The Importance of Leveraging AI & Machine Learning in Order Management
Ever wondered how retailers always seem to know what’s in stock? You might already have a glimpse into the quiet revolution happening behind the scenes, well beyond the age of spreadsheets.
Today, artificial intelligence (AI) and machine learning (ML) are driving transformation and reshaping how goods move from your warehouse to customers’ doorsteps. But what’s behind this shift, and why are so many businesses investing heavily in these technologies?
We’ll explore the role that ML and AI can play in order management, as well as go through a couple of examples from organisations that have been using these technologies for decades.
AI's Role in Modern Supply Chains
Let’s start with a simple fact: supply chains are always evolving. Their complexity isn’t going away anytime soon.
Customers expect next-day delivery, real-time updates, and seamless service across every channel. Meeting these expectations with traditional, manual systems and processes is a tall order due to the demanding nature of ecommerce.
That’s why, according to a recent Gartner survey, 40% of high-performing supply chain organisations are using AI and ML for demand forecasting. That’s more than double the rate of their lower-performing peers, and it’s not just about keeping up with the competition.
The global AI in supply chain market was valued at $4.5 billion in 2024, and it’s projected to grow at an eye-watering 42.7% compound annual growth rate. Clearly, companies see AI as a game-changer for efficiency and resilience and that’s why investment is accelerating.
The Access Group (Mintsoft’s proprietary owners) conducted their own research and found that 82% of businesses polled stated that AI helps them produce better work, a testament to the technology's transformative potential.
Half of supply chain leaders plan to implement generative AI (GenAI) in the next year, with chief supply chain officers (CSCOs) allocating, on average, 5.8% of their budgets to GenAI in 2024. It’s rare to see such rapid and widespread adoption of any technology, which tells you just how much is at stake.
AI isn’t just a bolt-on feature; it’s woven into every stage of the supply chain. From procurement and warehouse management to last-mile delivery, AI is enabling a level of visibility and responsiveness that would have been unthinkable a decade ago.
Case in point: Amazon. Their fulfilment centres are a hive of activity, with AI-assisted robots fetching items for humans. Computer vision systems scan barcodes and sort goods, while predictive models help anticipate order surges. This blend of robotics and AI means Amazon can process millions of orders daily, with remarkable speed and accuracy.
Zara is another compelling example. Their AI-driven systems monitor sales in real time and can shift inventory between stores at the drop of a hat. If a particular style is flying off the shelves in Manchester but languishing in Leeds, AI spots the trend and triggers a transfer, ensuring stock is always where it’s needed most.
Walmart’s Alphabot system is yet another example. Here, robots pick and pack grocery orders, which are then checked by human staff. This hybrid approach has doubled processing volumes and improved both staff satisfaction and customer experience.
While these examples are at the more intense end of using AI to fulfil customer’s orders, they’re no longer outliers, as more and more businesses adopt the technology.
Key Benefits of AI in Order Management
Utilising AI in order management has plenty of positive implications for your business. Let’s break down the core benefits.
Automation of Workflows
AI takes over repetitive tasks such as order entry, data validation, and notifications. Imagine a system that scans incoming emails, extracts order details, checks stock, and sends confirmations.
Being able to increase stock levels to prepare for demand can allow warehouses to be ready for fluctuations and avoid waiting for stock deliveries. Read more about AI in order management here.
What does this get you? Orders are processed faster, errors are slashed, and staff can focus on more valuable work.
Demand Forecasting Optimisation
One of the standout uses for AI is predicting what customers want and when they expect to receive it. Machine learning models digest historical sales, market trends, weather data, and even social media buzz to forecast demand. This helps maintain optimal inventory levels and reduces stockouts/overstock.
Reduction of Human Errors
Manual processes are prone to mistakes like miskeyed orders, mismatched inventory, and missed shipments. AI-driven systems catch anomalies instantly. For example, if an order doesn’t match available stock or a delivery address looks off, the system flags it before it becomes a costly problem.
Real-Time Inventory Tracking
According to McKinsey, companies using AI-driven inventory tools have managed to cut inventory levels by up to 35% while still improving service levels by 65%.
IoT sensors and predictive analytics show businesses exactly what’s in their stock, where it’s located, and how fast (or not) items are moving. This real-time visibility becomes extra useful for omnichannel retailers juggling online and in-store sales.
Seamless Order Fulfilment
Not only can AI pick and pack orders, it also optimises the entire fulfilment process on your behalf. From choosing the best warehouse to fulfil each order to plotting the most efficient delivery routes, AI ensures goods get to customers quickly and cost-effectively. Robotics and smart logistics tools, like those in Amazon and Walmart’s warehouses, are now standard for high-volume retailers.
Improved Customer Satisfaction
It’s all of these improvements that add up to help you deliver a better experience for customers:
- Orders arrive faster and more reliably
- Chatbots provide instant answers to customer queries
- Real-time updates keep customers in the loop
- Personalised recommendations make shopping feel more tailored and engaging
Case Studies of AI Implementation
Order management tools are increasingly relying on AI as a normal part of their product function to bring these benefits to their customers. Let’s look at a few more examples to see how these benefits play out in practice, including companies that used Mintsoft for this transformation.
Mintsoft & Fulfillable: Automation That Drives Real Results
When Fulfillable, a growing fulfilment business, set out to expand its automated offerings, it turned to Mintsoft’s order management platform. The results have been impressive:
- Manual processes slashed: Tedious tasks like invoicing, which previously took up to two days per month, are now fully automated.
- Accuracy transformed: Mintsoft’s barcode scanning app ensures every order is picked correctly, virtually eliminating inventory errors and customer complaints.
- Professional platform: Fulfillable now offers a white-labelled, client-friendly portal with over 150 integrations, supporting seamless onboarding and customer transparency.
“Lots of time was spent on manual processes which Mintsoft has now allowed us to automate. Our ethos is to automate as much as we can, so that we can reduce expenses by streamlining our operations where we can. Mintsoft has allowed us to do that.”
Ben Chidzoy, Co-founder of Fulfillable
Walmart: Predictive Analytics at Scale
Walmart uses AI and machine learning for everything from inventory management to supply chain optimisation. All this with predictive analytics tools forecasting demand, automating replenishment, and even optimising delivery routes.
During peak seasons, Walmart staff can ensure shelves are well-stocked and customers get what they need, when they need it. This further helps them reduce stockouts and keep inventory costs in check (even lower them).
DHL: Smarter, Faster Logistics
DHL was also one of the earliest adopters of AI, using it for routing, tracking, and forecasting. Their custom machine learning models analyse traffic, weather, and demand to suggest the most efficient delivery routes.
This improves operational efficiency, reduces delivery times, and guarantees a better customer experience. Plus, AI-driven insights have played a fundamental role in helping DHL maintain its competitive edge for so many years.
ML/AI Challenges and Considerations
Adopting AI doesn’t come without its own set of hurdles. Here are a few to keep in mind before full-scale AI adoption:
Integration Challenges
Many organisations are still using legacy software; those systems, while sometimes they "philosophically" fit AI, really don't always integrate with modern AI components as easily. Also, incorporating such systems can be complicated and laborious as you try and tie them together, and that's required simply to tap into the real capabilities AI can provide.
Adaptability to Changing Technologies
AI and ML are still developing. Organisations must invest deeply, not only in learning, but also have to use IT systems that allow for agile, nimble, and flexible organisations that adapt to the developments.
Generative AI means that both new opportunities and new risks are likely. Implementing AI is not cheap, and that can mean both technology costs and the cost of re-skilling staff in the AI-ised world. Change management is highly important as well. Staff must understand how AI will change their role, and how they can work with the inevitable change that technology will encourage.
Data Privacy and Security Concerns
AI performance is determined by the data it uses. With poor data quality, you’ll have poor decision-making. Identifying and handling sensitive customer data raises privacy and compliance issues.
The regulations imposed on businesses, such as the GDPR, require you to be clear about the decision-making of AI, and ensure that you protect personal data every step of the way. Using Open AI tools isn’t an option when you’re handling the sensitive personal data of your customers.
The Long-Term Implications of ML and AI for Businesses
Looking ahead, the impact of AI and ML on order management will only deepen. Here’s what to expect:
- Scalability: AI allows for more orders to be processed without the equivalent increase in costs. When processing 50 orders or 5,000 orders daily, AI is scalable.
- Cost savings: Automating processes reduces staff requirements, redundancies, and returns. Smart procurement and inventory management also lower costs.
- Personalised inventory management: AI can look at how customers behave, allowing businesses to plan and fulfil inventory needs, improving service levels, and reducing waste.
- Workforce evolution: Since repetitive tasks can be automated through AI, workers will first need to complete higher-value work. This labour evolution will require re-training and a willingness to change, but will also create new labour opportunities.
AI and machine learning capabilities have transitioned from being the future of order management to quickly becoming the linchpin of order management.
Companies are investing billions of dollars, allocating almost 30% of their budget to GenAI, while at the same time achieving record gains in efficiency, accuracy, and customer satisfaction.
The largest players in ecommerce are already distinguishing themselves among competitors and, with AI, are unlocking fundamentally higher levels of productivity and service.
For smaller businesses, the opportunities to get ahead with AI are real, but competitors are likely moving fast and exploring the same options.
AI with Mintsoft
Mintsoft’s automation capabilities make order management a breeze. From the moment an order is placed, automation can take over to process through to picking, and again through to shipping to the consumer. In addition, Mintsoft’s AI capabilities include an AI digital assistant – Copilot, to securely query data through conversational prompts, helping to provide actionable insights to further your business decisions.
If you'd like to see these in operation and find out how Mintsoft's AI-enabled order and warehouse management technology can help your business streamline processes, reduce costs, and keep customers happy from round one. Book your demo now and see how the future of order management can work for you.