Logistics 2026 Annual Review & Outlook
Executive Commentary |
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Early adoption sounds bold, but there are strategy and strength in being a“ fast follower.” Observe where others invest, stumble and succeed to save time, money and frustration.
Finally, remember logistics is driven by people. The best AI solutions will not eliminate human judgment. They will amplify it. A human-in-the-loop approach ensures automation supports, not replaces, expertise. Maintaining this balance is critical to preserving and accelerating organizational success.
Trade Tech
Bryn Heimbeck
President and Co-Founder www. tradetech. net
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“ Be aggressive and creative in finding ways to lower costs or remain status quo and see freight costs rise.”
Mike Regan
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schedule with the terminal for the cargo pick up prior to arrival.
Digital providers will have enormous efficiency, and the service they provide to their customers will be at the same level of consistency and predictability that machines brought to manufacturing. This will be where the commercial strategic advantage comes to those who lead. Those that don’ t will be at risk.
Humans will still be involved doing the real thinking needed to manage the supply chain, but the administrative process will be mechanized in much the same way that machines replaced human energy in manufacturing 100 years ago.
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TranzAct Technologies
Mike Regan
Chief of Relationship Development www. tranzact. com
I’ ve spoken with financial analysts as well as senior executives at carriers and third-party logistics( 3PLs)— all expect 2026 to be a year of separation for shippers.
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Artificial intelligence, in the larger sense of a software system taking over human work, represents a revolution as important as the mechanization of manufacturing in the Industrial Revolution. This revolution will come from integrating the business process with sales driving operations and accounting, combined with rules-based logic that automates the administrative process.
AI does not mean that the software system will come up with a poetic solution for the customer. Large language models are not the answer to the logistics service model. Giving the customer exactly what they negotiated with the salesperson, regardless of where the shipment originates, from booking to delivery, will be the bedrock of the next generation of digitalization.
The service environment will be fully digital. Rates will be available on demand. Ordering a shipment will be as easy as ordering a pizza home delivery online. Payments will be automatically calculated and often transacted electronically. Customs entry, after an item has been imported once before and classified by a qualified human customs broker, will be automated and conducted while the shipment is in transit prior to arrival. Port terminal efficiency will be hugely impacted by those that are digital and, thus, ready to
“ This will be where the commercial strategic advantage comes to those who lead. Those that don’ t will be at risk.”
Bryn Heimbeck
“ The next phase of evolution will be AI agents capable of analyzing information and autonomously executing operational tasks.”
Kooil O
Samsung SDS
Kooil O
Executive Vice President, Head of Logistics Business Division www. samsungsds. com
Despite carrying over 80 % of global trade, maritime logistics continues to operate with siloed data across carriers, terminals, forwarders, etc. This fragmentation restricts transparency and responses to disruption and slows decision-making. As supply chains demand greater resilience, speed and predictability, artificial intelligence has emerged as a strategic accelerator to reshape the future of ocean shipping, addressing long-standing industry challenges rooted in fragmented systems, uneven digitalization and limited data interoperability.
AI applications fall broadly into two categories: analytical AI and generative AI. Analytical AI leverages structured data to identify patterns in it, improve forecasting accuracy, optimize operations and support risk management. Its value is particularly clear in route optimization considering traffic conditions and delivery priorities, inventory forecasting to prevent overstocking or stockouts, and loading optimization by transforming manual loading processes in a proactive and efficient manner. Generative AI, powered by large language models, expands intelligence into unstructured information. It can summarize market updates, detect emerging risks, extract information from emails or PDFs and respond to operational questions through natural-language queries. It also powers intelligent customer-service automation, allowing chatbots to manage routine inquiries such as tracking requests or schedule changes, freeing human expertise for more complex workflows.
The next phase of evolution will be AI agents capable of analyzing information and autonomously executing operational tasks. Routine tasks will be automated initially, and, over time, it will orchestrate entire logistics flows in a more integrated and holistic manner.
Ensuring timely and accurate data across non-standardized systems is essential to fully harnessing the potential of AI in logistics. That is, inaccurate or irrelevant information leads to flawed analyses, in line with the principle of“ Garbage In, Garbage Out.” Accordingly, third-party logistics providers must accelerate digitalization and build interoperable systems across the logistics ecosystem to drive genuine digital transformation.
92 Journal of Commerce | January 5, 2026 www. joc. com