AI rush fails to boost port earnings despite wider adoption, survey finds

A new Boston Consulting Group survey of 103 industry experts across five continents found that container ports and terminals are scaling artificial intelligence deployments, yet only 4% of respondents reported measurable earnings gains from the technology. The findings, published in October 2026 in partnership with the Terminal Industry Committee 4.0 (TIC4.0), expose a wide gap between operational adoption and documented financial returns.

While 44% of organizations said they had reached the scaling stage or beyond, just 11% systematically tracked AI's contribution to efficiency or margins. The survey assessed 43 AI use cases, with extracting data from shipping documents the most common application - 62% of respondents were exploring or implementing it. Predicting equipment failures in cranes and straddle carriers followed at 48%.

Operational wins that don't reach the bottom line

Respondents reported clear operational benefits. Improved efficiency was cited by 74%, faster decision-making by 44%, and cost reductions by 41%. But those improvements have not generally translated into documented earnings. An operator may identify faster workflows without systematically establishing how much those gains contribute to financial performance. Customer experience improvements lagged at 18%, suggesting adoption remains focused inward rather than on customer-facing services.

Uncertainty over return on investment was the most frequently cited barrier to wider adoption, named by 41% of respondents. Data quality followed at 32%, and 30% pointed to difficulties integrating AI with existing systems. The survey also revealed a split in perception: 44% of respondents below C-suite level identified unclear returns as a barrier, compared with 21% of senior leaders. The findings suggest that confidence at the top is not always matched by a clear business case for the teams deploying the technology.

Investment plans press forward despite unclear returns

Port operators continue to commit resources. Some 59% of respondents planned to hire or train AI specialists, 55% were allocating funding to research and development, and 47% planned to add AI modules to existing systems. BCG and TIC4.0 recommended that operators establish evidence of value before expanding deployments, using performance baselines accepted by the operational managers closest to the work. They also called for investment in shared data foundations across businesses rather than disconnected projects at individual terminals.

The report identified daily operational workflows as an area for future development. The share of respondents who saw AI integration into those workflows as beneficial was expected to rise from 60% to 74%. Interest in forecasting operational conditions and their causes was expected to increase from 49% to 67%. For professionals managing AI for Operations Courses, these findings underscore the need to connect technical capability with measurable business outcomes.

Customer demand as a route to value

Freight forwarders were cited by 61% of respondents as a source of demand for AI-enabled terminal services, followed by third-party logistics providers at 58% and container shipping lines at 52%. BCG urged operators to develop services alongside customers, linking technical capabilities to needs for which there is already commercial interest.

Why this matters for operations and strategy leaders

For executives overseeing ports, terminals, or logistics operations, the survey makes one point clear: scaling AI without a system to track its financial impact leaves money on the table. The 4% figure is not a failure of the technology - it is a failure of measurement. Operations leaders who build baseline metrics before deployment, and who require their teams to connect efficiency gains to margin improvements, will be the ones who turn AI pilots into documented earnings. The gap between 44% scaling and 4% seeing returns is a management problem, not a technical one.