When asked, artificial intelligence defines itself as the capability of machines or software to perform tasks that normally require human intelligence, adding that it is designed to process data, identify patterns, and act on them—often improving over time without being explicitly reprogrammed. However, in the massive industry that is shipping, where the margin for error is minimal, can it be trusted? In the recently published Maritime Cyber Trends Report 2026 from Cydome, Katerina Raptaki of Navios stated that shipping companies are deploying AI faster than they are defining cyber accountability and that, in 2026, the question after an incident won’t be ‘was the AI wrong?’ but ‘why was it trusted?’ So, if we want to look at this from an analytical standpoint, we need numbers. And they show that the maritime industry’s accelerating adoption of artificial intelligence is sharply compressing the cybersecurity response window, with new data showing that up to 60% of newly disclosed software vulnerabilities are weaponised within 48 hours. The real opportunity is to rethink and simplify the underlying processes first and then apply AI That same Cydome report also found that the average time from vulnerability disclosure to active exploitation has fallen from 63 days in 2018 to five days in 2024. Today, AI-driven tools are targeting some systems within 15 minutes of a flaw being detected. The report also notes a 1,600% surge in voice phishing attacks and an 800% rise in assaults on edge network devices in 2025. A new white paper from maritime cyber specialist CYTUR warns that shipping’s digital revolution has outpaced its defences and that the industry is facing systemic cyber risk. The white paper claimed that maritime cyber incidents in 2025 surged by 103% compared to 2024, emerging as a critical threat to maritime safety. The Institute of Marine Engineering, Science and Technology (IMarEST), in its survey of 130 maritime professionals and in-depth interviews, found that around 80% of respondents believe AI can improve efficiency. However, it also found that 37% have personally witnessed AI failures. The report added that only 11% have any formal AI policies. Even though the numbers do look very problematic, IMO and BIMCO claim that AI-based threat detection reduces incident response times by up to 70%. Maritime organisations integrating AI-driven analytics also benefit from predictive maintenance and early warning of emerging cyber risks. But the point Raptaki was making was somewhat supported by Bob Doncom, chair of the IMarEST AI special interest group. He said that just because AI may arrive at an answer faster than a human, that answer is not necessarily correct. “The machine might be wrong, but if you don’t do anything in, for example, a rapidly evolving collision situation you’re wrong as well,” Doncom stated. However, he points out that people can cope with one, two, or three variables, whereas AI can handle seven, eight, or more, and all sorts of variables can be thrown in, with different scenarios run to see the likely outcomes. “Human in the loop is absolutely brilliant, unless you can’t afford the time. In rapidly evolving situations, such as collision avoidance, the volume of information and speed of events can overwhelm human operators,” Doncom said. Seafarers, like any human being, can only take so much input at once, and Doncom believes that as the situation gets more complex and the threat gets closer, humans may be just to