Artificial intelligence (AI) has existed as a concept since the earliest days of computing. Through a combination of poor funding and a general lack of computing power it has taken nearly 70 years of modern computing history for AI technologies to become viable for large scale adoption. Today, AI is used widely in many consumer and business sectors, and industrial sectors such as maritime are now showing significant growth in demand for AI systems.
AI is a sub-field of computer science that deals with the development of computer systems that can perform tasks normally associated with human intelligence. It is not one technology, but a combination of various different complementary technologies that allow the systems to function. Good artificial intelligence is capable of performing tasks either at a fraction of the cost and time of using humans to achieve the same goal or of performing tasks that are impossible for humans to complete.
Just as there are different types of human intelligence, there is a whole range of different types of artificial intelligence. These include digital twins, machine learning, knowledge based systems, neural networks, sensor fusion systems, and hybrid systems. Different system types are suited to different use cases, and it is important to choose the right tools for the job at hand.
In the maritime industry the adoption of AI has been growing gradually for a number of years, and has recently exploded. In 2022 the maritime industry is forecast to spend $931 million USD on artificial intelligence solutions. That figure is forecast to more than double in the next five years to $2.7 billion USD by 2027, a compound annual growth rate of 23%.
This rapid growth is driven in part by investment into the sector. In the last 12 months, $331 million USD has been invested in startups and SMEs developing AI solutions for the maritime sector, with a further $43 million in grant funding being awarded to develop the technology for the maritime sector around the world.
The use cases for AI in the maritime industry are wide ranging. They include supporting the operation of vessels through systems that can support autonomous navigation or voyage optimisation. They also include systems that can support the maintenance and monitoring of vessels including equipment health management, working alongside and supporting remote engineers, supporting safety data analysis, and the virtual commissioning of systems and equipment.
Ship operators who want to adopt artificial intelligence systems need to understand that the core premise that this technology is built on top of is learning from failure. AI has the potential to revolutionise maritime operations and create significant competitive advantages for those companies that embrace it. But the pathways to adoption are not straightforward. Though incredibly powerful, this nascent technology is still in the earliest days of adoption in the industry. This report includes recommendations to ship operators to ensure they have the best possible chance of success. These include working with the right data, buying in existing systems where possible, leveraging expertise to support developing systems, and creating a safe environment for testing new systems.