When tomorrow’s historians map the evolution of the supply chain, they’ll look back on these as pivotal days.
Days when organizations could, at last, understand their complex tapestry of procurement, warehousing, production, logistics, and fulfilment processes. Days when artificial intelligence began helping Supply Chain leaders to proactively and strategically shape operations like never before.
If those historians are also interested in 90s films, they might even compare this era of rapid supply chain transformation to the moment when, finally able to “see” the Matrix, Neo starts properly bending it to his will.
In this article, you’ll learn how artificial intelligence is continuing to supercharge supply chain planning and execution – and why the next few years are set to be even more exciting, as the technology grants Supply Chain leaders powerful new abilities, and an even more central role in driving their organizations’ success.
- Want a primer on supply chain transformation? Check out our guide.
How AI continues to transform the supply chain
1 - End-to-end supply chain visibility
Supply Chain AI is booming. The global market is expected to grow by over 30%, year-on-year, until 2030. And for many businesses, the adoption of AI is being facilitated by AI itself.
Every supply chain is essentially one mega process, built from many micro ones. Artificial intelligence – using data from each individual micro process, and information about how they interact – is now helping organizations to understand the mega process. Or, to put it another way, to create a digital twin of their supply chain and see what’s really going on.
As we’ll explore, this end-to-end, real-time visibility provides the foundation needed to successfully apply AI in countless other ways. But it’s also transformative in itself, allowing for previously hidden problems to be rapidly surfaced and addressed.
A great example? The leading agricultural technology company that, once it had created a digital twin of its processes, was able to effectively identify and fix issues in its master data – and prevent more than 2,000 production stops in just three months.
With AI helping to model the supply chain and granting new operational transparency, organizations can also drive progress towards their ESG objectives. Suddenly, it’s easier to develop and demonstrate ethical sourcing strategies. It’s also easier, especially if you use AI-powered analysis, to optimize logistics operations and delivery routes, reducing your emissions. (And, of course, your fuel costs, too.)
2 - Deeply resilient supply chain operations
Today, being resilient doesn't just mean withstanding supply chain disruptions and recovering fast. AI and generative AI are empowering Supply Chain leaders to reimagine what resilience looks like, and take a much more proactive approach to safeguarding their business-critical operations.
Building on the insight provided by digital twins, AI and generative AI are helping Supply Chain managers to simulate the impact of everything from natural disasters to new trade tariffs. Then, the tech is empowering them to model and evaluate a range of strategic responses, and even suggesting ways to minimize their exposure to the risk.
Let’s take a new tariff as our example. AI can help a Supply Chain manager understand which suppliers and routes the new tariff will affect, suggest alternatives, and even model the time and cost impact of switching to each one.
- Want to dive deeper?
- Read our article on modern tariff management.
- Watch our demo of Celonis for tariff management.
3 - Precision demand forecasting and inventory management
Imagine a global supply chain free from excess inventory and untroubled by stock-outs. It’s a beautiful vision, right? And with AI, it can be your reality.
AI’s gift for analyzing a wide array of data inputs – market trends, weather patterns, competitor pricing, supplier performance, the expected impact of product promotions, and many, many more – is already supporting more accurate demand forecasting and planning.
At the same time, AI is able to sift powerful insights from the vast and varied data streams created by today’s sensor-laden supply chains:
- Identifying issues.
AI is helping to flag everything from emerging bottlenecks to entrenched inefficiencies. McKinsey reports how one company used an AI-powered digital twin to increase warehouse capacity by nearly 10%, without expanding its warehouses at all.
- Surfacing opportunities.
The right machine learning model can help to evaluate supplier performance and determine optimal lead times for material provision. (Which could help you reduce inventory costs, stockouts, and lost sales.)
- Assisting the humans in the supply chain loop.
A global leader in sustainable packaging has created an AI Copilot to help its plant engineers check what spare parts are available at other locations – effectively minimizing unnecessary orders and excess stock.
4 - Supply chain hyperautomation
Ask someone on the street to describe an automated, AI-enabled supply chain, and they might think of warehouses decked out with advanced robotics, where autonomous drones use computer vision to track inventory.
And they wouldn’t be wrong. Almost half (49%) of the Supply Chain leaders surveyed for our 2025 Process Optimization Report are already automating their warehouses with AI. But increasingly, warehouse automation is the tip of the hyperautomation iceberg.
From procurement right through to order management, AI and generative AI are rapidly reducing manual tasks and touches throughout the supply chain. For example:
- AI Agents are helping procurement teams respond to supplier inquiries, simultaneously reducing backlogs and bolstering relationships through timely communications.
- AI is also reviewing blocked customer orders and recommending which should be allowed to proceed – accelerating cash flow, while helping credit managers be more productive.
- AI is automatically ordering stock when inventory levels dip below replenishment thresholds, and keeping production flowing smoothly.
- Fuzzy matching is identifying duplicate supplier, master data, and customer records, streamlining operations and engagement.
The AI-enabled, hyperautomated, autonomous supply chain of the future is arriving fast. Gartner predicts that, within the next five years, half of all cross-functional supply chain management solutions will use intelligent agents to execute decisions autonomously.