Eight hours per shipment: that is the time artificial intelligence could strip out of air cargo collections, according to CHI Cargo Group CEO Kai Domscheit, by letting truck dispatch and collection planning start well before the traditional release-order trigger fires.

Speaking at Aviation Connect in Athens last week, Domscheit argued that the savings come from moving planning earlier in the chain. Today, ground handlers and forwarders wait for the release order before they dispatch trucks. If AI systems could read and act on the underlying data beforehand, collection planning could begin hours in advance.

The obstacle, he said, is where that data currently sits. The air cargo industry generates vast quantities of operational information, but much of it remains trapped in emails, PDFs, scans, spreadsheets and other unstructured formats that machines cannot readily use.

"The future of air cargo is not going..." Domscheit told the Athens audience, in remarks reported by The Loadstar, before his argument turned to the structural shift AI implies for the supply chain.

Where do the eight hours come from?

The claimed saving does not come from faster trucks or shorter warehouse dwell. It comes from the sequence of events around a shipment's release:

• Release orders currently act as the trigger for truck dispatch and collection planning.
• Data needed to plan those collections often already exists in unstructured formats before the formal trigger.
• AI can extract and structure that data, allowing dispatch decisions to move earlier in the timeline.
• The result, per Domscheit's estimate, is roughly eight hours saved per air cargo shipment.

For an industry where collections are planned daily against fixed cutoff times, pulling planning forward by most of a working day would change how forwarders schedule trucking capacity. Handlers would gain earlier visibility of pickup demand, and carriers could see projected volumes sooner.

What does this mean commercially?

The commercial logic is straightforward. If collection planning starts earlier, truck utilization improves because dispatchers can consolidate pickups with more lead time. Forwarders gain a wider window to rebook or reroute when capacity tightens. Handlers, who currently plan against late-arriving release information, would face fewer end-of-day surges.

The barrier is data quality rather than technology ambition. Unstructured formats — the emails, scans and spreadsheets Domscheit pointed to — are precisely the documents that AI extraction tools are now built to process. The value of the eight-hour claim lies less in the number itself than in what it implies: the information needed to speed up air cargo collections already exists inside most operators' inboxes and files.

The industry's task, as framed in Athens, is unlocking it.

Whether AI-driven planning becomes standard practice will depend on how quickly handlers and forwarders can integrate extraction tools into existing dispatch workflows — and on whether the promised hours translate into measurable rate and reliability gains.