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routing and logistics optimization at a scale that wasn’ t possible before. But AI has clear limits: specialist physical tasks requiring fine motor skills, context or real-time improvisation. While AI can support compliance workflows, it can’ t handle complex legal judgments or nuanced decision-making.
This industry is built on millions of repeatable, transactional processes— bookings, documentation, scheduling, exception handling— ripe for reengineering through agentic and generative AI, representing the greatest near-term opportunity. AI’ s value will come not from replacing people, but from removing friction so human operators can focus on the decisions that truly move shipments forward.
When it comes to visibility systems, while they tell you what is happening, advanced technologies extract the“ so what”— enabling predictive capabilities, real-time decision-making and prescriptive actions. Technology also allows deeper system integration, where visibility feeds into core infrastructure to improve coordination and unlock optimization across the network. In such a complex landscape, real value lies in the ability to turn data into action fast enough to drive resilience and efficiency.
Finally, the cooling of venture capital investment marks a healthy and overdue reset for logistics tech, after it chased rapid scale and aggressive growth models often at the expense of long-term sustainability. With more selective funding,
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resilience, profitability and differentiated value take the spotlight.
This is a sign maturity, not retreat. Logistics is entering its next evolutionary phase, where, more than vision, companies must demonstrate viability. Investors now prioritize targeted innovation over broad disruption, with greater demand for solutions delivering measurable outcomes.
This shift will sharpen the industry’ s focus on technologies with practical benefits, rather than speculative hype. It’ s a recalibration favoring product-driven excellence, operational rigor and true technical differentiation. Ultimately, the companies that survive this phase will be stronger, more focused and better equipped to build lasting value.
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PayCargo Labs
Dennis Monts
President and Chief Operating Officer www. paycargo. com
The intermodal supply chain has long endured friction caused by limited system interoperability, manual processes and inconsistent data integrity. In the 1970s and 1980s, Western European mainframe-driven electronic data interchange networks connected
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terminals, carriers, forwarders and customs for cargo declarations and clearances. By the early 2000s, this evolved into web-based community portals and, ultimately, integrated digital ecosystems serving port communities.
Port community systems expanded beyond customs and manifest exchange to link terminal operating systems with external stakeholders. Supporting applications added vehicle appointment booking, demurrage and detention billing, container event visibility and, most recently, Ocean Shipping Reform Act compliance.
Pre-COVID, pure-play visibility providers emerged with niche, API-driven tools helping shippers stitch together data from disparate, gateway-specific portals. By 2020, pandemic-driven disruption triggered a flood of new entrants, commoditizing freight-lifecycle information.
During that period, investors favored top-line growth over bottom-line performance. That dynamic has shifted. Cargo visibility is now a baseline expectation, not a competitive edge. Differentiated solutions must deliver executional control by accessing systems of record and orchestrating freight movement profitably.
The next phase of digital logistics is not about seeing more but doing more with what’ s seen.
Technology creates value when accurate, real-time data powers automation and smarter freight flows. As exceptions surface, the data itself becomes cleaner and more trustworthy. Here, artificial intelligence plays a pivotal role,
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“ Technology creates value when accurate, real-time data powers automation and smarter freight flows.”
Dennis Monts
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