Glacis

I'm hosting a webinar on AI for Supply Chain leaders, drawn from 400+ executive conversations: https://bit.ly/469GXee (next Tuesday, Sep 15th, 10:00 CET)

Join us for a live webinar 'AI for Supply Chain Leaders' on September 15th at 10.00 AM CET In this session, we focus on what AI adoption actually looks like for supply chain teams at enterprise manufacturers. Grounded in proprietary data from AI adoption experiences of 400+ supply chain leaders, we break down the use cases that are working today, the hurdles that slow down rollouts, and clear frameworks to identify where AI fits; and how to vet the vendors who market their offerings.

For all the Supply chain leaders, join us for a live webinar, if you want to know what AI adoption looks like in real world. Grounded in proprietary data from AI adoption experiences of 400+ supply chain leaders, we break down the use cases that are working today, the hurdles that slow down rollouts, and clear frameworks to identify where AI fits; and how to vet the vendors who market their offerings. Date & Time: Sep 15, 2026 at 10.00 AM CET

Join us for a live webinar 'AI for Supply Chain Leaders' with Philipp Gutheim In this session, we focus on what AI adoption actually looks like for supply chain teams at enterprise manufacturers. Grounded in proprietary data from AI adoption experiences of 400+ supply chain leaders, we break down the use cases that are working today, the hurdles that slow down rollouts, and clear frameworks to identify where AI fits; and how to vet the vendors who market their offerings.

Most manufacturers I talk to name exception management as their main execution pain. Besides the major global disruptions, it's the steady stream of small supplier deviations every week that breaks the production schedule. Here is an example. When a supplier moves a delivery date or cuts the quantity, the change either never gets communicated or arrives too late. It lands in an inbox and stays there until a planner reads it and manually updates the ERP. Planners continue working from the original commitment in the ERP or the planning software until someone manually updates it, so the MRP looks healthy while the real schedule has already slipped. By the time the deviation surfaces at assembly, a material shortage occurs and planners have to reschedule the production line. Part of the reason why this persists is that 90% of PO confirmations still arrive by email. Expedite logs and batch open-order reviews only surface PO changes days later, after someone reads the reply and manually updates SAP. By then the window to act has closed. This is why manufacturers like Hussmann and WITTENSTEIN are automating supplier communication in the channel that suppliers already use: the inbox. AI agents read the replies, pull the confirmed dates, and write them back to the open POs while the window to act is still open. They flag the exceptions that still need manual intervention, like a price change or a quantity shortfall, so planners stop spending time on manual follow-ups. I have put together a short case study with a few real-world examples of how manufacturers are automating exception management. Download it here: https://lnkd.in/gHzHAPUs