Looking for any insight to Artificial Intelligence (AI) and how to use it in Supply Chain. Any suggested places to start that will allow for learning, support adoption, and create an environment of support? Any AI partners that you would recommend in terms of tools, software, and effective interface in a SAP environment?
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AI in F&R is a no-brainer but that would be a stand-alone solution (be it with a ton of integrations - depending on how deep you want to go).
To allow for learning, I'd look for spot opportunities (dynamic delivery windows, rebalancing of inventory on order, dynamic prioritizations at ports or warehouses, etc). The tight focus will allow for test and learn opportunities. Also, the space is changing at such a rate that I believe tech debt will be a significant risk to plan for.
Areas that I have explored that seem like great fits include:
Supplier Operations and Compliance
S&OP/Demand Planning and Forecasting
Omni-Channel Order Sourcing, Optimization, and Promising
Labor Forecasting
Distribution Center Operational and Human Resource Support
Based on my research, experience, and partnerships, IBM and Google provide applications that are notably more mature and well-suited for seamless integration with SAP, compared to other available options.
IBM has a MARIO product that helps with inventory optimization and is integrated with SAP. Biggest target areas for SC AI other than inventory optimization are Procure to Pay, spend analysis, and disruption analysis (ie, if Panama Canal indicates passage increases from 30 days to 45 days, or LA port goes on strike, AI can identify all shipments using those routes, how that could affect inventory, proactively recommend options, and, if you trust it, place the orders).
If you are asking about resources for learning about AI:
https://www.goodreads.com/book/show/60623908-power-and-prediction
https://www.amazon.com/Rule-Robots-Artificial-Intelligence-Everything/dp/B09DDCWKKX
Demand Planning and any forecasting tasks are a great use case for AI. Other examples are "rough cut" spend categorization, warehouse route optimization, and a lot more.
I don't know about SAP specifically, but if you're open to exporting the data, there are a lot of tools out there, and you could custom build something as well if needed.
I know we're not supposed to sell here, but feel free to message me if you want to explore possible use cases or practical steps!
When it comes to AI in supply chain, the biggest success factor I’ve seen is starting small, tying projects to clear outcomes, and ensuring your data foundation is solid. Clean, consistent data often makes or breaks AI adoption.
A few practical areas where I see companies are already gaining value:
- Demand Forecasting & Inventory Optimization – moving from quarterly to weekly AI-driven forecasts to cut excess stock.
- Predictive Maintenance – using IoT data to anticipate downtime and keep production on track.
- Supplier Risk Monitoring – applying NLP to financials and ESG reports to flag supplier risk earlier.
- Sustainability – automating emissions rollups for compliance reporting, especially in Europe.
To build a culture that supports adoption, I’d recommend starting with a small internal AI Center of Excellence (CoE). Think of it as a handful of business and technical folks working together as a hub to vet tools, spot good use cases, share learnings, and set some guardrails so adoption scales in the right way and to the right teams.
For learning, Gartner’s own AI research is excellent. MIT Sloan has strong work on AI in operations, the Manufacturing Leadership Council publishes industry-specific case studies, and platforms like LinkedIn Learning or Coursera are good for foundational courses.
The most effective approaches I’ve seen are pragmatic. Don't adopt AI for AI sake. Prove value in one area, then expand.