Southeast Asia has emerged as a crucial focus for industries aiming to diversify their supply chains in response to US-China trade tensions and sluggish growth.
This diversification has benefits for Singapore as it continues to have more companies from Microsoft, Google to Rolls-Royce and TikTok as well as Shein set up regional headquarters in Singapore, which is seen as a stable base amid geopolitical headwinds.
The semiconductors industry in Singapore has also reached its peak; Singapore has become the largest production hub outside the United States for US firms like Applied Materials and Micron.
However, with supply chains constantly being disrupted, Singapore needs to focus on technological innovations in the supply chain space.
Across all industries, AI is being sought after as a critical tool to augment human intelligence and support risk mitigation strategies around these sorts of issues and drive the most intelligent supply chains on the planet. And with businesses more vulnerable to disruptions than ever before it’s never been more needed.
In fact, a report by IDC states that by 2026, 60 per cent of the top 2000 companies will use generative artificial intelligence (Gen AI) tools to support core supply chain processes.
AI technology isn’t simply a plug-and-play solution, however. To get the most out of AI, companies need to abide by a few guiding principles.
AI should augment humans
The achievements of AI in the past couple of years are nothing short of incredible, which is why it’s easy to forget the things that machines cannot provide, which are called the three C’s: context, collaboration and conscience.
Models cannot derive meaning from context, critical in so many areas of the supply chain, nor can they work together to solve problems, including addressing issues like sustainability or human rights in supply chains.
This is why AI should augment humans. The most powerful combination is for humans and AI to work together, a belief reflected in a Workday survey of decision-makers, 93 per cent of whom believe in the importance of keeping the human in the loop when AI is making significant decisions.
Concurrency and AI can transform supply chain management
Supply chains connect many functions across a company and beyond, which is why optimising one link doesn’t optimise the entire chain. For example, AI can greatly increase the accuracy of forecasts, but we want more than highly-efficient silos. The power of AI on its own is not enough.
Also Read: Leveraging AI and ML in supply chain management for smarter decision making
The real breakthrough is not from AI but with concurrency, which integrates AI in the workflow to align decision-making across the supply chain for faster response.
We want AI for its ability to predict with greater precision, speed, and elegance, and we need concurrency to connect supply chains for better, faster response, no matter what the conditions are.
The bottom line is AI embedded in concurrency leverages predictions while absorbing the volatility we cannot predict from the inevitable disruptions our supply chains will always face.
The power of AI must be democratised
For AI to realise its potential, everyone must be able to use it. We will always need experts to explore new ways to apply AI, but empowering businesses to adopt it themselves is crucial to realising its true power within the supply chain industry.
For this reason, the best solutions are the ones which don’t require technical proficiency in AI or data science in order to use in your day-to-day role.
If solutions are designed for someone with supply chain context and business knowledge, they can “consume” the results of a model without knowing how to build it. Democratising AI in this way ensures its use, so choose to work with a provider who allows you to start from where you are and evolve.
AI solutions are not exactly black and white
Many AI solutions come in a black box that even data scientists struggle to unpack. This is bad for visibility, but it can also be bad for adoption; businesses are ultimately responsible for their forecasts and, if they can’t explain how an AI platform is helping them to make their forecasts, they might think twice before trusting it.
In fact, researchers have found that humans are more forgiving of what they perceive to be error on the part of fellow humans than they are from machines, a trait that can lead to them to develop “algorithm aversion”.
One approach to overcoming this aversion is state-of-the-art techniques that make black box AI models more understandable. For example, explainability techniques such as feature attribution methods can be used in demand sensing to help a planner see how adding a signal like weather affects predictions.
Creating AI solutions that we can understand goes hand in hand with democratisation and, ultimately, will help improve adoption across the supply chain industry.
In conclusion
It’s clear that AI is transformative for the supply chain, and it’s fascinating to envision an industry augmented by this exciting technology.
As we ramp up our use of AI, though, we need to remember that the trick to getting the most out of it is by adopting a human-centred approach. When AI is embedded across the end-to-end supply chain, expertly fusing the best techniques available, we can reimagine what is possible in our supply chains.
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