Publication: Express Computer

In an exclusive interview with Express Computer, Kapil Mahajan, Global Chief Information Officer, Allcargo Logistics Ltd., provides insights into the profound impact of digital transformation on the logistics and shipping industry. The interview delves into Allcargo Group’s pivotal role in shaping the evolution of the sector and its commitment to leveraging cutting-edge technologies.

The logistics industry, traditionally slow in technology adoption, witnessed a significant paradigm shift in recent years. Kapil Mahajan emphasises the industry’s recognition of technology’s pivotal role, particularly amid the COVID-19 pandemic. Allcargo Group stands out by not only following industry trends but by strategically investing in digital interventions to enhance operational efficiency and overall business agility.

How has digital transformation specifically impacted the logistics and shipping industry, and what role has Allcargo Group played in shaping this evolution?

Traditionally, the supply chain and logistics industry, both in India and globally, has not been inherently digital-native, lagging in technology adoption. However, a significant shift occurred in recent years, notably pre-COVID, during the pandemic, and post-COVID. Businesses started recognising the pivotal role of technology and digital interventions in the industry. In India, many organisations embarked on this digital journey, with some already achieving maturity. Globally, beyond a few major players, a widespread trend of substantial investments in digital initiatives emerged, introducing industry-first use cases in the past three to four years. In our specific case, we have dedicated substantial efforts and resources to digital interventions, focusing not merely on following the trend but rather on enhancing operational efficiency and overall business agility.

Given the low-margin nature of our industry, interventions that impact cost reduction, process efficiency, and reduced dependency on manpower hold significant value. Recognising this, we have established a Chief Digital Officer role, leading a team dedicated to digital-first projects. We have not only adopted digital at the surface but also strengthened core systems to align with the digital ecosystem comprehensively. It is crucial to integrate digital transformation at all intersection points, emphasising its impact on the bottom line. At Allcargo, our substantial investments in technology have resulted in the digitalisation of numerous processes.

Digital intervention is an ongoing journey, encompassing AI, machine learning, and more recently, generative AI. While translating these technologies into mainstream business practices requires research, development, and proof of concepts, we are committed to this investment. From a group standpoint, our vision is to infuse digital capabilities across every business process. For instance, our group company, Bathy, is pioneering the development of a cloud-native ERP, a first-of-its-kind in the industry, representing a long-term investment aimed at transforming logistics practices in India.

In what keyways you are leveraging artificial intelligence and machine learning to optimise the logistics operations and enhance overall efficiency?

In the past four years, I have strongly advocated for the idea that every business process will evolve into a cognitive one, a vision that is materialising today. Beyond just a few use cases, mainstream AI is expanding its reach, and it is imperative to democratise AI, making it a competitive tool in the hands of operational users. This goal aligns with ensuring that every process becomes smarter, augmented, and cognitive. An example is the adoption of Computer Vision, a form of AI, to handle unstructured data like videos and images in our logistics operations. For instance, our computer vision model automates the interpretation of delivery documents, enhancing efficiency by eliminating manual data entry.

Another application involves the use of AI in proof of delivery processes, improving the cash flow cycle by enabling real-time verification and immediate invoicing. Fleet optimisation is also enhanced through AI, optimising vehicle placement at cross docks for more efficient loading and unloading. Also, AI and machine learning assist in determining optimal routes for last-mile deliveries based on locational data. To democratise AI further, we have incorporated offline AI capabilities, utilising edge computing applications that work offline, ensuring functionality even in areas with limited connectivity. We have focused on tailor-made AI solutions, deploying cloud-based models globally and offline models within India, catering to specific operational needs. While some use cases remain confidential, these advancements underscore our commitment to leveraging AI and machine learning to enhance operational efficiency and drive innovation within the group.

Given the rise of generative AI, how do you see its potential applications in the logistics domain, and have you explored any specific use cases for generative AI?

Currently, our utilisation of generative AI is in an experimental phase, with a specific focus on improving our HR processes. We recently introduced a generative AI-powered conversational bot designed to handle HR documents. The model is trained on a diverse range of HR policies from our three major entities—Allcargo, ECU, and Gati. When a user poses a question, the model generates responses by extracting relevant information from the documents, utilising generative AI. The primary objective is to enhance the employee experience by enabling the generative AI to promptly address common queries related to leave policies, medical benefits, and other HR-related matters.

This initiative aims to alleviate the workload on HR personnel, allowing them to focus on more complex tasks. Additionally, we are exploring other use cases, such as content creation, leveraging GenAI. However, we are mindful of potential copyright issues and are working with partners like GCP and Amason to train the model on our datasets. While the adoption is gradual and teams are still in the learning phase, the HR bot has shown promising results, laying the foundation for broader applications of GenAI within the organisation.

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