WEEKLY NEWS


MATT PETOT Leadership Spotlight


Founder and CEO of CargoAi BY Anastasiya SIMSEK


Artificial intelligence has moved beyond conference panels and pilot projects. Across air cargo, the conversation has shifted from whether to digitise to how quickly operational friction can be removed without compromising control. As volumes fluctuate, margins tighten and geopolitical


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innovation theatre but as infrastructure. For Matt Petot, Founder and CEO of CargoAi, 2026 marks a turning point from experimentation to execution. The industry, he argues, is no longer debating AI in abstract terms. It is testing where it delivers measurable operational advantage — and where expectations remain ahead of reality.


From reaction to anticipation Petot expects AI and automation to “fundamentally reshape how decisions are made and executed in air cargo operations” in the coming year. The most visible shift will not be dramatic robotics on the ramp, but speed and anticipation in digital workflows. “What will genuinely evolve is speed and anticipation: faster booking decisions, earlier disruption detection, smarter routing, and far less manual coordination,” he says. In practical terms, this means fewer emails, fewer duplicated checks and less reactive fire-fighting when shipments fall off schedule. Predictive intelligence sits at the centre of that shift. In 2026, Petot argues, predictive tools will enable teams to anticipate capacity constraints and detect potential delays before disruptions escalate. Routing and allocation decisions can then be adjusted pre-emptively rather


risk persists, automation is increasingly framed not as


their fragmentation. Airlines, forwarders and GSAs frequently operate across disconnected booking systems, tracking platforms and reporting dashboards. “The priority in 2026 should be simplification rather than adding more tools,” he says. The path forward lies in connected platforms that unify booking, tracking, execution and payments through shared data layers and APIs. Resilience, he argues, will not come from layering new applications onto legacy systems, but from reducing fragmentation and standardising workflows. This diagnosis reflects a broader structural issue. Air cargo’s digital maturity has been uneven, shaped by bilateral integrations and regional compliance


requirements. As cross-border regulatory oversight


intensifies, fragmented systems create both operational inefficiency and governance risk. Connected data architectures offer not only speed but traceability.


Where AI is already working Despite the hype, Petot is pragmatic about where AI is already delivering tangible impact. Booking assistance,


rate comparison, predictive tracking and workload reduction are producing measurable gains. Operational teams feel the benefit directly through fewer manual checks and faster


times. By


contrast, fully autonomous


pricing optimisation and end-to-end automated irregular operations handling remain, in his words, “more promise than


than retroactively.


Volatility will not disappear, but operational surprises should reduce in frequency and impact. Yet he is clear about the limits. “What is unlikely to change as quickly is the need for human judgment.” Air cargo remains highly regulated, exception-driven and commercially nuanced. AI will increasingly augment teams by handling repetitive tasks and surfacing insights, but it will not


replace experienced


operators navigating compliance requirements, sensitivities operations.


and


customer irregular


Simplification over accumulation If


2025 was by experimentation,


reality”. The constraint is not ambition but data consistency and trust. Algorithms require reliable, standardised inputs; where


data weak, governance


“For AI adoption to mature, data must be treated as a core operational asset


rather response than a by-product,” Petot argues. Clearer ownership


and transparency around how recommendations are generated are essential. Trust, he suggests, will not be built on perfect data sets but on consistent, explainable outputs.


is


automation falters.


characterised 2026,


in Petot’s view, must be defined by simplification. The industry’s digital problem is not the absence of tools but


ACW 23 MARCH 2026 www.aircargoweek.com


Scaling without headcount Automation’s appeal is particularly acute as logistics players confront rising volumes and operational complexity without commensurate labour availability. Digital workflows, Petot notes, allow organisations to manage increasing shipment volumes “without proportional growth in headcount, while maintaining speed and service quality.” In this context, competitiveness becomes a function of orchestration rather than scale alone. Companies that can coordinate booking, tracking, documentation and payments within unified environments gain structural advantage over those reliant on manual coordination. CargoAi’s vantage point across airlines, forwarders and digital platforms offers a cross-sectional view of behaviour change. In 2025, Petot observed a decisive shift from experimentation to execution-focused innovation. Organisations are prioritising solutions that deliver immediate operational impact. Persistent bottlenecks — email overload, fragmented tracking and manual coordination — remain widespread, but tolerance for abstract digital strategies is waning. A defining pattern for 2026, he suggests, will be the rise of unified platforms and AI agents capable of orchestrating workflows across the shipment lifecycle rather than addressing isolated tasks. The implication is clear: point solutions may improve margins incrementally, but structural efficiency requires end-to-end integration. Petot’s advice to decision-makers is pointed: “Focus on outcomes, not technology labels.” Initiatives that reduce manual workload and operational friction within weeks — unified booking and tracking, AI- assisted decision support, automated payment workflows — offer the highest near-term return. Projects that fail to simplify operations quickly are unlikely to justify their cost.


“Focus on outcomes, not technology labels.”


This tension between potential and preparedness underlines a central theme of digital transformation. Technology deployment is rarely the primary bottleneck. Data ownership, validation at source and organisational confidence in AI-generated recommendations are more decisive factors.


AIR CARG O WEEK


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