Artificial intelligence is coming to container ports and terminals, but its wider use has not yet yielded any significant, measurable financial returns. A new industry survey of 103 experts finds a huge disconnect between the boom in AI use cases and their impact on companies' bottom lines.

“Research conducted by Boston Consulting Group (BCG) in partnership with the Terminal Industry Committee 4.0 (TIC4.0) found 44% of respondents said their organizations were at or past the scaling stage. But only 4% said they had realized measurable earnings gains from AI, and only 11% said they were tracking the technology’s impact on efficiency or profit margins.

The results signal a growing challenge for port operators: to prove that technological progress does indeed lead to concrete business results.

The survey was conducted in August 2026, gathering views from professionals across five continents, including terminal operators, port authorities, container shipping lines and port technology suppliers. The study was published by BCG in October and was contributed by TIC4.0, an international non-profit association established in 2019 and headquartered in Brussels.

“Accelerating AI deployment in terminal operations

The research examined 43 possible uses for AI, and identified a number of areas where port operators are researching or already using the technology.

One of the most prominent use cases was the processing of shipping documents, with 62% of the respondents investigating or implementing AI-driven document data extraction. 48% of respondents were also interested in using AI to forecast equipment failures on machinery like cranes and straddle carriers, to plan for maintenance.

We are seeing more and more the benefits of operations Some 74% of respondents said they had improved operational efficiency, 44% said they had made faster decisions and 41% said they had reduced costs.

But such broad improvements in customer experience are not yet there. The hype notwithstanding, just 18% of respondents said AI had improved the customer experience, suggesting current implementation efforts are focused on improving internal processes rather than transforming customer-facing services.

But operational improvements don’t always lead to higher profits. Improved uptime and faster administration offer substantial benefits. Operators have no way of knowing how much these improvements are contributing to their bottom line without consistent measurement.

“The biggest challenge is the uncertainty about returns.

Interest in artificial intelligence is increasing, but uncertainty around return on investment is hindering broader adoption.

The biggest barrier, 41% of those questioned said, was the lack of clear financial returns. Data quality was the second most-cited issue, at 32 percent. Thirty percent said it was difficult to integrate AI solutions with current systems.

The research also found senior executives who sponsor the programs and the employees who actually implement them have different perspectives.

Non-C-suite respondents also were more likely to cite unclear returns as a key barrier to AI adoption (44 percent). By contrast, the percentage was 21% for senior executives.

This gap shows that confidence in AI in a strategic context does not always translate into a compelling business case for the teams charged with making these technologies a reality.

But there is a lot of intent to invest. Some 59% of respondents said they would hire or train AI specialists, while 55% said they would set aside funds for research and development. Another 47 percent intended to incorporate AI modules into existing systems.

Operators told to focus on operational value

For BCG and TIC4.0 the next phase of AI development must be about real results, not just how many deployments.

They advise building strong performance baselines before scaling AI initiatives and directly involving operational managers to define and validate the metrics for tracking improvements.

The groups also emphasized the necessity of creating common data foundations across enterprises. Operators need to move from siloed technology projects at individual terminals to more consistent data infrastructures that allow for greater integration and collaboration.

The use of AI is expected to be an increasingly important domain of daily operational processes . The proportion of respondents who consider the use of AI in everyday work processes to be beneficial is projected to increase from the current 60% to 74%.

The use of artificial intelligence to predict and explain operational conditions is also set to increase from 49% to 67%.

Such developments could enable ports to go beyond isolated pilot projects to more integrated systems that aid operational planning and decision-making.

New commercial opportunities could be opened up by customer demand

In addition to internal efficiency, customer demand could be another way for terminal operators to create tangible value from artificial intelligence.

61% of respondents cited freight forwarders as the strongest potential source of demand for AI-enabled terminal services. Third-party logistics providers followed with 58% and container shipping lines with 52%.

BCG therefore called on port operators to develop AI-based services together with their customers. The goal is to link technological capabilities to well-defined commercial requirements rather than presenting solutions that do not have an established market demand.

This could help turn AI investments into new service opportunities and strengthen the ties between terminals, logistics providers and shipping companies.

Why It Matters: The increasing use of artificial intelligence in ports and container terminals signals the industry’s push toward digital transformation. But adoption is not sufficient. Operators need to demonstrate that AI is a sustainable source of competitive advantage, with credible financial and operational benefits, and to overcome the challenges of implementation to encourage further investment.