Study Reveals Shipping Companies Embrace AI Pilots, Yet Struggle With Scaling and Trust

A new study shows shipping companies are excited about artificial intelligence but still wary of its risks. While many see efficiency gains, others warn of “misplaced trust”; “poor implementation”; and overreliance and the loss of human judgment. The challenge is moving from pilot projects to meaningful adoption.

Artificial intelligence (AI) is moving fast into the maritime sector, long known for its slow pace in adopting new technology. A new report (Beyond the Hype: What the Maritime Industry Really Thinks About AI…. And Where They’re Making It Work) by Thetius, in partnership with Marcura, suggests that shipping companies are in rapid shift in AI adoption, from 10-15 years as a standard into just 2 to 3 years.

The survey of 130 maritime professionals and multiple in-depth interviews across the industry shows that optimism is high. 82% believe AI can improve operational efficiency and reduce workloads. 81% of respondents say their companies have already launched pilots or small-scale projects.

Yet only 11% have a formal policy to scale AI. Most are stuck in the experimental stage who are unable to fully integrate new systems into core operations. A further 18% are still exploring AI with limited hands-on experience.

The benefits of AI are not in doubt. 97% of respondents said the technology is useful for reducing manual workflow inefficiencies, including “augmenting inboxes to automatically flag key data”. 87% said it helps in analyzing charter party contracts, while 85% pointed to its usefulness in both voyage operations and regulatory compliance monitoring. 

For some executives, the promise is transformative. “AI is a real value. It is not just a technology. It is solving actual pain points faster, smarter, and at scale,” said Theofano Somaripa, Group CIO at Newport S.A.

At the same time, optimism does not always translate into readiness. Only 23% of companies are training staff to build confidence in AI. Even fewer, 17%, are being transparent about how AI makes decisions inside their organization. This requires both stronger governance and education because early excitement risks stall before meaningful adoption.

A chief engineer for a shipping company with between 251 and 1,000 employees admitted he was unsure about AI’s role in his job. He said he was “somewhat optimistic about AI but unsure about how it could or should be used” within his role. This uncertainty reflects a broader gap between leadership vision and frontline reality.

Trust and Human Resistance

The report highlights that the biggest blockers to AI adoption are not technical, but human. 66%of respondents worry that overreliance on AI will reduce human skills and oversight. 37% had personally witnessed an AI project fail. The study suggests that the industry is learning from mistakes rather than abandoning AI entirely.

“Many operators fear losing control. They’ve spent decades honing their judgment in high-stakes roles like chartering and operations. So when AI is introduced, there’s a perception that machines are taking over, not assisting,” said Janani Yagnamurthy, Vice President of Analytics at Marcura.

These concerns are especially strong in high-responsibility jobs. Charter managers, operations managers and captains often see autonomous systems as a threat to their expertise. Even when AI is only making recommendations, many feel it is the start of a slippery slope where human judgment could be sidelined.

In commercial roles, the fear is about losing “human touch”. “In the shipping industry there is still that feeling of the person, the face-to-face relationships and not just the computer,” said Giuseppe Oliveri, Director at d’Amico.

For seafarers, the disconnect is ever broader. Steven Jones, Founder of the Seafarers Happiness Index, said that AI is still largely absent from day-to-day shipboard operations. Sales teams may promote new solutions, but crew often face the burden of figuring out how to use them under time pressure. “Salespeople sell a dream… and then time-stressed seafarers are left trying to unbox and make it work,” Jones said.

Trust issues also stem from experience. A master mariner with more than two decades at sea said he lost faith in AI tools after incorrect data filtering led to poor results. “The systems were lacking. While the intentions were good, the data wasn’t being filtered properly and it was leading to incorrect information output,” he said.

Part of the problem, the report argues, is misleading language. Referring to systems as “intelligent” or “autonomous” risks over-trust. In reality, most maritime AI is predictive but not autonomous, and depends on data quality. As one ship manager explained, the danger is in treating AI as smarter than it is. “People train their AI models but they don’t train their people. If the crew and the office do not understand the AI outputs, it could lead to misuse, which creates mistrust. We need to first train our people and our minds,” he said.

The emotional side of adoption also matters. Workers who see themselves as “pilots” of AI and actively steer the technology, are more productive and loyal than those who feel like “passengers.” Building this pilot mindset is crucial to bridging the trust gap.

Risks and the Road Ahead

Beyond emotional resistance, there are practical concerns about the risks of AI in maritime. The most common involve data privacy, job displacement, regulatory uncertainty and overhyped vendor claims.

61% of professionals cited cybersecurity and data breach vulnerabilities as their biggest concern in implementing AI in maritime operations. Many fear that uploading sensitive charter party or voyage data into generic AI systems could expose confidential commercial information. Insecure practices, such as pasting data into open platforms, increase this risk.

Job loss remains a sensitive topic. 15% of respondents said they were very concerned about AI replacing roles, while another 23% said they were somewhat concerned. A maritime consultancy manager with more than 20 years of experience warned, “In five years, it may well make me redundant (or looking for a new job!).”

Yet some executives view AI differently. A CEO said he was not looking to cut headcount but to “handle 2x the business with the same headcount.” Others stressed that AI should be seen as a way to automate repetitive tasks. Ai will be freeing staff for higher-value work.

Vendor hype is another major stumbling block. Nearly a quarter of respondents said they distrust vendor claims, and 37% have seen AI projects fail or cause harm. Some companies have cut ties with suppliers after finding tools did not match operational needs. Transparency is seen as the solution. “The vendors walked us through everything… They answered every question, and that openness built the trust we needed to move forward,” said Ha Eun Ruppelt, a Maritime Transformation Advisor.

The danger of AI “hallucinations” is also large. Without maritime-specific training, generic AI tools can misinterpret terms. Yagnamurthy of Marcura offered a telling example. “A general AI agent might say that SF means standard form, but in shipping, it means storage factor,” she said.

The report suggests that vertical AI, built on maritime data and workflows, will be key to avoiding these pitfalls. Companies that develop context-specific solutions will gain faster trust and adoption.

For now, most shipping firms remain at the pilot stage. 81% are experimenting, but only a third have progressed into full adoption. Without clear policies, training, and leadership support, the industry risks moving too quickly on hype, or too slowly out of caution.

“AI will be a part of our life, like it or not. In a few years, we could not imagine how life was before AI implementation, like we cannot imagine how to live without electricity,” said Newport S.A.’s Somaripa.

The study concluded that “AI in maritime is no longer just a technical project. It is a governance, cultural and communication challenge. The companies that succeed will be those that combine transparency, leadership, and industry-specific solutions, while keeping human expertise at the center of decision-making.”

source : thedigitalship