January 5, 2026

Annual Review & Outlook 2026

Logistics

Executive Commentary

Book Your Cargo

Rohan Sachdev

Chief Growth Officer www. bookyourcargo. com

There are things AI can and cannot do in ocean logistics. Today, it is most effective where disruption is common: missed appointments, rolled sailings, chassis and yard constraints, and documentation gaps. Predictive models can identify exceptions earlier and recommend corrective actions that prevent downstream delays and costs. These tools enhance operator decision speed and quality.

However, AI cannot resolve the structural constraints of the supply chain. Terminal capacity limits, inland infrastructure, labor availability and regulatory processes remain physical realities. AI also depends on accurate milestone data to be effective. In 2026, the competitive advantage will come from human-in-theloop automation— supporting operators and standardizing response rather than replacing judgment.

In a similar vein, as the industry has reached a point where most shippers and providers have visibility, the differentiator is the ability to use information to change an outcome. The highest value comes from platforms that reduce exceptions, minimize manual touches and increase cost predictability through proactive decision-making. Visibility is only strategic when it controls dwell, prevents avoidable accessorials and shortens the time between issue detection and issue resolution.

In the realm of reliability, end-to-end supply chain performance increasingly depends on drayage reliability— it is the defining frontier. Appointment windows, chassis availability and yard flow determine whether shipments stay on schedule. Accountability is shifting toward real-time exception response and measurable recovery performance. Shippers will favor partners who can manage variability, not only report it.

We have three expectations for 2026. Operator-facing AI assistants will evolve into workflow engines that not only suggest actions but also initiate bookings, escalations, documentation release and reconciliation steps. Appointment and gate scheduling APIs will become standard tools across many markets, reducing rework and unnecessary waiting time. Finally, contract terms will increasingly reference exception recovery time and cost transparency as core service performance indicators, rather than relying primarily on on-time delivery percentages.

AI will strengthen operations, but it will not satisfy the need for disciplined execution.

“ AI cannot resolve the structural constraints of the supply chain.”

Rohan Sachdev

is a single 8-year-old truck with minimum insurance.

That persistent oversupply has forestalled a much-awaited recovery. Yet the tide is turning, aided by two recent regulatory mandates. One is restrictions on“ non-domiciled” drivers. This policy provided a pathway for non-US residents, who may lack proper work permits or fail to meet legal or other requirements, to operate a truck. A recent DOT audit found that some 200,000 non-domiciled driver licenses have been issued in the US.

The other is the English-language proficiency mandate, issued last May by the Trump administration. This requires a commercial drivers’ license holder to demonstrate sufficient proficiency in reading and speaking English, understanding English traffic signs and signals, the ability to respond to inquiries and make entries on reports and records.

Both these regulatory initiatives are helping correct supply. Will all this be enough for the much-awaited market correction to take place? Only time will tell... but it is certainly overdue.

BuyCo

Carl Lauron

Founder and CEO www. buyco. co

After big data, blockchain, and the metaverse faded from headlines, AI has emerged as the latest technology trend. But is it merely another buzzword or a fundamental shift in container supply chain operations? The evidence suggests genuine transformation. AI’ s value proposition aligns precisely with container logistics structure: fragmented stakeholders, unstructured documentation, multilingual communications and operational complexity. The technology transforms unstructured data into structured, actionable information— directly addressing the industry’ s most persistent inefficiencies.

Client demonstrations consistently generate“ wow” moments as logistics professionals recognize AI’ s practical impact in numerous use cases, including intelligent vessel selection analyzing carrier allocations, freight costs, ETAs, ETDs, CO2 emissions, and direct versus transshipment routing to optimize booking decisions; automated documentation workflows submitting booking requests, verified gross mass declarations, and shipping instructions without manual intervention; smart document classification automatically identifying incoming email attachments and associating them with correct shipments; bill of lading verification comparing draft bills of lading against shipping instructions to catch discrepancies; and shipment creation from email extracting booking details from importer communications.

By extracting data from unstructured documents and integrating it with robust booking workflows, AI accelerates manual tasks while maintaining procedural compliance and ensuring optimal shipment routing.

However, projections indicate AI’ s global energy requirements will equal

“ AI’ s value proposition aligns precisely with container logistics structure.”

Carl Lauron

January 5, 2026 | Page 83