Theme: Digitalisation 
Industry Adoption: ⚫ ⚫ ⚪ ⚪ Early Adopters 
Impact: ⚫ ⚫ ⚪ Significant

A 2024 Maersk survey shows that decision makers rank Al 10th out of the top 15 trends.

Artificial Intelligence (AI) is reshaping the world as well as logistics in many ways. For example, it automates and optimises processes such as planning, procurement, and decision making. Generative AI enhances productivity and efficiency, enabling applications like vessel route optimisation that adapt to safety, weather, and energy factors. Moreover, by addressing disruptions such as changes in economic policies, weather and unexpected events, AI helps streamline operations and cut costs.

The logistics sector is the third-largest user of generative AI globally. This trend is advancing, though it is not yet a leading one. While startup activity remains limited, with just over ten relevant startups since 2015, innovation is robust. Between 2019 and 2023, more than 1,000 patents were filed, including over 700 groundbreaking innovations – a testament to AI’s transformative potential. Academic interest is strong, with approximately 2,500 publications, and C-Suite mentions increased from 130 in 2022 to 190 in 2024, indicating growing awareness. 

_{Average values of the top ten trends: Startups: 57; Patents 9,327 (thereof 316 groundbreaking); Science Publications: 6,141; C-Suite Mentions 1,376; More C-Suite mentions typically signal that trends are in the early or early adopter stage, while fewer indicate movement towards full integration or the industry standard.} 

Although the trend is widely discussed, it is still in the early adopter stage. Only 3% of respondents in our survey stated that the trend is fully implemented in their company’s logistics. Industry experts confirm that AI is relevant, but it is currently not “at the top” of company priorities.

Top 15 Trends

Share of Key Decision Makers, who consider the trend to be relevant for their company’s logistics

Artificial Intelligence – Relevance by Industry

What are the opportunities?

AI enhances demand forecasting, inventory management, and real-time decision making, enabling companies to operate more efficiently.  AI-powered predictive maintenance tools minimise equipment downtime by detecting early signs of wear, and optimising servicing schedules before failures occur. Route optimisation systems analyse factors such as traffic patterns and weather conditions to minimise delivery times and fuel consumption. Generative AI unlocks actionable insights from vast datasets, helping businesses optimise supply chains.

What are the challenges?

Talent shortages and cultural resistance complicate efforts to deploy AI effectively. Additionally, current computing power struggles to process vast data volumes – for example, the numerous variables in demand planning - exceed the capabilities of today’s computers. To overcome these barriers, companies must invest in infrastructure, workforce training, and strategic planning to ensure smooth implementation.

Sources:

• Statista (2024).
• Survey among 500+ global logistics decision makers across various industries, conducted by Statista for Maersk (Q4 2024).
• In-depth interviews with global industry experts, academia, and futurists.
• Unstructured web sources with more than 10,000 search term permutations using AI.
• Curated data from startup databases, patent databases, and analysis tools, as well as Semantic Scholar.