The Continued Rise of AI and ML in Supply Chain Optimization

Welcome to Part One in a 7-part series on the top seven supply chain trends for 2024. This content is adapted from our webinar, Top 7 Supply Chain Trends for 2024. Click here to watch.

To kick off this blog series on the top seven supply chain trends for 2024, we’re going to dive right in to some of the hottest topics in supply chain right now: artificial intelligence and machine learning. (Would it even be a proper list if we didn’t mention one—or both—of those?)

AI and ML Begin to Normalize

The pressure is on for these technologies to begin reshaping traditional supply chain processes. 2023 brought us an AI revolution and we expect that pressure to continue in 2024. However, as early adopters and quick-to-market technologies begin to shake out, we expect to see 2024 normalize some of the AI and ML landscape. The abilities of these technologies to analyze vast amounts of data, identify patterns, and make decisions is revolutionizing how companies are thinking about their decision-making capabilities.

There is a massive opportunity when you start thinking about what AI and ML can do with access to the amount of data supply chains—and warehouses, specifically—create. But we must acknowledge the risk that lies in the over-reliance on AI-driven decision making.

While these technologies excel at analyzing data, unforeseen circumstances or outliers may not be adequately accounted for in algorithms. An algorithm wouldn’t have predicted the pandemic, for example. This lack of adaptability could lead to suboptimal decisions, especially in rapidly changing environments.

In 2024, we expect to see AI and ML begin to be used for practical efficiencies, but we’re going to continue to see those human overlays.

Data Security Concerns Surrounding AI and Machine Learning

When you’re thinking about accessibility to large amounts of data, a concern we’re seeing is the potential for data security breaches and privacy issues. Again, as these technologies rely heavily on vast amounts of data and sensitive information, we’re seeing that there’s, of course, going to be an increased risk.

What we typically see with new technologies is that there are growing pains when it comes to security and legal challenges. While there’s no doubt that security and legal advances are going to catch up, we can’t say it’s there yet and the reality is that, unfortunately, early adopters are going to have to help navigate those challenges. They’ll get the opportunity to help shape what some of that looks like.

Our recommendation is that teams begin to dip into the AI and the ML opportunities, in low-risk ways that provide efficiency gains without exposing a ton of risk to their company or their strategy.

Ethical Considerations Regarding AI and ML

In addition to security and legal issues, there are ethical considerations to be examined as these technologies evolve. As biases present in historical data may be perpetuated into AI algorithms, this can obviously lead to unfair treatment, discrimination, and unintended consequences, which raises concerns about the ethical use of AI in supply chain decision-making.

Conclusion

Our key takeaway here is that ultimately, while AI and machine learning offer transformative benefits, we recommend a careful and low-risk entry into these new technologies to mitigate risks and ensure responsible, sustainable, and thoughtful integration into supply chain technologies. The new shiny object approach is not going to be the path that works here.

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