Since the Asia-Pacific (APAC) region is the linchpin of global trade, technology innovations that materialize there have a percussive, far-reaching impact. Artificial intelligence is no different. Supply chain leaders who implement it for enhanced supply chain risk management (SCRM) will see substantial, lasting improvements.
Why managing supply chain risks is advantageous
No organization is immune to extreme weather events, poor supplier performance, geopolitical issues, workforce shortages, and demand fluctuations. Supply chain risks affect everyone, from the smallest business to the largest enterprise. Since the APAC countries are central to global trade, they know this fact all too well.
A tremendous amount of goods moves through the APAC region. McKinsey & Company states that Asia alone makes up over 50 percent of global trade value, 22 percent of which involves the continent on both ends. Since so many trade routes converge here, disruptions are impactful. Despite the gravity of the situation, many organizations are ill-prepared to handle disruptors.
This pain point stems from limited transparency throughout supply networks. According to one recent survey, real-time, end-to-end visibility is only a reality for just over 50 percent of logistics organizations in the APAC region. How are they supposed to deploy effective SCRM strategies if they can’t even identify potential risks?
There is a silver lining. Although addressing this issue requires time and effort, doing so is advantageous. Minimizing risk increases uptime, improving companies’ on-time rate and preserving brand reputation — no more worrying about the risk of downtime-related losses or premature contract termination that stems from being underprepared.
With an AI-driven SCRM strategy, business owners can identify and assess the impact of risks sooner, reducing disruption-related revenue losses and freight expenses. In addition to controlling costs, they may improve their compliance and agility, granting them a competitive advantage in an oversaturated market.
How an AI SCRM solution generates business value
What’s better than proactively mitigating possible risks? Knowing precisely when they will occur. While a preventive tool is great, a predictive one is better — that is why AI analytics outperforms similar solutions.
Intelligent algorithms can recognize shipping patterns and business trends that humans can’t. These demand forecasting capabilities enable professionals to anticipate demand for equipment, workers, or products, helping them meet their clients’ needs more consistently. Ultimately, they improve business continuity and gain a competitive advantage.
No tool outputs more relevant, accurate predictions than an advanced, well-trained AI. Despite being an out-of-the-box solution, its training dataset enables it to meet business-specific needs. Supply chain professionals are not restricted to typical off-the-shelf strategies.
These benefits are likely why chief executive officers (CEOs) have adopted supply chain technologies. A PwC survey revealed that around 43 percent of APAC CEOs invested in supply transformation in 2023, slightly above the global average of 41 percent. Analysts expect this trend to continue, with AI leading the charge.
For instance, the International Data Corporation predicts six in 10 A2000 supply chain companies will utilize AI for dynamic shipping and supply network optimization by 2028, reducing response times by 75 percent and transportation spending by 5 percent. By 2029, they will achieve an estimated 20 percent efficiency gains.
Supply chain leaders can use AI to enhance SCRM
AI technology can enhance most, if not all, SCRM approaches. For example, a generative model can improve communication between business owners, suppliers, and logistics partners, reducing miscommunications and delays. Keeping everyone informed on the latest incident response strategies helps them react in concert.
The most impactful application involves predictive analytics. An algorithm can anticipate the likelihood and severity of disruptions by identifying patterns and trends that are challenging — or even impossible — for humans to notice. For example, it can recognize when a purchase order is about to be delayed or an extreme weather event will block a port.
With this knowledge, supply chain professionals can minimize the impact of disruptions. If they need help, a large language model can offer alternative trade routes or contingency plans, enabling them to pivot immediately.
This technology offers what few similar solutions can — transparency into an organization’s extended supply network. Regardless of whether they have a handful of suppliers or rely on thousands of vendors, an advanced algorithm can identify, assess, and monitor risk. This is why it is such a valuable asset.
Of course, a successful integration requires strategy. Adrian Johnson, the vice president and general manager for Hitachi Vantara APAC, believes the rapid proliferation of AI in Asia is inevitable. He states the region’s markets demonstrate “AI can transcend pilot projects” if leaders recognize that “data availability, security, quality, and governance” are non-negotiable.
Improving supply chain resilience with AI technology
Unlike other SCRM solutions, a machine learning model is not limited to analyses or document retrieval. It is dynamic, flexible, and individualized, enabling it to react to the ever-evolving world of logistics without missing a beat. Early adopters of this technology will benefit substantially, giving themselves a competitive edge in an oversaturated market.
Zac Amos is the Features Editor at ReHack, where he covers business tech, HR, and cybersecurity. He is also a regular contributor at AllBusiness, TalentCulture, and VentureBeat. For more of his work, follow him on Twitter or LinkedIn.
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