NFI, one of North America's largest privately held supply chain firms, has been named an honoree in the Operational AI Integration category of the 2026 AI Excellence in Supply Chain Awards for its work across NFI Transportation Management, the company's managed transportation arm. The award recognizes real AI deployments with measurable outcomes rather than pilots or proof-of-concepts, and NFI's entry documented specific weekly time savings across its logistics operations.
The company's approach is organized around a three-pillar framework rather than chasing single use cases. The pillars - Operational Support, Back Office Support, and Customer Value Add - each contain distinct tools with documented deployment statuses and quantified results.
Operational support: attacking manual load tracking
NFI deployed agentic AI to handle load tracking through web scraping, email monitoring, and automated phone check-ins, replacing the manual process of associates calling, emailing, and logging into portals to check on freight. The tool is live for LTL freight and is being onboarded for truckload, currently saving 160 hours per week.
Alongside the tracking tool, NFI built a natural language chatbot that gives associates instant access to standard operating procedures and reporting. The company says this approach has reduced formal training time and help-desk tickets while improving employee satisfaction.
Back Office Support: reclaiming over 100 hours a week
NFI's back-office AI tools focus on what the company calls "eliminating the monotonous." Three systems handle the heaviest lifting. An email triage and response system processes inbound freight bill correspondence automatically, saving 60 hours per week. A freight bill-to-load match exceptions tool trains a model to handle the tedious matching work that historically required manual searching - two of three phases are live, saving more than 17 hours per week, with another 10 hours of potential savings identified for the third phase.
An FBA aging app automatically prepares aging reports for carriers on request, good for 15 hours per week in savings and a direct improvement in how carriers are served. Combined, the back-office tools reclaim more than 100 hours per week. The load-tracking work alone frees the equivalent of four full-time employees' worth of capacity.
For professionals managing operations teams, the pattern here is worth noting: NFI didn't build one AI tool to solve all problems. It built several small, targeted tools, each with a specific job, a measured rollout status, and a documented ROI. That's a more replicable model than a single large platform bet.
Customer Value Add: the Digital Twin
The customer-facing side of NFI's AI work is centered on Navitrace, a global intelligence platform that functions as a "Digital Twin" of a customer's transportation network. The Digital Twin is built from proprietary data and contracted rates, and it runs on-demand "what-if" scenarios. Customers can model the impact of adding or removing carriers, compare contracted rates against market pricing, or evaluate consolidation strategies.
NFI reports the Digital Twin is uncovering an average of 5% to 10% in transportation savings per customer; one client alone realized more than 600,000 dollars in annual savings. A supporting appointment scheduling tool has produced a 75% reduction in dwell time, helping customers avoid on-time in-full penalties.
The development of Navitrace came in response to what NFI describes as a market full of cumbersome, one-size-fits-all visibility tools. The platform's modular, microservices-based architecture is built to reveal scenarios organizations might not have previously considered - a distinctly different outcome than the standard real-time reporting layer.
Why this matters for operations and transportation managers
The lesson in NFI's win is not the technology itself but the discipline around it. Every tool had a named function, a live or in-development status, and an hours-saved figure attached to it. "What set NFI apart was that they could show their work," said Adam Wingfield, FreightWaves' editorial director. "Most entries in this category talk about AI in the abstract, but NFI came in with hours saved, dollar figures, and a clear read on what's live versus what's still in development."
Managers in logistics or operations should look at NFIs structure: it asks of each problem, "Is this an AI use case worth building?" and then builds narrowly and measures publicly. Job displacement after the savings is then reallocated from reactive tasks to what NFI calls "professional empathy" in client and carrier interactions. While not every company has the scale to run agentic email triage, the same scrutiny applies anywhere: know what the tool costs, know what it saves, and be able to quote both numbers in a meeting. For managers interested in a structured approach to which workflows are prime candidates, training for AI for Operations covers exactly this kind of prioritization. AI for Transportation Managers is a dedicated learning path designed to help production-oriented managers go from concept to deployment. More broadly, the interview with Wingfield makes clear that documented results is what survives contact with an awards review - and with an executive budget review.
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