Predicting ChatGPT's impact on the future of supply chain

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Amidst a sea of generative AI applications, ChatGPT has been a standout thanks to its breadth of knowledge and simplistic interface. 

While ChatGPT isn’t the first generative application of its kind, it has set itself apart by possessing a human-like quality when you chat with it – and as a result, many C-level executives are energized by the positive potential AI could have within their organizations. 

When it comes to solving issues within the supply chain, Mike Watson, faculty member at Northwestern University, and Polly Mitchell-Guthrie, VP, Industry Outreach & Thought Leadership at Kinaxis, speculate that it may be able to solve complex issues that require ideation and decision-making. Could AI be a game-changer in the industry?

In our latest Big Ideas in Supply Chain podcast, Mike and Polly explore how generative AI models have the potential to refine data, impact productivity, and empower people to develop more efficient supply chains. 

Here are some takeaways from their conversation.

Why C-level executives are paying attention to ChatGPT 

ChatGPT has captured millions of users’ imaginations despite some of its shortcomings. Even though the application lacks robustness and accuracy, the potential of generative AI programs isn’t lost on the public, or C-level executives. 

At its core, ChatGPT uses text to formulate a response when you ask it questions. It does this by predicting what the next word should be based on previous prompts its seen. 

Thanks to the program’s success, Mike says its popularity has convinced many organizations to start thinking seriously about AI and what value it can add in terms of increasing productivity. Mike explains, “ChatGPT just took [generative AI] to another level. […] And this gives us another excuse to talk to leadership teams about what this means and how it might impact their organizations and supply chain.”

Right now, ChatGPT is regarded as a personal productivity tool capable of responding to sophisticated search questions. For organizations interested in adopting this type of technology, the application holds a lot of promise in terms of increasing efficiency. Many companies are already exploring building versions designed to meet their unique needs.

For example, Bloomberg released BloombergGPT, which uses its own wealth of data to create a large language model similar to ChatGPT but for finance. “This is our opportunity for supply chain. How can we take all our supply chain data, all our information, […] feed it all in and then we have this natural language interface that I can start to ask questions related to my supply chain,” says Mike. “And then ChatGPT, or whatever equivalent tool, will start to be able to query that database in a very interesting way and bring back data that's very specific to my business, my industry, the kinds of questions that I'm asking. I think that to me feels like the big unlock of all this.”

How generative AI may affect supply chain roles

Many people are still hesitant to embrace AI and automation for fear of losing their jobs, but Mike feels optimistic about AI assisting, rather than replacing, many roles in the industry. 

For supply chain practitioners, he views generative AI and automation as tools that can be used to improve ideation and decision-making. “I think what feels to be one obvious use of ChatGPT and similar technology is that the non-coder can now write code,” he says. “In supply chain, there's hundreds and hundreds of decisions that we make, and you can think of each of those decisions, ‘can I write an algorithm to do that?’ and an algorithm needs some code if I want to help automate that. And so, this could unlock the potential for supply chain companies to really start to apply lots of different algorithms in lots of places.”

This ability would help non-coders dive into new opportunities within their roles without losing a significant amount of time or effort. For example, if a code takes 20 minutes to produce through generative AI that can automate a certain task or help form a decision, then the results of the exercise would be positive. Even if the automation fails, there still isn’t a significant loss for the time spent on it.

Despite AI’s ability to potentially help accelerate ideation and decision-making processes in the supply chain, Mike and Polly agree that we aren’t anywhere near a point where human intelligence will become obsolete within supply chain roles. “AI still lacks the three C's, Context, Collaboration, and Conscience,” explains Polly. “It’s indifferent. It doesn't know right from wrong. We have to bring it from right from wrong.”

Generative AI is a fast-developing technology that is still in its early stages of evolution. At this time, supply chain leaders have the exciting opportunity to mold it, so the next generation of ChatGPT-based applications are equipped to resolve supply chain’s most pressing problems.

To hear more about generative AI and its future impact on supply chain from Mike and Polly, watch the full video podcast here: 


Big Ideas in Supply Chain graphic with red, green, blue and yellow circle designs and black and white headshots of speakers Mike Watson and Polly Mitchell-Guthrie with text reading Predicting ChatGPT's impact on the future of supply chain

Be sure to check out other recent Big Ideas in Supply Chain podcasts for additional insights and best practices to take your supply chain planning strategies to the next level:



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