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AI IN LOGISTICS a reactive process to a proactive one,” Griswold said.
AI is also helping organizations identify accrual risk.
“ With the rise of generative AI, systems can now interpret changing business rules, customer requirements and operational nuances expressed in natural language, allowing workflows to be adapted far more quickly than through traditional development cycles, which require coded updates and release schedules,” Chang said.
In transport management environments, AI is increasingly used to explain cost behavior across lanes, modes and regions rather than only to optimize routing.
“ AI performs best when it is trained on diverse, real-world data,” Griswold said.“ AI that is embedded within a‘ global by design’ freight audit and TMS model delivers materially better outcomes than AI layered onto domestic or lightly globalized platforms.”
Systems, such as nSure AI Data Capture, are integrated directly into global freight audit, payment and transport management workflows rather than deployed as standalone tools. Trained on diverse freight documents across multiple modes and regions, they maintain performance where static rules or templates fail.
These AI-based services allow operational teams to focus on true
connect and act on it across workflows with greater autonomy,” Chang said.
A major shift will also be, what he describes as, the democratization of data analytics. Ordinary users— not just dedicated analyst teams— will ask natural language questions and receive real-time, contextaware insights drawn from consolidated shipment, financial and document data.
“ Both at WOWL and industrywide, the focus will be on embedding governed, auditable AI into daily execution while making advanced analytics directly accessible to business users at the point of decision,” Chang said.
Across freight audit, payments and transport management, AI adoption is
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“ This has elevated both systems from operational tools to financial intelligence platforms,” Griswold said.
Scale and specialty
PayCargo, WOWL and nVision position themselves as logistics-sector specialists. Some newer providers have struggled to deliver consistent results because of fragmented data, limited training sets or centralized operating models that cannot scale sufficiently, Griswold noted.
“ As organizations grow globally, manual processes simply do not scale,” he said.“ Many low-cost providers attempt to manage this through offshore labor or superficial automation, but this approach often leads to inconsistent quality and hidden risk.”
Customers have had to become more discerning. exceptions, negotiations and oversight rather than routine processing.
“ The result is global scalability without linear increases in cost or loss of control,” Griswold said.“ AI is not replacing human judgment; it is extending it, allowing teams to make better decisions faster, across more complexity, with less risk.”
What’ s next?
Much more is still to come in terms of AI-based applications for the logistics industry. Instead of ranking transportation providers based solely on rates, AI will provide more nuanced bid scoring to reflect real-world execution.
“ Over the next 12 months, we expect AI to further automate classification, contextual understanding and crossdocument reconciliation, enabling systems not only to extract data but to validate, reshaping when tasks are performed. Processes that historically relied on after-the-fact verification are increasingly occurring during execution. That shift is transforming multiple parts of the workflow. Financial controls move closer to shipment activity and compliance checks occur continuously.
“ The real transformation lies not just in visibility or the volume of data, but in the quality, accuracy and governance of that data,” Chang noted.
“ Organizations that combine accurate, normalized data with governed automation and informed human oversight will achieve stronger decisionmaking, faster response times and a more sustainable competitive advantage in transportation management.” n
email: 999mattsmith @ gmail. com www. joc. com March 2, 2026 | Journal of Commerce 81