Will AI Remove Humans From Supply Chain Management?

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Artificial intelligence (AI) is the most disruptive technology of the modern era, if not of history. While it has use cases across virtually every industry, some have more to gain — and lose — than others. Supply chain management is one such role that AI could drastically transform, possibly to the point where humans no longer do it.

Many technologists emphasize that automation ultimately creates more jobs than it takes, but that still means some roles disappear. Could supply chain management be one of those jobs? What would that mean for the industry? Here’s a closer look.

AI’s Role in Supply Chain Management

All but 6% of supply chain businesses already use AI in some capacity. Roughly 11% say it’s critical to their operations, a figure that could apply to more than a third of these companies before long. It’s easy to understand why as AI improves many aspects of supply chain management.

Demand Forecasting

AI’s predictive capabilities are one of its strongest assets in supply chain management. Machine learning models can analyze past sales data and current trends to predict upcoming demand shifts. Companies can then order less of some products and more of another to prevent stock-outs and surpluses.

As AI has advanced, so have its forecasting abilities. Some supply chain AI solutions can predict incoming disruptions by analyzing the weather, financial trends, geopolitical issues and other shifts. They can then recommend changes to mitigate the impact of otherwise disruptive events.

This level of forecasting is remarkably difficult for human analysts, especially given how complex supply chains have become. However, it’s precisely the kind of in-depth analysis where AI excels.

Inventory Management

Similarly, AI is also transforming inventory management. Predictions about demand shifts and disruptions are only as helpful as a company’s ability to adjust its inventory accordingly. That requires extensive visibility over multiple storage locations, making human error likely.

Data sets this large and repetitive make it easy to make mistakes. Volatile supply and demand factors make these errors even more likely. As a result, stock-out rates in the U.S. have risen to more than 35% after the onset of the COVID-19 pandemic. AI offers more reliability, as it can track inventories in real-time and doesn’t make data entry errors.

AI solutions can also go further and automatically order products as needed. Some companies even use it to determine where to stock certain items and where to ship from to enable the fastest possible deliveries.

Supplier Evaluation

Businesses are beginning to use AI in the upstream side of supply chain management. Minimizing costs and preventing delays is largely a matter of using the right suppliers. AI can evaluate possible sources to identify the best one for each product or material.

The chief advantage of AI here is that it’s both accurate and fast. Finding the right one manually can take too long. Conventional computing is too unreliable, given the complexity of these decisions. Roughly 70% of supply chains now put more emphasis on reliability and flexibility than pure costs, so a simple cost comparison is insufficient. AI can manage that nuance while improving speeds.

AI can also adapt to shifting trends, alerting companies when a current supplier is no longer the best option. This decision agility is crucial in today’s fast-moving market.

Process Optimization

Supply chain AI can manage internal processes, too. Manufacturing and shipping a product involves a lot of moving parts. That means inefficiencies can arise from many areas and the best strategy is rarely immediately evident, but AI can automate this decision-making for faster, more effective changes.

These optimizations could be as straightforward as routing deliveries more efficiently — something many logistics companies have embraced. As AI advances, though, it could go much further. Businesses could use AI to construct and analyze digital twins of the entire supply chain and suggest changes across virtually every step.

Is the Human Factor Still Necessary?

Looking at AI’s extensive role in supply chain management, it’s hard to see where humans fit in anymore. AI will only get more capable and reliable from here, so if current trends continue, it’s not outlandish to think this technology could do everything today’s supply chain managers do.

Despite this potential, AI won’t likely replace humans in supply chain management, at least not entirely. For all of its benefits, AI has some considerable downsides, too. Hallucinations are one of the most prominent. Today’s most popular generative AI models spout false information 3%-27% of the time, which could have disastrous consequences in supply chain management.

Of course, human predictions aren’t perfect, either. But if a supply chain management system was entirely automated, it may automatically respond to a factor with little to no basis in reality. That could lead to stock-outs, delays, and considerable expenses. Given how far-reaching the consequences of supply chain decisions can be, human experts should always have the final say.

Putting too much in the hands of AI has dubious ethical implications, too. AI’s substantial data use makes them a bigger target for hackers and could lead to accidentally leaking sensitive information. AI’s well-documented bias problem could cause serious issues, too, especially if AI managed workforce considerations like hiring.

It’s also important to remember that even the most advanced AI only responds to trends in data. Consequently, events with little data behind them pose a considerable challenge. Supply chain disruptions like the COVID-19 pandemic may be rare, but AI isn’t likely to predict them accurately or respond effectively when they do happen. They’re too sudden and unpredictable, requiring more flexible humans to manage.

AI Is Not the End of Supply Chain Management

When considering both AI’s advantages and downsides, it becomes clear that human supply chain managers won’t go away, but their jobs will change. Businesses may need fewer employees in these positions, but they’ll still be critical. Similarly, the job will entail less analysis and require more understanding of AI models and how they work.

Tomorrow’s supply chain managers will use AI to inform virtually every decision and likely automate many small actions, like ordering and billing. The final decision — especially in terms of company-wide strategic changes — will still fall to humans, who must interpret AI’s insights. This transition will likely entail some job disruption, but it’s not the end of the profession.

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