The turbulence of the last few years has been challenging for the logistics industry more than most others. From the sudden and lasting disruption of the COVID-19 pandemic, through the grounding of the Ever Given container ship that blocked the Suez Canal, to the effect of ongoing conflicts around the world, there has been a lot for logistics businesses to deal with in a very short space of time.
However, the industry as a whole has proven resilient through these headwinds - and now finds itself in a strong position to grow and innovate, especially as new consumer demands are delivering new opportunities. Artificial intelligence is a central part of that drive to innovate, and is helping logistics organizations revolutionize their supply chains, make more informed and proactive decisions, and operate at a level of efficiency far beyond what was previously possible.
But how does all this new technology work in practice?
How to use AI in logistics
As AI is relatively new technology in mainstream terms, the use cases for it in the logistics industry are emerging and gaining traction at a rapid rate of knots. However, at the time of writing, it’s already being widely used in four key areas:
1. Workflow management
AI is proving transformative in streamlining operations in a wide range of different workflows throughout the supply chain. This can include the management of inventory, and order processing, ensuring that goods move smoothly from initial manufacture all the way through to customer receipt. All of these improved workflows come together to reduce costs, boost speed and efficiency, and enhance the overall customer experience.
2. Stock control
AI is enabling stock control to shift from a reactive approach towards a proactive one. By using predictive analytics and AI-driven forecasting, logistics firms can ensure that any gaps in stock are covered before they can even emerge, whether that’s on the shelves or in the distribution center. Adjusting for peaks and troughs in demand, and monitoring availability in real-time, can ensure that the right amounts of stock are always in the right places at the right times.
3. Customer service
Many typical customer service issues arise for logistics companies when the information that service agents have to hand is inconsistent, inaccurate, out of date or simply unavailable. AI can resolve all of these problems by updating customer case information in real time and ensuring that the agent has all relevant details to hand, enabling speedy and satisfactory resolutions of issues when they arise.
4. Training
Logistics operations can be tricky for new hires to get up to speed with, and on top of that, there are also new products and services to learn about all the time. AI eases the process of onboarding and on-the-job training, through monitoring of working performance and pinpointing of areas where the biggest improvements in skills and knowledge can be made. AI agents can also help fill in the expertise gaps through calling on the latest product information, and making it accessible for agents answering customer queries.
How AI can help prevent supply chain disruptions
AI is going beyond enabling some very good things for logistics businesses - it’s also playing a leading role in preventing some bad things happening too. In particular, it’s working on many fronts to minimize the supply chain disruption that can be so damaging to revenue, morale, customer experience and brand reputation:
Risk identification
As well as pointing out potential efficiencies, AI can also be used to identify potential risks before they can cause operational disruption. Through detailed analysis of customer and supplier data, as well as real-time monitoring of wider metrics and data points, anything that could have an impact can immediately be flagged. This gives logistics teams more vital time to respond and put alternative measures in place to minimize the effect of any problems.
Resource management
Connected to the previous point, AI can help with practical and appropriate advice around the measures required to minimize the impact of disruption. AI can go as far as simulating different strategies, from adjusting inventory levels or changing suppliers to exploring alternative shipping routes, and work out which is the most realistic and viable prospect. This can be conducted in a very short space of time to enable rapid response.
Insight generation
Real-time monitoring and tracking of products, whether being shipped by the pallet-load or delivered individually to customers, means GenAI gives logistics businesses vital visibility into supply chain performance. Not only can this help them spot issues with their own parts of the chain, but it also helps them get insights into areas where some of their direct or even indirect suppliers may be struggling.
Smarter decision-making
All of the insights, visibility and analytics in the above points can come together to support real data-driven decision-making throughout a logistics enterprise. Supply chain managers can make faster and better choices based on having more detailed and up-to-date information to hand, which supports better outcomes in the short-term and the long-term.
How to unlock the power of AI for business evolution
AI offers huge benefits for the logistics industry, making operations smoother, faster, and more efficient. But to get these benefits, businesses need experts who can provide the right AI solutions.
AI improves workflow management, stock control, customer service, and employee training. With predictive analytics, AI helps businesses manage stock proactively, reducing shortages and meeting customer demands. It also provides real-time updates to customer service agents, solving issues quickly and improving satisfaction. AI supports employee training by identifying skill gaps and providing resources to improve.
To fully benefit from AI, businesses need to work with experts like Ciklum. We understand the logistics industry and can deliver customized AI solutions. We ensure our AI deployments are ethical, transparent, and fair, building trust among employees and customers. We also provide training to help employees use AI effectively.
How to prepare your business for AI
You may be in a position where you haven’t yet adopted AI in a widespread fashion - or your business has dipped its toe in the water and experimented. In either of these scenarios, it can be difficult to understand how to make the transition to a logistics and/or supply chain where the benefits of AI are embedded through every part of the process. It’s for these reasons we recommend the following five steps as a means of understanding what your business needs from AI, and how you can get there:
1. Identify skill and knowledge gaps
Start with a comprehensive assessment of the current capabilities of your workforce, and benchmark those capabilities against the skills needed to effectively leverage AI. Common areas where gaps exist include (and are not necessarily limited to) data literacy, machine learning, software development and AI project management, but could also extend into workflow management and data.
2. Establish ethical guidelines
The ethical use of AI should be a top priority, and will only become more important in the months and years to come. Clear ethical guidelines and governance frameworks for how AI is used are essential, so that platforms are deployed transparently and responsibly. This should help ensure data privacy, accountability and fairness in AI deployments, helping to build trust and confidence in employees and customers alike.
3. Integrate AI into existing workflows
The introduction of AI tools and solutions into existing workflows should be gradual, so that the change isn’t too disruptive. Employees should have a central and vocal role throughout the change, so that their feedback is taken on board, and improvements and adjustments can be made during the process rather than after it.
4. Reskill and upskill employees
AI represents a major departure from the technology skills and expertise that many employees will be used to. Alongside any AI deployment should be a retraining and upskilling program that ensures all relevant staff have the knowledge they need to get the most from AI technology. This can include personalized training plans, hands-on experiences, and opportunities to proactively get involved with AI projects.
5. Collaborate with tech partners
Working with expert technology partners, vendors and service providers can help ensure that you have all the knowledge and technology you need to make your AI deployments successful. If you don’t feel that your existing partnerships can deliver on your objectives, then now is the time to explore new options, especially around experts in AI and Conversational AI, Machine Learning, Process Automation and Experience Design. Learn more about the Ciklum approach to AI here
