IBM says generative AI can help automate business actions

Key Points:

  • IBM’s SNAP software framework utilizes generative AI, specifically large language models, to predict the next action in a business process and offers suggestions for next steps, improving automation efficiency in enterprises.
  • SNAP leverages semantic stories and natural language narratives to capture more details of a business process, surpassing the capabilities of older AI programs that utilize sequence of activities as input for predictions.
  • The research findings show that SNAP outperformed older AI programs in next-action prediction, especially when the dataset contained rich semantic information, suggesting its potential for enhancing automation in businesses.

Summary:

Businesses are increasingly looking to automate human tasks for greater efficiency, and IBM’s latest research focuses on using generative artificial intelligence (AI), such as large language models (LLMs), to improve automation. The proposed software framework, SNAP, trains an LLM to predict the next action in a business process, offering suggestions for the next steps. This approach leverages semantic stories and natural language narratives to capture more details of a business process, going beyond the capabilities of older AI programs. The researchers found that SNAP outperformed older AI programs in next-action prediction, particularly when the dataset contained rich semantic information.

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