Harnessing generative AI in manufacturing and supply chains

Generative AI (gen AI) is taking the world by storm. In a recent McKinsey survey, 79 percent of global executives said they had some familiarity with it, and 22 percent said they use it regularly in their work. The technology is expected to herald a new age of efficiency in operations: in manufacturing and supply chain alone, it could reduce expenses by up to half a trillion dollars.1

Gen AI’s implementation needs and use cases differ from those of analytical AI. Analytical AI is broadly implemented for forecasting, set point optimization, and the use of historical data to improve processes and outcomes. Gen AI, meanwhile, opens a new frontier for problem solving, illustrated by recent innovations in content creation, insight generation, and human-like interaction (exhibit).

Gen AI applications can accelerate, augment, and automate manufacturing and supply chain operations.

As gen AI models mature and establish their reliability, they will gradually converge with analytical AI in operations. Analytical AI has had significant impact in operations, and generative AI is likely to help with process acceleration, task simplification, and workforce productivity evolution.

Where gen AI can make a difference

Gen AI has a breadth of potential use cases in operations, and a picture is emerging of what an AI-driven workspace might look like, with benefits across the plan-make-deliver value stream.

In planning, gen AI can consolidate cross-functional insights and qualitative consumer sensing analysis for improved demand forecasts. It can suggest next best production plans to mitigate supply chain disruptions. And it can provide insights into inventory health or recommendations to reduce inventory.

On the manufacturing front, gen AI can unlock untapped productivity during production, leveraging root cause analysis to predict failures and reduce defects, and draft easy-to-follow dynamic work instructions. It can also augment operator stations by offering live, AI-supported troubleshooting and operating guidelines.

And in delivery, gen AI can help get products to customers on time and in full by automating document generation, verifying completions before transit, and communicating with customers on order tracking via AI chatbots. Paired with digital twins, gen AI can create warehouse designs and production scenarios faster.

While it is difficult to quantify the exact impact of discrete use cases of gen AI within operations today, early adopters have clearly shown that the technology will be a key tool to support manufacturing and supply chain organizations in becoming more flexible, efficient, and intuitive in meeting the needs of tomorrow’s end markets.

One emerging theme has been the speed at which gen AI has been able to move from idea to pilot. During pilots, organizations are experiencing significant shop floor adoption in days and weeks, rather than getting stuck in pilot purgatory for months and years.

Keep a human in the loop

Users of this revolutionary technology should be aware of the risks it introduces. These include the possibility that data fed into models will leak, the possibility of compromising IP, and exposure to liability under regulations such as the International Traffic in Arms Regulations (ITAR) and the Health Insurance Portability and Accountability Act (HIPAA).

On top of this, models have inherent biases that may amplify certain segments of data unduly, compromising the reliability of their conclusions. This underscores that AI models are not an opportunity to abandon human responsibility; human operators must take a conscientious, active hand in their use.

As in every industry, gen AI’s full operational value can be realized only through company-wide transformations. In such contexts, stakeholders benefit from a strong initial understanding of their organization’s highest-impact segments, existing technical infrastructure, and operating model. Such a process enables robust, scalable, and intuitive impact.

Gen AI is going to redefine the meaning of connected manufacturing and supply chain operations. First movers have the greatest potential to capture the value available and improve productivity.

The authors wish to thank Stephanie Rank and Marshall Riccardi for their contributions to this blog post.

1The economic potential of generative AI: The next productivity frontier,” McKinsey, June 14, 2023.

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