Air cargo’s next hurdle: connecting fragmented shipment data across the supply chain

# What the problem is

# Why it matters now Trade patterns are changing. Thangavelu pointed to China–US ecommerce volumes, which have fallen significantly over the past year after changes to US de minimis rules. "The volume is actually shifting, but it's not disappearing," he said. At the same time, overall freight is growing and capacity has increased year on year. Those shifts mean stakeholders need near-real-time clarity on what is moving, where and in what quantity.

# Where fragmentation shows up

# The standards angle: ONE Record IATA's ONE Record aims to create a common digital record for shipments, and many stakeholders are aware of it. But Thangavelu emphasised that "being ready" for ONE Record is not the same as operating it. Implementations are progressing — the article points to Lufthansa's work with multiple technology partners as an example — but achieving a single source of truth across the entire shipment lifecycle will take time.

# Where AI can add practical value With standards adoption incomplete, AI offers a route to bridge gaps. Thangavelu described AI agents that connect different systems, reconcile competing sources of shipment information, and enable cargo participants to make and execute decisions. Practical applications include:

• Ground operations: confirm correct piece counts, spot last-minute manifested shipments, and trigger labour and equipment allocation.
• Commercial functions: link operational systems to global trade intelligence to provide early signals on commodity flow changes, informing pricing, capacity allocation and network planning.
• Flight planning and revenue management: faster insight into shifting demand allows airlines to adjust sales strategies and capacity decisions more quickly.

# Short-term implications for operators Adoption will be incremental. Operators should prioritise the data flows that create the most immediate operational pain: e.g., the handover between carriers and ground handlers, manifested vs actual counts, and customs release information. Where ONE Record is not yet in place, consider AI-driven reconciliation tools that ingest multiple feeds and surface a single operational view.

# Practical next steps suggested by the story

• Map the most inconsistent data handoffs in your operation (ground handling, customs, carrier-manifest reconciliation).
• Pilot reconciliations that focus on concrete decisions (labour scheduling, gate assignment, revenue allocation).
• Track ONE Record implementations by key partners and align integration plans to avoid duplicated efforts.

# Final takeaway Digitisation has laid the groundwork. The immediate priority is building reliable, reconciled views of shipments so operational and commercial teams can act fast. AI can serve as a practical connector while standards like ONE Record continue to scale up.