In Conversation with ChatGPT: Will AI Revolutionize Supply Chain Management?

We’ve all seen the conflicting headlines touting the impending doom and the long-awaited revolution that will be ushered in by artificial intelligence (AI). With the rapid rise and ongoing success of AI-based tools like ChatGPT, seemingly every thought leader has chimed in to confirm our worst fears: like it or hate it, the ‘robots’ are here. But is that really the case? Or will AI-based tools simply make the menial parts of our jobs easier and allow us to focus on more critical tasks? To answer this question, I asked the expert itself: ChatGPT.

ChatGPT is a large-language model, trained and developed by OpenAI and is often described as a game-changer for everything from menial administrative tasks to complex writing and editing. By combining natural language processing with machine learning, the tool can synthesize and communicate insights from big data, a key advancement for companies still struggling to make the most of their existing data. The tool is designed to mimic interaction with a human, allowing it to have phenomenal potential for integration with organizations at any level of technical expertise.

For this blog post, I “chatted” with ChatGPT to learn more about how the tool thinks it can impact supply chain management. Here I’ve provided a condensed version of our “conversation,” including ChatGPT’s answers to three of the most interesting questions facing the industry. Overall, the tool provided answers that reflect some of the technical advances long promised for S&OP and in the short-term, I agree with ChatGPT that AI-based tools (although not strictly the open-access ChatGPT module) can be used to see immediate improvements in predictive analytics and inventory management.

Jessie: How do you think ChatGPT and other AI-based tools will change supply chain management for large global corporations over the next one year and over the next five years?

ChatGPT: ChatGPT and other AI-based tools have the potential to significantly impact supply chain management for large global corporations in the next one year and five years. Here are some ways in which this might happen:

Next One Year:

1. Enhanced predictive analytics: AI-based tools can analyze data from multiple sources to provide more accurate predictions about demand, inventory levels, and supply chain disruptions.
2. Efficient inventory management: AI-based inventory management systems can help optimize inventory levels, reducing waste and increasing efficiency.
3. Improved supplier selection: AI-based tools can analyze supplier performance data to help organizations make more informed decisions about supplier selection and relationship management.
4. Enhanced customer experience: AI-based chatbots and virtual assistants can provide personalized and responsive customer service, improving customer satisfaction and loyalty.

Next Five Years:

1. Increased automation: AI-based tools can automate routine tasks such as order processing, inventory management, and supply chain monitoring, freeing up human resources for more complex tasks.
2. Supply chain optimization: AI can optimize supply chain networks by identifying the most efficient routes, transportation modes, and warehouses, reducing costs and lead times.
3. Real-time monitoring and response: AI-based tools can monitor supply chain performance in real-time and provide alerts when issues arise, enabling proactive responses to disruptions.
4. Sustainability and ethical considerations: AI can help organizations track and optimize their environmental impact and ensure ethical practices throughout their supply chain.

Overall, AI-based tools have the potential to transform supply chain management for large global corporations, improving efficiency, reducing costs, and enhancing customer satisfaction, while also enabling more sustainable and ethical practices.

Jessie: What do you think is the biggest impact that AI-based tools will have on supply chain management at all levels of the supply chain?

ChatGPT: The biggest impact that AI-based tools will have on supply chain management at all levels of the supply chain is the ability to provide real-time insights and improve decision-making capabilities.

At the strategic level, AI-based tools can analyze data from multiple sources to identify trends, predict demand, and optimize supply chain networks. This can help organizations make informed decisions about sourcing, production, and distribution.

At the tactical level, AI-based tools can monitor inventory levels, track shipments, and identify potential supply chain disruptions in real-time. This can help organizations quickly respond to changes in demand, adjust production schedules, and reroute shipments as needed.

At the operational level, AI-based tools can automate routine tasks such as order processing, inventory management, and supply chain monitoring. This can help organizations reduce costs and increase efficiency, freeing up human resources for more complex tasks.

Overall, the ability to access real-time insights and make informed decisions at all levels of the supply chain can have a significant impact on supply chain performance, enabling organizations to be more agile, efficient, and customer-focused. AI-based tools can help organizations achieve these goals by providing the necessary data and insights to drive continuous improvement and innovation.

Comment of the Author: Interesting to see all the above mentioned improvements in ChatGPT’s preview are already existing, so ChatGPT is probably not up to date yet. With the algorithms of intelligent supply chain software, such as the cloud-based solutions from flexis, all this functionality can already be provided today. We seem to have to improve our communication with ChatGPT.

Jessie: What do you think is currently missing from AI-based tools that would assist with supply chain management on a global scale?

ChatGPT: While AI-based tools have the potential to significantly improve supply chain management on a global scale, there are still some areas where they can be improved to better support these efforts. Here are some of the key areas that are currently missing:

1. Data standardization: One of the biggest challenges in using AI for supply chain management is the lack of standardized data across the supply chain. Different suppliers and partners may use different systems and formats, making it difficult to integrate and analyze data effectively. Developing standard data formats and protocols can help address this issue.
2. Robust data quality: AI-based tools rely heavily on data inputs to generate insights and predictions. Ensuring that data is accurate, complete, and up to date is critical to the success of these tools. Organizations need to invest in data quality processes and technologies to improve the reliability of the data that AI models use.
3. Interoperability: Supply chain management involves many different systems, applications, and technologies, making it important for AI-based tools to be interoperable with these systems. Developing open APIs and standard interfaces can help ensure that AI tools can easily integrate with existing systems and workflows.
4. Explainability: As AI-based tools become more sophisticated, they can sometimes generate insights and predictions that are difficult for humans to understand or interpret. Developing models that are transparent and explainable can help build trust in these tools and make them more accessible to non-technical users.

Overall, addressing these issues can help ensure that AI-based tools are more effective and can be more widely adopted in supply chain management on a global scale.

End of interview.

I think one of the more interesting points raised by ChatGPT was the potential to analyze supplier performance and provide recommendations on the best suppliers for each part of the BOM. These big changes will likely come in the next few years as ChatGPT and other advanced AI tools become readily available and integrated into industrial software. I agree with ChatGPT that the most significant advances will be in the automation of supply chain management. AI-based tools will be able to even more automate routine tasks. Another area highlighted by ChatGPT that is already starting to emerge in S&OP solutions is AI-enabled optimization of sustainability metrics.

Interestingly, ChatGPT did not highlight any areas that will be impacted by AI-based tools that haven’t already been discussed elsewhere—a product of a tool that learns from the human body of knowledge. Where it provided some interesting insight was when I probed what the tool thought was currently lacking in AI-based solutions, including with ChatGPT itself. The top answer? Data standardization. You can see examples of this in real-time using ChatGPT as the specificity and quality of the prompt drastically impacts the output of the tool. As AI-based solutions continue to learn and mature, this will hopefully improve. Specifically in supply chain management, data standardization will also be important to improve the output of AI-based tools, as disparate data across the supply chain currently complicates the ability of these tools to monitor, analyze, and report insights into big data.

A recent Gartner survey additionally determined that companies are viewing data standardization as a major hurdle to AI-driven tools, leading to the increased utilization of synthetic data for model generation and testing. Data accessibility, complexity, and availability all make it difficult to take advantage of existing data to truly gain AI-enabled insights.

Image from Gartner report: Generative AI for Synthetic Data.

In the meantime, anyone can take advantage of the ability of ChatGPT to change their day-to-day work environment: drafting e-mails, synthesizing technical topics, developing a meeting schedule, or even planning a travel itinerary. I think the most exciting applications of this tool and technology have yet to be seen. As ChatGPT highlighted, the next five years will likely see expansion of these types of tools into almost any application. In the meantime, one of the clearest applications of ChatGPT is content creation, for blog posts just like this one.

If you want to learn more, download your guide to Supply Chain Resilience and the new Normal.

In this Guide you will learn:

1. Four steps to supply chain resilience

2. Use case of a large appliance manufacturer