In today’s dynamic maritime industry, advanced technologies like artificial intelligence (AI) are shaping the future of decision-making, operations, and sustainability. I got the chance to hear from Jan Simon, VP of Digital & IT at Hafnia, about how AI in maritime is transforming operations, the challenges of leveraging complex datasets, and the roadmap for building a resilient and efficient enterprise.
Nick Emmett: What is the potential for AI to transform decision-making in maritime organizations?
Jan Simon: I’d say the potential is very high. AI has the capacity to revolutionize decision-making in maritime organizations by offering predictive and prescriptive analytics, which can improve efficiency and profitability. Leveraging historical datasets and real-time information, advanced algorithms can forecast market trends by predicting fluctuations in market prices and fixture rates to help organizations position their fleets effectively. When it comes to operations, AI could analyze datasets like operational P&L and bunker prices to identify cost-saving opportunities and improve voyage planning. In terms of risk mitigation, AI could provide quick insights into market volatility and operational risks to allow for more informed, data-driven decisions.
Nick Emmett: What would you say are the biggest challenges with managing and analyzing complex datasets?
Jan Simon: There are definitely some challenges. The first one is data silos—when your systems aren’t connected, it’s hard to integrate everything seamlessly. Then there’s data quality. If your datasets are inconsistent or incomplete, it really undermines the effectiveness of your AI models. Scalability is another issue, especially as the volume of data keeps growing, as it requires robust infrastructure. Another is conducting real-time data analysis —that’s always a tough one because you want speed, but you can’t compromise on accuracy.
To overcome these, we’ve been focusing on unified data platforms, better data governance practices, and scalable, cloud-based solutions. Once you address these issues, the payoff is huge. You get timely, accurate, and actionable insights that give you a real edge.
Nick Emmett: What do organizations need to build the right AI-ready data infrastructure?
Jan Simon: The first step is investing in scalable infrastructure—cloud-based systems are key because they’re flexible and can grow with you. Data governance is another big one, as I mentioned. You need clear policies to ensure data quality, security, and accessibility. Integration platforms are also important because they let data flow seamlessly across different departments and systems. And of course, you need real-time data access. IoT and advanced analytics tools make that possible.
As for historical data, it’s critical. That’s what trains your AI models to recognize patterns and trends. Without it, you don’t have a solid foundation for predictive and adaptive capabilities. By combining historical data with real-time insights, you can create systems that are both robust and adaptable to market changes.
Nick Emmett: As AI in maritime becomes more prevalent, how should organizations approach ethics, data governance, and the balance between automation and human oversight?
Jan Simon: Taking a proactive approach to ethical considerations and governance is really important as we integrate AI. Transparency is key—we need to clearly explain how AI-driven decisions are made. Bias mitigation is another area we focus on, and it’s essential to regularly audit algorithms to minimize the ever-present risk of them becoming skewed. And we certainly do not want to lose the essential human element. AI is a tool, not a replacement for the expertise of our teams, so we need to maintain a collaborative approach where the two are complimentary. To ensure proper data privacy, we adhere to global standards like GDPR for handling sensitive information.
Ultimately, it’s about building trustworthy AI systems and balancing them with human oversight for responsible and ethical use.
Nick Emmett: What AI trends do you think will shape the industry? Is there anything specific that excites or worries you?
Jan Simon: There are so many exciting trends right now. Digital twins are a big one, which provide real-time simulation models for vessel performance and maintenance. Autonomous shipping is another, which can improve navigation and operational efficiency. AI-driven sustainability is also gaining some momentum, helping to optimize fuel consumption and monitor emissions.
And we’re very interested in natural language processing—it could be a game-changer for analyzing contracts and communications. This potential for AI to drive sustainability and make operations more efficient is really intriguing. But at the same time, there are concerns around cybersecurity and the risk of losing human expertise as automation becomes more prevalent. It’s a balance we’ll all need to manage carefully.
Nick Emmett: How is Hafnia using AI in the near term to improve decision-making?
Jan Simon: We’re actively developing AI at Hafnia to improve decision-making across the board. One example is voyage optimization. Our AI models analyze a range of variables, like bunker prices and weather conditions, to suggest optimal routes. This helps us reduce fuel consumption and improve our efficiency. We’re also using AI for predictive maintenance, helping us identify potential equipment failures before they happen and minimize downtime and repair costs. We’re also using advanced analytics to give us a better understanding of market trends and insights so we can make smarter chartering decisions.
Our goal is to integrate AI into broader aspects of our operations to enhance efficiency, achieve sustainability compliance, reduce costs, and maintain a competitive edge.
Data Strategy for a Decision Advantage
Hafnia’s forward-thinking approach to AI demonstrates the transformative power of data-driven decision-making in shipping. By addressing challenges head-on and embracing innovative technologies, they’re setting the business up for operational excellence into the future to gain a decision advantage.
There are also external solutions that can play a key role in supporting a maritime organization’s data strategy, such as IMOS Data Lake. Data Lake securely stores complete historical records of an organization’s data, ensuring data is fully standardized and searchable to power advanced analysis – such as with the use of AI – and better decision-making.
Learn more about Data Lake and get in touch with one of our experts here.
About Jan Simon, VP of Digital & IT at Hafnia
Jan Simon is the Vice President of IT and Digital at Hafnia, where he has led the company’s digital transformation since April 2018. Based in Copenhagen, he oversees IT strategy, technology road mapping, digital innovation, and cybersecurity for the global product tanker company. His work focuses on leveraging technology to deliver measurable results in complex organizational settings