US Companies Trail Their APAC Peers in Supply Chain AI Use Cases. Why?

Key Takeaways

1. 1

   APAC companies represent 10% of our 526-brand list but 22% of our AI use cases, suggesting a higher concentration of AI supply chain innovation in this region.

2. 2

   More than one in 20 supply chain job posts in APAC mention AI/ML skills, which is 50% more than supply chain job posts in Europe and twice as many as in North America.

Amid recent global volatility and disruption, companies are increasingly looking across borders to diversify operations – not only to improve manufacturing optimization but as an opportunity to learn from others who are experimenting and seeing success in relevant areas. 

A top-of-mind area for supply chain professionals is, of course, AI – a quickly evolving category of tools from which great value can be derived if implemented efficiently, effectively, and at scale. Zero100’s annual AI survey revealed that 86% of respondents don’t have an end-to-end AI strategy in place, yet certain regions are already outperforming others. Focusing in on APAC and North America in our use case library, we found that North America has only 29 genAI cases across 253 brands, whereas APAC has 22 genAI cases across 85 total brands – 2.3x as many. 

Let’s look more closely at what APAC leaders are doing to understand why their concentration of AI implementations is so high.

Firstly, APAC is deliberate about hiring for specific skills. According to our analysis, more than one in 20 supply chain job posts from the region mentions AI/ML skills – that's 50% more mentions than in supply chain job posts in Europe and twice as many when looking at posts in North America. And, in practice, these skills give rise to implementation. Asia-based companies, like Alibaba and Samsung, are specifically investing in LLM-driven generative models with their internal data to support teams across supply chain functions for increased productivity and efficiency gains.

Secondly, our research reveals that APAC countries are fertile grounds for AI talent, and people are, of course, a key enabler of successful AI strategy. For non-APAC-based companies, moving operations and hiring in these regions has become a way to secure AI talent, and Dell, HP, Nike, and others have all made recent moves to expand their APAC networks.

This surplus of AI talent and targeted strategies for hiring them for APAC teams will have influenced the number of AI implementations in the region. Among the companies leading the way in using AI for cost reduction and efficiency gains to attain ROI are Chinese tech company Lenovo and Japanese manufacturer Komatsu.

Lenovo: Production Planning 

Lenovo reduced PC production planning by 400% using AI. The flexible tool uses deep reinforcement learning and multi-objective optimization algorithms to effectively deal with large-scale combinatorial optimization by taking into account numerous key indicators, like the number of products, orders, order fulfillment rates, and production capacity utilization rates.

Komatsu: Demand Planning

Komatsu uses probabilistic range models matched to real-time processing to optimize multi-echelon inventory placement of components and spare parts across their global supply networks. This enables timely what-if scenarios in executive Integrated Business Planning (IBP) meetings and drives postponement options that improve inventory turns by up to 50%.

With this sort of ROI at stake, consider how you might fill gaps in your AI strategy with implementations like those we’re seeing in the APAC region and also reflect on your AI hiring strategies. Consider collaborating with Zero100 to to dive deeper into the best AI investments to gain ROI for your specific business and how to locate the right teams to operate that new tech. 

To see a different data cut or to dig deeper into this topic, reach out to our Head of Research analytics, Cody Stack, at Cody.Stack@zero100.com. 

Methodology

Zero100’s proprietary data and analytics are a combined effort between our data scientists and research analysts. We provide data-first insights matched with our own research-backed points of view and bring this analysis to life via real-world case examples being led by supply chain practitioners today.    

For this study, we analyzed 542 supply chain organizations across APAC, NA, LATAM, and EMEA, looking at publicly available mentions of AI usage. We also analyzed 2.4 million LinkedIn job posts from 100 B2C companies. Our analysis categorizes listings based on mentions of specific digital skills within job titles and descriptions.