AI in agri-food logistics: what is actually deployed, not what is promised

Measured and realized: C.H. Robinson's quote-to-cash automation

C.H. Robinson is the strongest documented case of AI moving from pilot to measured business result in freight. In a February 2026 newsroom post, the company stated that its 'Lean AI' program had 'increased productivity by more than 40%' since 2022, automating pricing, order entry, capacity sourcing, pickup/delivery appointments, freight tracking, document handling and invoicing. By its Q2 2026 results (published 29 July 2026), that figure had risen to 'more than 60% productivity improvement since the end of 2022 in both NAST and Global Forwarding' — its North American surface transportation brokerage and its international freight-forwarding arm respectively — alongside a 20% year-over-year increase in adjusted operating income and margin expansion of 280-470 basis points across those two units in the same period.

The distinguishing feature here is that these are backward-looking, already-realized figures tied to specific reporting periods and business units, not a forecast. Trade press independently corroborates the underlying mechanism: 'hundreds of AI agents running quoting, order-entry, and tracking' embedded directly into C.H. Robinson's own application layer, rather than bolted-on point tools.

In production, outcomes undisclosed: Cargill's named platforms

Cargill won the Business Intelligence Group's 2026 BIG Artificial Intelligence Excellence Award, and the coverage names specific, currently-deployed systems rather than a generic AI narrative: CMAX, described as predictive analytics that 'optimize port and shipping logistics', and CarVe, a computer-vision system that 'boost[s] yield and reduce[s] waste across protein supply chains.' Cargill also runs on-farm platforms (Agriness, CattleView, Prosense Feed, Galleon) for herd performance and feed efficiency, and generative-AI tools (Ask Emma, Taste Tinker) for product development.

What's missing from the public record is any quantified outcome for CMAX or CarVe specifically — no percentage improvement, cost saving or throughput figure was disclosed in the award coverage or in Cargill's own materials we could access. That's a meaningfully different claim than C.H. Robinson's: a real, named, production system exists, but the size of its effect hasn't been made public. Treat it as evidence AI logistics tooling is operating at scale inside a major agri-food trader, not as evidence of a specific return.

Disclosed, but still a projection: Kuehne+Nagel's investor target

The figure that circulates most widely in trade coverage — Kuehne+Nagel's AI agents adding CHF 100-150 million to annual profit — is real in the sense that the company disclosed it to investors, dated to July 2026 materials, applying to roughly 25,000 white-collar roles (a ~5% productivity gain against roughly CHF 1.7 billion in staff costs for those roles) with the target date being end of 2027. What often gets dropped when the figure is repeated: Kuehne+Nagel's own investor materials call this 'a gross estimate' built on a finance-based methodology rather than measured output metrics, and management has said explicitly that 'adoption and rollout could move the number.' This is a disclosed target, not a result — the distinction the trade press coverage of it is careful to make and that secondary repetition often loses.