analysing vast amounts of data, such as traffic conditions, delivery windows, and vehicle capacities, to determine the most efficient transportation routes. Machine learning algorithms continuously learn from historical and real-time data to adapt routes, minimising fuel consumption, travel time, and operational costs. AI can also account for variables like weather, road closures, or customer preferences, ensuring that deliveries are timely and efficient. By optimising routes, AI enhances logistics efficiency, reduces environmental impact, and improves customer satisfaction through more reliable and faster supply chain.

3. Proactive maintenance to avoid costly breakdowns inside the warehouse

AI can support predictive maintenance both inside and outside the warehouse by analysing and interpreting data from sensors on equipment, such as forklifts, machinery and the fabric of the warehouse itself, to proactively predict potential failures before they occur. By processing real-time and historical data, machine learning can identify patterns and issues that raise red flags on wear and tear and signify potentially imminent malfunctions. This allows for proactive maintenance, reducing downtime and extending the lifespan of assets. Maintenance can then be scheduled during non-peak times to avoid disruptions.

4. The opportunities presented by AI integrated cameras

AI integrated with camera hardware – supported by computer vision technology that allows information to be extracted from barcodes, videos, digital images and other visual inputs – enhances warehouse management by providing real-time monitoring and analytics. AI-driven cameras can track inventory levels, detect misplaced items, and monitor the movement of goods and personnel. These systems can identify inefficiencies, such as bottlenecks, enabling speedy and corrective actions.

It can also alert health and safety teams to potential safety hazards, such as high-risk pedestrian collision points, overloaded shelves or equipment malfunctions, and for them to take necessary up-front actions.

5. The creation of more sophisticated digital twins for enhanced scenario planning and training

AI has the potential to significantly enhance the benefits of digital twins in a warehousing environment. AI-powered digital twins can simulate warehouse operations, allowing for scenario testing and identifying inefficiencies before implementing changes in the physical environment. This enables dynamic adjustments in layout, inventory management, and workflow processes based on real-time conditions and predictions. AI can also help digital twins learn from historical data to improve accuracy in forecasting demand, equipment maintenance, and resource allocation.

Finally, AI digital twins can be used to provide low risk training where failure doesn’t matter, for example through workers wearing headsets to drive a virtual forklift truck before they operate a real one.

6. Enhancing the human interface with AI

In time supply chain leaders will be able to use AI like we all do with Siri or Alexa to get simple answers in human language to questions on specific intralogistics matters, for example: “Can we fit this new customer in?” or “How can we make this new warehouse safer?"

7. Getting robots to do more

As AI develops it will become smart enough to allow robots to do more jobs, for example to work in hazardous and/or low and high temperature environments. It will also enable robots to recognise shapes of objects helping to improve their ability to pick different products and fulfil orders.

Whilst the take up of AI in the warehouse is currently a mixed picture, it is undoubtedly the future for intralogistics, as reflected by UKWA members like DHL and Wincanton who both have dedicated innovation centres so their businesses can tap into developments in this field and beyond.