Innovation, Agility & Technology

Unlocking Efficiency: How AI Streamlined Operations at MAC Container Line

5 Minutes read

A REF Artificial Intelligence Case Study

As a part of REF’s AI Curious community, we spoke with REF Member Brad Heier, President of MAC Container Line. We discussed how AI has transformed operational processes, addressed key challenges at the company, and how he sees it implementing AI solutions in the future.

Overview

MAC Container Line is a non-vessel operating common carrier (NVOCC) that contracts with shipping carriers to provide freight services to smaller and medium-sized shippers. The company acts as a freight middleman, booking space on carriers' vessels and reselling that space to their customers. Prior to implementing an AI solution, MAC Container Line’s primary challenge was efficiently processing documentation and data provided by their shipper clients into their own systems.

Challenge

Typically, when shippers send MAC Container Line documentation containing crucial details – such as container numbers, weights, and seal numbers – they do so in various formats, including Excel spreadsheets, Word documents, or Adobe PDFs. Brad shared that, before implementing an AI solution, manual data entry associated with processing shipping documents was one of the most time-consuming tasks for the team at MAC Container Line. Before the AI solution, the MAC Container Line team had to manually extract this information and input it into their systems. This was a labor-intensive and time-consuming process, not to mention prone to human error.

Artificial Intelligence (AI) Solution

MAC Container Line discovered that they could use the AI capabilities in Adobe Acrobat to automatically extract key data like container numbers, weights, and seal numbers from the lengthy shipping documents provided by customers. Brad shared that this allowed them to transform a 30-minute manual data entry task into a 1-minute automated process, improving efficiency and reducing errors.

Further Implementation

Following the success of their initial AI implementation, MAC Container Line began exploring further applications of AI-powered automation. In addition to Adobe Acrobat, Brad and his team have now also successfully implemented Microsoft's Co-Pilot tool to streamline other repetitive data extraction and processing tasks.

Concerns and Approach

Currently, MAC Container Line maintains a cautious and investigative approach to AI adoption within their organization, preferring to evaluate and implement AI-powered tools on a case-by-case basis. Despite the tangible benefits realized from the AI adoption within MAC Container Line, Brad remains mindful of potential challenges and risks associated with AI on a broader scale – including potential impacts on human creativity and caution regarding the risks associated with granting AI systems access to sensitive business data.

Conclusion

MAC Container Line’s successful integration of AI technology has enabled the company to better streamline operations, enhance efficiency, and mitigate operational risks associated with manual data processing. By embracing Artificial Intelligence (AI) selectively and thoughtfully, MAC Container Line remains poised to navigate the evolving landscape of freight logistics while maintaining a commitment to operational excellence and client satisfaction.