Recent research shows that ٦٣% of maritime professionals use artificial intelligence (AI) daily in their work. However, only ٨% of them recognize their organization as a mature entity with governance in the use of AI.
Costs of Validation and Trust in AI
More than half of the participants (٥٥%) spend at least one hour a week reviewing or correcting outputs generated by AI, and nearly one-fifth of them dedicate five hours or more to this task. However, ٨٥% of these individuals have stated that using AI ultimately saves them time.
The so-called “validation tax” report refers to the time and attention spent reviewing AI-generated work. The main question is how much of this validation is necessary. Trust in AI-generated outputs is still growing; ٥٧% of individuals are in the middle of a five-point scale.
Challenges of Trust and Review
Some reviews are likely to be unavoidable. Seven out of ten say they always review an AI suggestion before acting on an important business decision, while ٨٠% believe that a specific person should always be responsible for a business decision, no matter how capable the AI is.
The majority of respondents encounter errors while reviewing AI outputs, and less than one in ten says that their organization’s data is fully ready to rely on AI. If experience shows that an AI output is reliable, ٤٧% said they would spend less time reviewing it.
Future Opportunities and Challenges
The report states that the opportunity lies in not eliminating human oversight but keeping it proportionate: maintaining oversight where the consequences of mistakes are critical while reducing unnecessary reviews. For example, the CP Optimiser tool, which is a lease contract review tool, has been jointly developed by Marcura and Tomini Chartering. This tool analyzes contracts with the accumulated knowledge of the company and highlights clauses and risks that may need to be identified by an experienced colleague.
The CEO of Tomini Chartering, Thomas Stearn Holm, described this system as a “collective brain” for the organization and emphasizes that it is a human-to-AI and back-to-human process: humans input knowledge, AI gathers it and connects it to the relevant clause, and then humans make the final decision.
The conclusion of this report is that companies should measure the complete human and AI process, differentiate necessary validations from reviews arising from uncertainty, use human corrections to improve future performance, and establish clear ownership and governance.
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