Industrial Electronics

Outlook 2024: 5 ways generative AI will impact fulfillment operations

05 January 2024
Generative AI could be used in 2024 to help understand where a fulfillment system is having difficulties and address the problem in real-time instead of learning about it later. Source: Mustafa/ Adobe Stock

In 2023, generative artificial intelligence (AI) — or software that produces various types of content and can be trained — was used as a social experiment or to help businesses online.

In 2024, it will be used to transform fulfillment operations in the industrial sector.

According to market research firm Deloitte, usage of generative AI is expected to grow exponentially over the coming decade and likely will become a large part of every organization. As technology improves and how vendors can use AI expands, it will likely affect workforce planning and much more.

The introduction of warehouse management systems (WMS) and transportation management systems (TMS) increased the demand for skilled workers. However, AI along with other software platforms may decrease the need for operations and technical staff, Deloitte said.

1) Training

Generative AI is going to be huge in training and likely a staple with warehouse fulfillment operations. The AI will likely lead to a shift toward more user-led training for WMS, TMS and operational enhancements.

This will lead to users having a conversation with the system to learn a business’ best practices and functionality.

2) Trial and error

As generative AI learns a system, a user could operate and test software enhancements to improve the quality of fulfillment at locations. This could include changes to picking or route management done by a user and without the need to bring in pricy software developers.

3) Root-cause analysis

Deloitte predicts that generative AI will be used in operations teams for root-cause analysis in real time. This will help understand where a fulfillment system is having difficulties or not meeting the expectations of the vendor.

This could be directly asking the system why products aren’t in the correct location instead of just getting an error that a product isn’t in the proper location.

4) Reporting

Generative AI is very good at creating reports. In fulfillment centers, a floor manager could ask the AI to auto-generate any desired reports for orders and the system would do it easier than any current method could.

This might even be as detailed as picking out a particular employee’s fill order rate or the order rate of a particular product for any type of period.

5) Collaborations

Deloitte said communication and collaborations might be the most important of all the uses for generative AI. The system may allow teams to structure, organize and streamline data sets across networks.

This type of collaboration would lead to cost optimization and a better customer experience. It could be anything from a summary of a Zoom call to customizing slides for specific audiences.

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