The Great Disconnect: Bridging the knowing/doing gap in logistics

Summary

Our 34th Annual Study of Logistics and Transportation Trends finds a persistent gap between recognising what’s possible and actually doing it across people, process and technology. A survey of 281 experienced logistics professionals surfaces five core disconnects: AI awareness without adoption; talent treated as a priority but under-supported; credentials valued but not funded or rewarded; strategy that stabilises rather than creates advantage; and technology that doesn’t work for the people who use it.

Key Points

AI tops the list of future drivers, yet only a tiny share of firms provide structured AI training or back organised experimentation.
Workforce challenges rank high, but only ~35% of companies have a dedicated learning & development function and career-path issues hinder retention.
External credentials are widely valued, yet few organisations cover costs, allow study time, or link certification to promotion/pay.
Many strategic responses have been reactive (hiring freezes, delayed investments) and overall performance remains largely unchanged from last year.
Practitioners want integration, automation, better UX, visibility and future-ready systems — but current tech often fails to deliver on these basics.

Why should I read this?

If you work in logistics, this is the survey you’ll wish your execs had read aloud in the boardroom. It’s short, blunt and full of the exact gaps teams keep tripping over — plus five clear, practical fixes to move from ‘we know’ to ‘we did’. Consider it a nudge (or a shove) to stop watching tech demos and start changing how people, processes and systems actually work together.

Context and relevance

This study matters because it comes from seasoned industry leaders (three in four respondents are director-level or above) and pinpoints where awareness isn’t translating into capability. The disconnect affects resilience, competitiveness and talent attraction at a time when AI, automation and shifting trade dynamics demand faster, more deliberate action. The recommended actions — small, targeted steps for AI readiness, L&D, certification support, outcome-focused strategy and user-centred tech — map directly to current industry priorities and can be implemented without huge capital outlays.