What happened
In a survey conducted in August 2026 with the Terminal Industry Committee 4.0 (TIC4.0), BCG assessed AI adoption across the global container ports and terminals ecosystem, drawing responses from 103 experts across five continents. The headline finding is a wide adoption-to-value gap: 'only 4% can show a gain in earnings' and just 11% systematically track AI's contribution to efficiency or margin, even though 44% of respondents have moved into scaling or a later stage. 'Unclear return on investment is the leading barrier to scaling AI, cited by 41% of respondents,' and the doubt runs deeper below the C-suite (44% vs 21% of senior leaders). Customers pull hardest — freight forwarders at 61% — yet only 18% report a better customer experience and 'nearly all of the gains stay operational' (74% cite improved operational efficiency). BCG recommends closing the gap in two stages: prove value before scaling and fix data foundations enterprise-wide, then shift spend to operational AI and co-develop services with customers.
Why it matters
This is a concrete quantification of the 'AI value' problem facing capital-intensive operating businesses: broad adoption and momentum but almost no measured earnings proof and a C-suite-to-frontline perception gap on ROI — a pattern that likely holds across industrial sectors, not just ports.
Action needed
If you lead a capital-intensive operations business, audit whether you can actually attribute a measurable earnings gain to your AI use cases, and fix enterprise-wide data foundations before scaling — then shift investment to operational AI rather than platforms.