AI in Maritime Transport Market Projected to Hit USD 9.7 billion by 2033

Yogesh Shinde
Yogesh Shinde

Updated · Jul 15, 2024

SHARE: Scoop, we strive to bring you the most accurate and up-to-date information by utilizing a variety of resources, including paid and free sources, primary research, and phone interviews. Learn more.
Advertiser Disclosure

At Scoop, we strive to bring you the most accurate and up-to-date information by utilizing a variety of resources, including paid and free sources, primary research, and phone interviews. Our data is available to the public free of charge, and we encourage you to use it to inform your personal or business decisions. If you choose to republish our data on your own website, we simply ask that you provide a proper citation or link back to the respective page on Scoop. We appreciate your support and look forward to continuing to provide valuable insights for our audience.


According to, The AI in Maritime Transport Market is poised for substantial growth, projected to reach USD 9.7 billion by 2033, with a steady CAGR of 5.3% during the forecast period from 2024 to 2033. This growth is driven by the increasing adoption of AI technologies in the maritime industry, aimed at enhancing operational efficiency, safety, and decision-making processes.

The AI in Maritime Transport Market is experiencing significant growth, driven by the increasing need for operational efficiency and safety in maritime operations. Artificial Intelligence (AI) is being integrated into various aspects of maritime transport to optimize route planning, improve cargo handling, and enhance predictive maintenance, thereby reducing operational costs and increasing profitability. These advancements are further supported by the growing adoption of automation technologies in the shipping industry, which contributes to the market’s expansion.

However, the market faces several challenges. The high cost of implementing AI technologies and the lack of technical expertise are major hurdles. Additionally, concerns regarding data privacy and the security of AI systems pose significant barriers to adoption. Despite these challenges, there are substantial opportunities in the market. The ongoing development of autonomous ships and the increasing emphasis on reducing environmental impact present new areas for growth. Furthermore, as regulatory bodies continue to support digital transformation in maritime transport, the market is poised for further expansion. This supportive regulatory environment, combined with technological advancements, is creating a favorable landscape for the adoption of AI in maritime transport.

AI in Maritime Transport Market

AI in Maritime Transport Statistics

  • The AI in Maritime Transport Market is projected to reach USD 9.73 billion by 2033, with a CAGR of 5.3% during the forecast period. In 2023, the market was valued at USD 5.81 billion.
  • In 2023, the solution segment emerged as the leader in the AI in Maritime Transport market, securing over 68% market share.
  • Additionally, the cloud-based segment dominated the market, commanding over 55.4% of the market share.
  • The route optimization segment held a dominant position within the AI in maritime transport market, capturing more than 37% share.
  • Geographically, North America held a leading position in the AI in Maritime Transport market in 2023, capturing more than 33.2% share, amounting to USD 1.9 billion in revenue.
  • Maritime transport is vital to international trade and the global economy, serving as the primary mode of transportation for over 80% of the volume of international trade in goods. Developing countries, in particular, rely heavily on maritime transport for their trade activities.
  • The Artificial Intelligence (AI) market is projected to reach an estimated value of approximately USD 2,745 billion by 2032.
  • Similarly, the Global Maritime Security Market is expected to be worth around USD 50.8 billion by 2033, growing from USD 25.8 billion in 2023 at a compound annual growth rate (CAGR) of 7% during the forecast period from 2024 to 2033.
  • A significant finding in the maritime industry is that 70% of ships consistently fail to arrive on time. This highlights the critical need for enhanced operational efficiency and reliability within the sector.
  • As the maritime industry becomes increasingly digitally connected, the importance of robust cybersecurity measures cannot be overstated. A report by CyberOwl revealed that the average cyberattack in the maritime industry may cost the targeted organization USD 550,000. Moreover, ransom demands have surged by more than 350% over the past year, underscoring the escalating threat of cyber incidents.
  • Traditional data analytics typically examine only 10% of vessel data. However, advancements in AI models now allow for the processing of nearly 100% of vessel data. This capability provides accurate insights on crucial operational parameters such as fuel consumption, speed, trim, hull fouling, and power consumption, thereby significantly enhancing the efficiency and performance of maritime operations.

Emerging Trends

  • Autonomous Navigation and Operations: The maritime industry is increasingly adopting autonomous ships, which reduce operational costs by minimizing crew requirements and optimizing cargo space. This trend is contributing to more efficient global logistics and has the potential to significantly alter maritime operations​​.
  • Enhanced Cybersecurity Measures: As the maritime sector becomes more digitally interconnected, robust cybersecurity measures are crucial to protect against cyber threats. This includes safeguarding navigation systems and sensitive data to prevent significant disruptions and financial losses​​.
  • Integration of Satellite Connectivity: Satellite connectivity is improving communication and operations in maritime transport. This technology enables vessels to maintain continuous communication and access critical data, enhancing navigational capabilities and operational efficiency regardless of location​.
  • Adoption of Clean Energy Solutions: The shift towards low-carbon and renewable energy sources, such as electric and hydrogen propulsion, is prominent. This move not only addresses environmental concerns but also aligns with global decarbonization goals, reducing emissions and fostering sustainability in maritime operations​​.
  • Implementation of DataOps and Digital Twins: DataOps is revolutionizing the way maritime data is handled, enabling real-time insights and optimizing operations. Digital twins are also becoming vital, providing simulations and real-time analytics that enhance decision-making and training, thereby improving overall vessel and fleet management​.

Top Use Cases of AI in Maritime Transport

  • Predictive Maintenance: AI is utilized to predict equipment failures before they occur, significantly reducing downtime and maintenance costs. This proactive approach is transforming traditional reactive maintenance strategies​​.
  • Route Optimization: AI algorithms analyze numerous data points to optimize shipping routes, reducing fuel consumption and improving time efficiency. This is crucial for cost savings and enhancing operational efficiency​.
  • Cargo Management: AI enhances cargo handling through automated systems that streamline operations, reduce errors, and improve loading efficiency, which is essential for managing the vast quantities of goods transported globally​​.
  • Safety and Surveillance: AI-powered surveillance systems and collision avoidance technologies are increasing safety in maritime transport. These systems provide enhanced monitoring and proactive management of potential risks​​.
  • Environmental Monitoring: AI is used to monitor and analyze environmental data to comply with regulatory standards and reduce the environmental impact of shipping activities. This includes tracking emissions and implementing eco-friendly practices.

Major Challenges

  • Complexity in Integration: Integrating AI into existing maritime systems poses significant challenges due to the complexity and diversity of operations in maritime transport​.
  • Cybersecurity Risks: As the maritime industry becomes more interconnected and reliant on digital technologies, it faces increasing cybersecurity risks that could affect the safety and security of maritime operations​​.
  • Data Quality and Availability: Effective AI applications require high-quality and extensive data sets. In maritime transport, gathering and ensuring the quality of such data can be challenging​.
  • Regulatory Compliance: Navigating the complex landscape of international regulations regarding AI deployment in maritime activities continues to be a hurdle for industry stakeholders​​.
  • Cost and ROI Uncertainty: The high cost of implementing AI technologies and uncertainty regarding the return on investment can deter maritime companies from adopting these advanced solutions.

Market Opportunities

  • Enhanced Route Optimization: AI can significantly improve route optimization, reducing fuel consumption and delivery times, which is crucial for the efficiency of maritime operations​​.
  • Predictive Maintenance: Leveraging AI for predictive maintenance can help in anticipating equipment failures before they occur, thus reducing downtime and maintenance costs​​.
  • Safety Improvements: AI technologies enhance maritime safety by analyzing traffic patterns and historical accident data to predict and prevent potential hazards​​.
  • Operational Efficiency: AI applications in automated navigation, data analytics, and real-time decision-making can streamline maritime operations and enhance overall efficiency​​.
  • Environmental Sustainability: AI aids in reducing the environmental impact of maritime transport by optimizing routes and improving fuel efficiency, contributing to efforts in reducing greenhouse gas emissions​​.

Recent Developments

  • April 2024: NAPA announced a collaboration with a major shipping company to implement its AI-powered fleet optimization software, aiming to reduce fuel consumption and emissions across the fleet
  • March 2024: Kongsberg announced an investment of NOK 640 million to expand its missile production capacity, supported by both Norwegian authorities and the EU’s ASAP program. This expansion aims to meet increasing demand and is expected to enhance Kongsberg’s capability in the maritime sector​.
  • February 2024: Cargotec unveiled a new AI-driven cargo handling system that improves the efficiency and safety of port operations, leveraging machine learning to optimize loading and unloading processes.
  • January 2024: IBM launched a new AI-driven logistics platform designed to optimize maritime transport operations. This platform leverages real-time data and predictive analytics to enhance route planning, fuel efficiency, and cargo management.
  • June 2023: Windward introduced its AI-powered Maritime Domain Awareness platform, which uses advanced machine learning algorithms to provide real-time insights into maritime traffic, enhancing security and operational efficiency.
  • August 2023: MarineTraffic released a new AI-based predictive analytics tool that forecasts vessel arrival times and potential delays, improving logistics planning for shipping companies.
  • September 2023: ShipNet launched an AI-enhanced maritime ERP system that integrates various operational processes, offering real-time analytics and decision support to maritime operators​.
  • November 2023: BMT introduced an AI-based system for predictive maintenance in maritime transport, helping operators to proactively manage vessel maintenance and reduce downtime


The AI in Maritime Transport market is poised for transformative growth, driven by the need for enhanced operational efficiency, safety, and environmental sustainability. However, the path forward is challenged by integration complexities, cybersecurity concerns, and regulatory hurdles. Despite these challenges, the opportunities presented by AI, such as improved route optimization and predictive maintenance, promise substantial benefits. As the industry navigates these waters, the adoption of AI will play a pivotal role in shaping the future of maritime transport, making it more efficient, safe, and sustainable.

Discuss Your Needs With Our Analyst

Please share your requirements with more details so our analyst can check if they can solve your problem(s)

Yogesh Shinde

Yogesh Shinde

Yogesh Shinde is a passionate writer, researcher, and content creator with a keen interest in technology, innovation and industry research. With a background in computer engineering and years of experience in the tech industry. He is committed to delivering accurate and well-researched articles that resonate with readers and provide valuable insights. When not writing, I enjoy reading and can often be found exploring new teaching methods and strategies.

Request a Sample Report
We'll get back to you as quickly as possible