CARGOCONNECT-JUNE2026 - Flipbook - Page 44
COVER STORY
AIR CARGO ASCENDS
The e-commerce
surge is altering
cargo processing
dynamics, forcing
airports and
handlers to prioritise
faster throughput,
shorter dwell times,
and standardise
coordination across
customs authorities,
airlines, and
logisticians.
SIMONE SCHWAB
SENIOR VICE PRESIDENT–
AVIATION AND CARGO
DEVELOPMENT, FRAPORT AG
temperature-sensitive handling processes.
When integrated with computer vision and
AI-led anomaly detection systems, these
technologies are capable of delivering far
greater consistency while minimising human
fatigue and operational error rates. Panicker
notes that conveyor-based automated sorting
systems are also being evaluated across
the airport’s cargo facilities to improve
throughput and reduce manual ine昀케ciencies.
Yet, beneath the visible layer of robotics
and automation lies an equally critical transformation: digital orchestration. Panicker
emphasises that Application Programming
Interface (APIs), Robotic Process Automation
(RPA), IoT-enabled monitoring systems, Radio
Frequency Identi昀椀cation (RFID) integration,
and real-time cargo visibility platforms are
increasingly becoming the digital backbone
of modern cargo ecosystems. These systems
are beginning to operate as interconnected
layers capable of synchronising cargo data,
infrastructure, and operational work昀氀ows
into a uni昀椀ed decision-making environment.
For instance, at Hyderabad Airport,
Panicker informs, IoT-enabled temperature
monitoring systems are already being piloted
within cold-room facilities to strengthen
handling reliability for pharmaceutical and
temperature-sensitive cargo. This growing
integration between automation and data
intelligence is also fundamentally reshaping
how operational decisions are made inside
cargo ecosystems.
The growing integration between
automation and data intelligence is also
fundamentally reshaping how operational
decisions are made inside cargo ecosystems.
Increasingly, cargo operators are recognising
that the next phase of e昀케ciency gains will
not come solely from adding infrastructure,
but from making existing infrastructure
signi昀椀cantly more intelligent, responsive,
and interconnected.
This accelerating convergence between
automation and digital orchestration also
re昀氀ects a much broader structural transition
underway across global air cargo ecosystems.
Sullivan observes that technologies such as
AI-driven capacity allocation, digital freight
platforms including cargo.one, WebCargo by
Freightos, and CargoAi, alongside API-based
pricing systems, are fundamentally reshaping the industry into a more connected,
intelligent, and responsive ecosystem.
According to Sullivan, the real transfor-
mation lies not merely in the technologies
themselves, but in the industry’s gradual
shift away from fragmented processes
and siloed messaging towards shared,
real-time data environments capable of
enabling faster planning, smarter execution,
and more collaborative decision-making
across stakeholders. He further notes that
interoperability, common digital standards,
and trusted data foundations are becoming
increasingly critical as airlines, freight
forwarders, and logistics operators seek
to improve forecasting precision, optimise
capacity deployment, and strengthen customer visibility across increasingly complex
global cargo networks.
According to Kirchner, Arti昀椀cial Intelligence (AI) in air cargo has already moved
well beyond experimentation and is now
delivering tangible operational impact across
day-to-day planning functions. Some of the
most visible gains are emerging within
demand forecasting and constrained capacity allocation, particularly in belly cargo
environments where space optimisation
remains critical. By leveraging AI-driven
planning systems, she points how airlines are
increasingly making faster and more precise
decisions around shipment prioritisation
and capacity deployment.
Kirchner further notes that AI is
strengthening load-factor optimisation and
routing precision by aligning cargo 昀氀ows
more intelligently with passenger network
schedules. In a market where 昀氀exibility and
reliability are becoming equally important,
these systems are helping carriers improve
aircraft utilisation without compromising
service consistency. Beyond operational
planning, she notes, AI-led customer-facing
tools such as automated booking, dynamic
pricing, and real-time tracking steadily
transforming cargo interaction models,
improving transparency and responsiveness
across the shipment journey.
A similarly digital-昀椀rst philosophy is
shaping operational planning at Riyadh
Cargo as well. Singh points out that the
carrier’s ‘digital-native’ foundation is allowing it to integrate AI and data-led systems
directly into the core architecture of cargo
operations without the limitations associated with legacy infrastructure. Through
CHAMP’s CargoSpot Neo platform, Riyadh
Cargo is deploying enhanced real-time
reporting, analytics-driven planning, and
Cargo ecosystems increasingly depend on
interoperable data platforms enabling real-time
coordination across logistics stakeholders.
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