Air cargo tech firm CargoAi has launched a new module that uses AI to anticipate operational risks and shipment delays.
The new AI Predictive Tracking service can be used within CargoAi’s third-party booking portal, CargoMART, and on its CargoCONNECT Track and Trace API.
The service uses “machine learning models trained on millions of historical shipments”, combined with live airline flight updates, to predict the expected timing of each key milestone in an air cargo journey.
These milestones include documentation submission (FWB), acceptance (RCS), manifesting (MAN), departure (DEP), arrival (ARR), freight availability (NFD) and final delivery (DLV).
“Predictions are continuously refreshed as new information is received, enabling operational teams to detect risk patterns earlier in the process,” the company said in a press release.
“Airlines can identify shipments that have not reached RCS or MAN before the cutoff and are therefore at risk of missing their planned flight.
“Alerts can be triggered to stations or GSAs to intervene, release blocked capacity, or prioritise high-risk shipments.”
CargoAi said that the data can also be used to benchmark station performance and identify recurring bottlenecks.
Fowarders will also gain visibility on shipments flagged as “at risk” and ground handlers can use predictions to prioritise acceptance, automate pre-alert management, and feed predictive risk levels into internal dashboards.
Source: https://www.aircargonews.net/editorial/2026/02/cargoai-utilises-ai-to-predict-air-cargo-shipment-delays/
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