Three ways to use GenAI to transform supply chain management 

1. Do the job of ‘narrow AI’ better

Tasks such as calculating optimal inventory levels are often much less straightforward than they initially appear. ‘Narrow AI’ solutions address this difficulty using complex algorithms that are run repeatedly until they produce the hoped-for results – but this requires substantial resources. GenAI tools are now matching the results achieved by algorithmic models (and even exceeding them in some cases), and do not require the same level of resourcing.

Benefits:

• More efficient than some of the narrower AI tools.
• A cheaper route to inventory optimization.

2. Reduce reliance on Excel expertise

IMD’s research suggests supply chain professionals spend as much as 60% of their time on Excel spreadsheets. This consumes huge amounts of time in the supply chain function and creates undesirable dependencies. GenAI won’t replace Excel, but it does have the potential to take over much of the heavy lifting in spreadsheet development and analysis because tools such as Microsoft Copilot are now capable of programming Excel on the user’s behalf.

Benefits:

• Potential significant productivity gains.
• Reduces the impact of the loss of an individual spreadsheet author.

3. Ask new questions about the business

With the exception of certain established use cases, the supply chain function has seldom put critical questions to traditional AI because, until now, it hasn’t been able to answer them. In contrast, GenAI’s flexibility and agility can make a stronger attempt to do this.

Benefits:

• The technology can be deployed in new areas of the supply chain.
• Meaningful answers to a wider range of questions can be sought.