AI Adoption in Freight Forwarding: Pace Matters for Success

Industry leaders are signaling that artificial intelligence represents a legitimate and necessary evolution for the freight forwarding sector, but success depends on measured, phased implementation rather than aggressive rollout. Eyal Goldberg, CEO of Breeze (an insurtech platform specializing in embedded cargo insurance), advocates for a two-stage adoption strategy: prioritizing automation of back-office functions before advancing to systems that manage physical container movements and logistics workflows. This guidance carries significance for forwarders and 3PLs evaluating their digital roadmaps.

The freight forwarding industry operates with unique operational constraints, real-time visibility requirements, complex compliance frameworks, multimodal coordination challenges, and inherent physical risk, that demand more sophisticated AI implementation than simple automation plays. Rushing deployment without accounting for these nuances risks costly integration failures, data quality issues, and operational disruptions during peak seasons. For supply chain professionals, the takeaway is clear: AI is not optional, but neither is strategic sequencing.

Organizations should audit their back-office processes (billing, documentation, capacity planning, exception handling) and identify high-volume, repeatable tasks suitable for AI-driven automation before investing in autonomous decision-making systems for freight operations. This staged approach allows teams to build internal AI literacy, validate data infrastructure, and refine workflows in lower-risk environments before deploying AI to customer-facing and time-sensitive logistics functions.