Amazon to Launch ‘Q’ Business Chatbot in Apparent Answer to ChatGPT - Modern Distribution Management

Amazon to Launch ‘Q’ Business Chatbot in Apparent Answer to ChatGPT

Amazon's incoming generative AI chatbot was built to respond to data analysis queries and questions about supply chain decisions.
AWS

In 2024, Amazon will launch a chatbot powered by generative artificial intelligence (AI) to support its supply chain process.

The chatbot — dubbed ‘Q’ — follows suit of the popular generative AI chatbot ChatGPT. This one, though, is targeted at supply chain professionals and operates within the tech giant’s cloud-based application AWS Supply Chain, which integrates with enterprise resource planning and supply chain management systems. It was built to respond to data analysis queries and questions about supply chain decisions, including in regard to:

  • key risks around inventory levels,
  • demand variability, and;
  • visualization of tradeoffs between different possible scenarios in the supply chain.

The chatbot is powered by Amazon Bedrock, and gives insight into data within the AWS Supply Chain Data Lake, according to a Nov. 28 news release.

For example, via a conversational prompt within the AWS Supply Chain application, a customer types a question, and Amazon Q would respond, as below:

Supply chain professional: “What is the financial impact of delayed replenishment orders in the Southeast region?”

Amazon Q: “There are currently 8 delayed replenishment orders that could cause an out-of-stock situation for 20 of your fast-moving products in that region. The delay will have a revenue impact of $150K.” 

The use of generative AI in B2B sales is all the buzz for its potential to reduce the amount of time spent on prospecting and customer-meeting prep by over 50% by 2026, Gartner officials conclude in an August news release. 

Read more about the hype of generative AI, and find out how distributors like you use AI to accelerate success of their business.

Amazon also announced various new capabilities for 2024, including specialized models to more accurately forecast and plan purchase of raw materials and components; a forecast tool for multiple tiers of suppliers; and a tool to collect carbon emissions and compliance data from suppliers.

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