Why AI Adoption in Logistics Remains a Double-Edged Sword

Despite a decade of digital investments in automation tools, dashboards, and AI pilots, the freight forwarding industry continues to operate on surprisingly manual foundations. According to a report from Deep Current, a Bremen-based logistics AI company, core workflows at European and Middle Eastern logistics firms remain heavily dependent on emails, spreadsheets, PDFs, and fragmented systems—even as organizations have deployed sophisticated operational systems. This disconnect reveals a critical gap between technological capability and practical implementation.

The industry faces a pivotal moment: AI and automation technologies can either significantly enhance efficiency and reduce errors, or they can amplify existing operational weaknesses if deployed without proper integration. The 72% finding cited in the report underscores that most logistics companies have not yet achieved the level of process standardization and data consolidation necessary to make AI genuinely transformative. Without addressing the underlying manual workflows and system fragmentation, adding AI on top of broken processes may create new liabilities rather than improvements.

For supply chain professionals, this research highlights an urgent strategic consideration: technology investment must be paired with operational redesign. Organizations need to first consolidate fragmented systems, standardize data formats, and eliminate manual touchpoints before AI deployment can deliver meaningful ROI. The stakes are high—companies that fail to do this legwork risk deploying expensive AI tools that cannot access clean data or integrate with core workflows, wasting capital while competitors move ahead.