Sunday 14 Jul 2024
main news image

This article first appeared in Digital Edge, The Edge Malaysia Weekly on February 12, 2024 - February 18, 2024

The traditional logistics ecosystem can be described as the connection of numerous nodes in a supply chain, which can at times be vulnerable to gaps, lack of visibility and disruption.

The emergence of generative artificial intelligence (AI) could be a unifying factor that stitches together a more holistic value chain, offering greater optimisation and analytical insights to a myriad of stakeholders such as suppliers, manufacturers, distributors and retailers. For example, the integration of technologies such as Internet of Things (IoT), augmented reality (AR) and AI in logistics scenarios today has been a huge game changer, creating efficiencies and productivity boosts that were previously unimaginable.

Popularised by one of its more commonly used and widely known algorithms, ChatGPT by Open AI, generative AI has since risen to prominence with an accelerated pace of adoption, and the logistics industry is no exception. With a projected market growth of 5.25% annually between 2022 and 2027, the logistics industry in Asia-Pacific needs to capitalise on new technologies and opportunities available to differentiate themselves and reap the operational benefits.

With the vast application scenarios and diverse range of algorithms with different core functions, how can logistics operators maximise the adoption of generative AI technologies and leverage them for different use cases amid the increasingly competitive supply chain landscape?

Powering a smarter supply chain management

We are now witnessing the Logistics 4.0 era, characterised by cutting-edge technologies such as machine learning, automation and data analytics, which is further bolstered by the e-commerce boom.

To cater for surging e-commerce logistics demand, operators have ridden the digitalisation wave to scale their operations and elevate customer experiences. Against this backdrop, generative AI could very well be the linchpin to reshaping how logistics operators optimise AI-driven supply chains to meet evolving customer expectations and better access today’s global digital economy.

For one, generative AI can streamline decision-making processes by analysing large data sets to provide actionable insights and suggestions. It is already delivering significant improvements across routine logistics operations in areas such as demand forecasting for e-commerce logistics needs, delivery route optimisation and supply chain risk management, to bring about an overall increase in efficiency and productivity.

Without a doubt, the digital transformation in logistics will benefit immensely from the integration of AI into existing systems to unlock new opportunities. AI will free up bandwidth and resources in organisations to allow them focus on other critical aspects of the business that can drive growth and increase competitiveness.

Strengthening talent retention within logistics

Despite favourable growth projections and with the world’s largest working-age population, the Asia-Pacific logistics market continues to struggle with talent attraction and retention. This can be attributed to general stereotypes about the nature of the industry and workforce, owing to the perception that it is labour-intensive, with erratic work schedules.

Besides driving smarter supply chain management and augmenting the omnichannel customer experience, generative AI will also be an indispensable asset in revolutionising talent development and retention. For instance, generative AI simulations trained on a company’s data and practices provide new employees with contextualised responses to any queries on the job.

Similarly, generative AI-enabled automation not only streamlines workflows but also elevates employees’ productivity and job satisfaction. Ultimately, freeing employees from mundane tasks and empowering them with more strategic work helps foster a sense of fulfilment and motivation in the modern workforce. In the same vein, employees can stay abreast of the latest technologies and be competitive participants in the digital economy.

On the industry level, generative AI has the capacity to transform the future job landscape and elevate logistics jobs. Not only do we witness the emergence of new jobs, such as prompt engineers, to help businesses successfully utilise new technologies, but businesses are also exploring ways to diversify their workforce to remain future-ready and resilient.

When managed responsibly, generative AI can have great potential to redefine work for all, serving as a catalyst in revitalising the logistics talent pool.

The future of AI in supply chains

In the Asia-Pacific supply chain market, generative AI alone is expected to expand at the fastest rate between 2023 and 2032 compared to the rest of the world.

Logistics operators must embrace it as a strategic necessity to stay ahead of the curve and effectively navigate the evolving supply chain landscape. In fact, generative AI can serve as a co-pilot that addresses skills shortages, scale agility within organisations and among stakeholders and implement risk management policies to safeguard against external challenges.

The multifaceted capabilities of generative AI have the potential to revolutionise supply chain operations by making them agile, efficient and customer-centric. It can empower decision-makers, streamline training processes and act as a catalyst in forging new digital frontiers, all while optimising logistics and ensuring compliance.

Like it or not, this emerging technology will play a leading role in the future of supply chains, and logistics operators that are adaptable and willing to leverage emerging technologies stand to gain competitive advantages in the industry.

William Xiong is senior vice-president of the Cainiao Group, the largest provider of cross-border e-commerce logistics globally

Save by subscribing to us for your print and/or digital copy.

P/S: The Edge is also available on Apple's App Store and Android's Google Play.

      Text Size