About 600 million tons of goods are moved annually across US inland waterways, a network of nearly 12,000 miles. As a perfect storm of aging infrastructure, unpredictable conditions and fragmented data converges on inland waterway logistics—making it harder to keep freight moving efficiently across these waters—AI is emerging as a solution for both carriers and shippers.
One company betting on that shift just got a vote of confidence. Cooperative Ventures—a joint venture between CHS Inc. and GROWMARK focused on AgTech investing—announced a new investment in OpenTug, an AI-native logistics technology company focused on inland and coastal marine transportation. Jason Aristides, co-founder and CEO of OpenTug, explains how AI can fit into an industry built on decades of tradition and hard-won expertise.
Treading Water
The US Army Corps of Engineers’ Inland Waterways Users Board reported that 80% of inland waterway locks and dams have exceeded their 50-year design life, which underscores how significant the infrastructure challenge has become.
“At the same time, the information needed to respond to those disruptions is often fragmented across carriers, terminals, shippers, emails, spreadsheets, GPS systems and other sources,” Aristides continues. “And there is also no universal way to track an individual barge when it is not connected to a towboat. That makes it difficult to understand the downstream impact of a disruption quickly enough to adjust plans.”
Aristides adds, “I think one of the industry’s biggest opportunities is improving how we anticipate and respond to those variables because we can’t control river levels, weather, or a lock closure, but we can make faster and better-informed decisions when conditions change.”
Data Streams
In terms of KPIs (key performance indicators), Aristides advises agricultural supply chain stakeholders who depend on barge transportation to look beyond traditional metrics such as on-time performance and focus more closely on asset utilization, voyage cost variance, invoice cycle time, carrier performance by lane and demurrage exposure.
“Unlike some other commodity sectors, agriculture is driven by high volumes, seasonal demand, and relatively tight transportation margins,” he explains. “Small improvements in planning and equipment utilization can create significant value across an entire shipping season.”
One KPI Aristides believes deserves more attention is asset utilization. In grain exports, it’s not simply about where barges are located, but whether they’re positioned to support the next movement at the right time. Barges often need to arrive in coordination with a specific export vessel, which requires planners to align incoming barge movements with vessel schedules across the network.
“More sophisticated ETA models can give planners the lead time and visibility needed to make those decisions earlier and keep equipment moving more efficiently,” he adds. “Ultimately, the most valuable KPIs are the ones that help planners optimize the network as a whole rather than measure individual voyages.”
OpenTug’s BargeOS optimizes marine logistics by streamlining commercial planning, voyage management, invoice reconciliation and reporting on one platform. The technology enables shippers and carriers to reduce idle barge days, improve ETA prediction accuracy and minimize demurrage charges. Combining integrated barge GPS monitoring with BargeOS Autopilot’s automated ingestion of traffic reports and operational emails provides a real-time view of barge movements and voyage activity.
Riding the AI Wave
Aristides says AI—which is built into BargeOS—can convert fragmented information into usable operational and financial data. It can capture updates from traffic reports, validate voyage events, process invoices and flag discrepancies that would otherwise require manual review.
With a longer history of voyage and cost data, AI can also improve ETA forecasting, quoting, cargo planning, signal optimization, invoicing and tracking. The long-term opportunity is to connect those workflows so decisions made during planning can be evaluated against actual voyage and financial outcomes.
But in a traditional industry with deep roots, the new wave of AI can face some pushback. “The biggest barrier is trust,” Aristides confirms. “Marine transportation depends on deep operational expertise, and many of its processes have been refined over decades. Adopting AI can mean challenging long-standing industry norms and reconsidering the way things have traditionally been done, so the technology has to demonstrate value without discounting that experience. AI should support experienced teams rather than impose decisions or disrupt proven workflows.”
Aristides adds that data quality and integration are also challenges because information is often spread across multiple systems and organizations. AI adoption depends on transparent outputs, reliable data and workflows that keep users in control of consequential decisions.
Charting a Course to ROI
In the immediate term, Aristides says the greatest opportunity for AI is automating administrative work such as processing traffic reports, maintaining voyage records, updating ETAs and reconciling invoices.
“The most meaningful ROI typically comes from a combination of productivity gains and better decisions,” Aristides elaborates. “Better planning and barge coverage strategies can reduce structural costs, while faster day-to-day decisions—like identifying a better equipment assignment, avoiding an unnecessary cleaning, or preventing an idle day—create direct financial value. Ultimately, the greatest ROI comes from helping customers make better operational decisions, not just complete existing processes more efficiently.”
Aristides relates the story of a customer who used OpenTug’s AI pipeline to ingest emails, documents, spreadsheets, GPS, weather, lock data and other operational information, and identified an opportunity to reduce the size of a dedicated barge fleet for a specific product by 33%, generating more than $3 million in projected annual savings.
“Longer term, AI can help optimize entire transportation networks by improving equipment assignments, forecasting disruptions, increasing cost predictability, and connecting decisions across planning, execution, and finance,” Aristides concludes. “The ultimate goal is not simply to automate individual tasks. It is to help operators and shippers understand the operational and financial impact of each decision across their full barge portfolio.”
