Ports Are Scaling AI. Here’s How to Make It Deliver

The logistics and shipping industry is undergoing a transformation as artificial intelligence (AI) becomes more prevalent. Ports and terminals, once reliant on manual processes and human intuition, are now exploring AI's potential to streamline operations and improve efficiency. However, despite the growing interest in AI, a number of challenges remain that are hindering widespread adoption and realizing its full benefits.

In a survey conducted by BCG and TIC4.0, nearly 100 leaders from the container ports and terminals ecosystem were asked about their experiences with AI. The findings reveal that while AI is being adopted at a rapid pace, the industry is struggling to prove its value and fully integrate it into core operations. Only 4% of respondents could demonstrate a gain in earnings from AI implementations, indicating that while AI is being utilized, its impact on the bottom line remains largely untapped.

One of the main barriers to accelerating AI adoption is the unclear return on investment. While customers are demanding AI-enabled services, the benefits of AI are primarily being kept within the organization itself, rather than being fully realized in terms of financial gains. This lack of clear ROI is particularly pronounced among decision-makers who are not part of the C-suite, with 44% of non-C-suite respondents expressing doubt about the potential benefits of AI.

Data quality and talent are also significant concerns for those looking to implement AI. Without high-quality data and skilled personnel to manage and analyze it, AI systems may not perform optimally. This has led to a focus on building the necessary foundations, such as hiring and training AI talent, reskilling existing staff, and integrating AI with existing systems, rather than solely on the technology itself.

Despite these challenges, there is a growing recognition of the potential benefits that AI can bring to the industry. Respondents expect the next three years to bring value from AI in areas such as forecasting, dispatch, and workflow integration, rather than just in building platforms and governance frameworks. To fully unlock the potential of AI, it is essential for organizations to prove its value before scaling up, establish a solid foundation across the enterprise, shift spending from setup to operations, and co-develop the commercial upside of AI with customers.