A new survey of 103 industry experts has found that artificial intelligence is moving beyond trials in container ports and terminals, but measurable financial returns remain scarce.
While 44% of respondents said their organizations had reached the scaling stage or beyond, Boston Consulting Group reported, only 4% reported measurable earnings gains and just 11% systematically tracked AI’s contribution to efficiency or margins.
The findings highlight a measurement gap as operators expand their use of technology to process shipping documents, anticipate equipment failures and support operational decisions. Conducted in August 2026 with the Terminal Industry Committee 4.0 (TIC4.0), an international, non-profit association established in 2019 and based in Brussels, the survey covered experts across five continents, including terminal operators, port authorities, container shipping lines and port vendors. BCG published the findings in October.
The study assessed 43 AI use cases. Extracting data from shipping documents was being explored or implemented by 62% of respondents, while 48% were exploring or using AI to predict failures in equipment such as cranes and straddle carriers.
Respondents reported benefits primarily in day-to-day operations: 74% identified improved operational efficiency, 44% faster decision-making and 41% cost reductions. Just 18% reported an improvement in customer experience, suggesting that adoption has so far focused more on internal performance than customer-facing services.
Those reported improvements have not generally translated into documented earnings gains. An operator may identify faster workflows or reduced downtime without systematically establishing how much those improvements contribute to financial performance.
Unclear returns remain the biggest obstacle
Uncertainty over return on investment was the most frequently cited barrier to wider adoption, named by 41% of respondents. Data quality followed at 32%, while 30% cited difficulties integrating AI with existing systems.
The survey also revealed a divide between senior executives and colleagues closer to implementation. Among respondents below C-suite level, 44% 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 responsible for deploying the technology.
Investment plans nevertheless indicate continued interest. 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.
Moving from pilots to operational value
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 important area for future development. The share of respondents identifying AI integration into those workflows as beneficial was expected to rise from 60% today to 74%, while interest in forecasting operational conditions and their causes was expected to increase from 49% to 67%.
Customer demand could provide another 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 it matters: For ports, expanding AI deployment is only part of the task; operators also need reliable evidence that it improves the business.
Read more articles by Stuart Chirls here.
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