Agentic AI in Supply Chain – Beyond the Buzzword | Ep. 25
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Agentic AI in Supply Chain – Beyond the Buzzword | Ep. 25
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They trace the shift from the first wave of AI, which made our existing forecasts and plans better, to the agentic wave, where systems can take a goal and work towards it on their own.
Rafael offers a genuinely usable definition of agentic AI, explains why giving a model tools changes everything, and is candid about why so many projects fail, from the 10,000-bottle order nobody approved to the temptation to dump an entire dataset into the context window.
The conversation then turns practical: where agentic AI is already creating value in planning, how optimisation is being democratised beyond PhD-level data science, and how Roima's Aura connects the data silos across IBP, MES, WMS and PLM to surface insights teams have been missing.
They close on the question everyone asks: what does this mean for the people doing the work?
Essential listening for supply chain managers, Heads of S&OP, IBP managers and anyone weighing where to place their next bet.
Key takeaways
- There are two waves of AI in supply chain. The first made existing tasks better; the second, agentic wave takes on goals and works towards them. "What is my OTIF?" is a request; "how do I increase my OTIF?" is a goal the system works towards on its own.
- A model becomes agentic when you give it tools to query data, run code or take action, and let it navigate them in a loop. More power means more risk, so guardrails and gates are non-negotiable.
- Projects fail on missing basic assertions and on dumping too much raw data into the model. Success comes from pairing the right use case with the right methodology.
- Aura gives AI the power of a developer, writing and running its own code across the full dataset, security-built from the ground up. It is like hiring a team of specialists you could never afford, and Roima's digital thread lets it connect insights across IBP, MES, WMS and PLM silos that never spoke to each other.
- Waiting for 100 per cent accuracy is the wrong test, because humans make mistakes too. The real question is the cost of an error and the gates around it, and so far these tools empower planners and keep them in control.
- 03:37 Why supply chain professionals need to care now
- 04:53 From the first wave of AI to the agentic wave
- 08:29 What "agentic AI" actually means
- 14:11 The big pitfall: dumping all your data into the model
- 15:18 Where we are now, and the tipping point
- 19:41 Democratising optimisation without an army of PhDs
- 24:30 Real use cases: from chatbots to Aura
- 32:11 The digital thread: connecting the silos
- 33:44 What this means for the humans, and wrap-up
Guest: Rafael Amaral, CTO and Co-Founder of TilliT (Roima Intelligence). More than twenty years in manufacturing technology across supply chain planning, optimisation and execution systems.
Host: Søren Hammer Pedersen, CCO, PERITO IBP at Roima Intelligence.
Production
This podcast is brought to you by Roima.
This podcast is produced by Montanus.
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