Introduction
Artificial intelligence (AI) is no longer a futuristic concept – it’s business reality. And yet, while many organizations are already experimenting, 70% are seeing only limited impact from their AI initiatives, according to a recent study. So, what’s going wrong – and how can ambitious AI projects be turned into measurable business success?
In global supply chains, AI has the potential to be a true game-changer. Companies face pressure from volatile demand, fluctuating raw material costs, and growing sustainability requirements. Those who act early and integrate AI gain a strategic advantage – through greater efficiency, transparency, and resilience.
This article highlights real-world examples of how AI is transforming not only processes, but also mindsets in supply chain operations.
Definition
Forecasts on demand, inventory, or risks often depend on countless variables and are not always a 100% accurate. AI can identify patterns, assess scenarios more reliably, and significantly increase planning accuracy.
Where exceptions are the rule, classic automation hits its limits. AI adapts flexibly – whether in supplier selection, HR processes, or content translation.
Global supply chains involve thousands of partners. While EDI is standard, emails and PDFs with critical information still dominate. AI-powered Intelligent Document Processing (IDP) using Large Language Models (LLMs) can systematically unlock these untapped data sources.
AI integration is already delivering tangible improvements across planning, logistics, and operations. These four examples show how companies are turning AI into business value:
Example: Freight invoice automation: Many logistics providers, especially smaller ones, don’t send invoices via EDI but as PDF attachments. AI can fully automate this process: Communication Mining identifies the email context as an invoice. Document Understanding extracts relevant fields like amount, freight reference, carrier name, and delivery date.
These are validated against backend data in systems like SAP Transportation Management (SAP TM). If everything matches the pre-approved freight rate, the invoice is auto-approved and forwarded for payment. If not, a dispute case is opened.
Outcome: Fully automated data processing, reduced errors, and real-time updates in cost or sustainability KPIs. When SAP TM is well-prepared, AI can turn these processes into a seamless flow.
This change enabled the company to automate and objectify forecasts and at the same time utilise resources more efficiently.
Results:
As soon as a truck approached the site:
Benefits: AI helped the company achieve shorter turnaround times and better dock utilisation. Morever, there were fewer bottlenecks and delays enabling a smoother transition to outbound logistics.
Early signs of wear or defects are flagged instantly, enabling:
As a result, logistics operations are more flexible with fewer disruptions leading to a more reliable supply chain.
Success Factors
How can you successfully integrate AI into supply chains in your company? Based on multiple client projects, one key insight stands out: technology alone is not enough. Success depends on a solid strategy, stakeholder buy-in, and a phased approach:
Where can AI create the greatest added value? The selection of high-leverage processes is crucial.
AI is only as good as the data it works with. A clean, robust data foundation is essential for accurate predictions and intelligent automation.
Instead of introducing AI on a large scale all at once, it is worth starting with proof-of-concepts and pilot projects. This allows initial successes to be measured and the system to be scaled gradually.
The use of artificial intelligence will change processes, which can cause uncertainty among employees. Transparent communication and training are essential to create acceptance of the new technology amongst staff.
Conclusion
AI offers enormous opportunities for companies with complex supply chains. But the difference between buzzword and business value lies in how you approach it:
Those who use AI in a targeted manner can proactively respond to market changes, organise the supply chain more efficiently and secure a competitive advantage in the long term.
With the right partner, a clear roadmap and the courage to rethink traditional models, AI can become much more than just another tech trend.
Article Information
Data, Analytics & AI
Supply Chain Management
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