Those born in the ’80s, like me, used to associate Artificial Intelligence (AI) with a futuristic idea driven by science fiction. However, the concept of AI emerged in the mid-20th century, when the first attempts were made to give machines capabilities comparable to those of humans (Turing, 1950).

The rapid growth of computing power, the availability of large volumes of data (big data), and advances in machine learning algorithms—especially deep learning—have driven development up to the present day. These advances have enabled machines to recognize images, translate languages, generate text, and make decisions with levels of accuracy previously unattainable.

Today, AI has ceased to be a fantasy and has become an integral part of our daily lives, often in imperceptible ways. From making queries to virtual assistants on mobile devices, receiving guidance on the best route while driving, to getting personalized recommendations on social media and streaming platforms, AI significantly influences our digital experience.

Although the implementation of artificial intelligence in the insurance sector is already a reality, its adoption in the maritime insurance field is progressing at a slower pace due to the particularities of a traditional, specialized, and less widespread industry. Nevertheless, there are cross-cutting applications as well as specific ones that are beginning to emerge in the market.

Efficiency on the High Seas

There is no doubt that one of the biggest leaps in AI, and one of the most publicized today, is chatbots with generative language models. These have improved customer service by providing immediate and personalized solutions. Current chatbots powered by this technology offer a much more natural and fluid interaction experience compared to older systems, which were limited to structured responses within a rigid script and often ended up forwarding the inquiry to a human customer service agent. Now, the new AI can understand more complex requests, provide guidance, and propose solutions to each user, thereby enhancing the customer experience. Combined with automatic processing of forms and documents, this reduces the approval times for new insurance quotes or renewals.

In claims management, AI automates the analysis of reports, detecting inconsistencies, missing documentation, and analyzing photos, with an efficiency that translates into faster settlements.

Recently, at the latest Alsum Forum in Spain (ALSUM, 2025), Claudia Bautista showed us that there are already insurance companies taking advantage of telematic devices installed on ships to monitor navigation behavior. This helps reduce claims and allows for better, individualized pricing, thanks to a better understanding of risk through real-time data.

Sailing in Turbulent Waters

The advancement of AI poses new challenges. Ethical issues, data privacy, and job automation are generating debates on how to regulate its development and ensure responsible use.

AI models trained on historical data can perpetuate biases. The new European AI Act (2024) requires transparency in “high-risk” decisions, such as a coverage denial. This obliges insurers to implement greater human oversight and improve the traceability of the algorithms used for risk assessment or premium determination.

Modern ships, as mentioned earlier, with hundreds of sensors and connected systems, can monitor navigation, machinery, and cargo. While this improves management, it also increases the opportunity for hackers to attack. Cybersecurity is therefore another urgent concern; the “NotPetya” incident that affected the shipping company Maersk in 2017 serves as a reminder of the growing risk.

Technological integration often clashes with the reality of many companies that still operate with legacy systems, which do not easily fit with modern solutions, whether due to technical complexity, economic constraints, or cultural resistance to change.

Added to this is the gap in specialized talent. We know how difficult it is to find experts in such a specific field as maritime insurance, and how much time it takes to train them internally. When you also consider the demand for AI and data management specialists, the challenge becomes even greater.

The use of AI in the educational process will be fundamental to developing the new skills required. AI literacy from schools should popularize its use, ensuring it is inclusive and equitable, and that no gaps are created that would prevent the effective use of these tools (UNESCO, 2025).

Augmented Intelligence, Not Replaced

As predicted by Leopold Aschenbrenner (2024), change is constant, and it is likely that the AI development we have seen in recent years will increase exponentially. Current news, such as the multi-billion-dollar investment recently announced by the U.S. government—including the construction of data centers, the promotion of semiconductor plants, and the improvement of the electrical system—combined with Nvidia’s new entry as a hardware provider to China, indicates that the race toward Artificial General Intelligence (AGI) has already begun.

AI will transform insurance underwriting, making it more accurate, efficient, and adaptable. Those who manage to navigate the path toward a healthy combination of AI with human expertise (Augmented Intelligence) will be more efficient and competitive, thereby improving profitability and customer satisfaction.

Even with this exponential development, in my opinion, AI or AGI will not eliminate the underwriter, but their role will need to evolve rapidly toward more strategic management, validating models and making decisions in increasingly complex situations.

At the end of the day, insurance is not just a data-driven contract; it remains and will continue to be a relationship of trust and fulfilled promises between people.

1. Turing, A. M. (1950). Computing machinery and intelligence.Mind, 59(236), 433–460.
2. ALSUM. (2025, 11 de junio). Memorias del Foro ALSUM Madrid.https://test.alsum.co/memorias_alsum/memorias-foro-madrid-11-de-junio-2025/
3. European Union. (2024). Artificial Intelligence Act. https://artificialintelligenceact.eu
4. UNESCO. (2025, 15 de abril). Inteligencia artificial y educación. https://www.unesco.org/es/digital-education/artificial-intelligence?hub=32618
5. Aschenbrenner, L. (2024). Situational Awareness: The Decade Ahead. https://situational-awareness.ai/wp-content/uploads/2024/06/situationalawareness.pdf