How AI Can Address Manufacturing Supply Chain Issues


The following first appeared on Robinson+Cole’s Manufacturing Law Blog. It is reposted here with permission.

The global market for artificial intelligence in manufacturing is valued at $3.2 billion in 2023 and is poised to grow to $20.8 billion by 2028.

Used wisely, AI can help manufacturers solve many of their most intractable issues, including supply chain issues that have frustrated companies and their customers since the pandemic.

Yet, many manufacturers remain unaware of how AI can help transform their business or even what exactly AI is.

Basically, AI describes machines performing tasks that would ordinarily require human intelligence: when your phone corrects your spelling, when your favorite streaming service suggests a movie, or when your automatic vacuum cleaner maneuvers around your living room, you are using AI.

In the manufacturing context, AI can enhance supply chain visibility. AI tools can compile and synthesize raw data from invoices, product orders, customs declarations, and other documents to track inventory as goods move through the supply chain.

AI can combine this information with historical data to predict sales and revenue, as well as demand fluctuations, enabling a manufacturer to optimize inventory levels.


Like everything else, AI has its pitfalls.

The computer maxim “garbage in, garbage out” applies to AI, so AI trained with poor data will return poor results.

The maxim “garbage in, garbage out” applies to AI.

Your experience with autocorrect has probably taught you that AI can struggle to recognize whether its rules have become inapplicable or whether an exception should be made.

AI can discern and repeat a pattern, but automatically repeating patterns can lead to biases that reduce the AI’s efficiency or, depending on how it is used, violate the law.

And if not properly governed, AI can be provoked into disclosing private or sensitive information.

Government Scrutiny

Moreover, AI’s impressive potential has attracted government attention.

Last year, the White House issued its Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, which announced that the federal government would “increase its internal capacity to regulate, govern, and support responsible use of AI.”

The Securities and Exchange Commission has begun pursuing companies that oversell their AI capabilities.

Following the White House’s lead, the Federal Trade Commission has warned against misuse of AI in various contexts, including uses in ways that it deems harmful to consumers.

Similarly, the Securities and Exchange Commission has begun pursuing companies that oversell their AI capabilities.

These and other agencies can use their enforcement powers to monitor the development and use of AI systems, and they have signaled their intent to do so.

Governance Plan

Given AI’s opportunities and risks, a manufacturer must manage its use of AI as thoughtfully as it does every other aspect of its business.

An AI governance plan can guide a company toward safe AI usage that works effectively and consistently with its culture while avoiding unwanted government attention.

A strong AI governance plan can empower a manufacturer to harness the promise of AI while avoiding its perils.

A cyber incident response plan helps mitigate damage if any harm, unauthorized disclosure, or cyberattack occurs, and it instructs the company to comply with applicable laws after a cyber incident occurs.

Together, a strong AI governance plan and a cyber incident response plan can empower a manufacturer to harness the promise of AI while avoiding its perils.

About the author: Robinson + Cole attorney Sean Griffin is one of the world’s first artificial intelligence governance professionals certified by the International Association of Privacy Professionals.


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