Overview
The next wave of gen AI use cases will see companies move beyond using it to increase productivity to employing it to redesign processes to transform the fabric of business operations, enhance innovation, and drive value. Just think of the infinite ways we use electricity; first used to light our homes, it then became an essential building block of modern life, so much so that we take it for granted in our daily lives.
Generative AI, too, has countless unexplored applications. Consumer packaged goods (CPG) and retail leaders can expect to see new use cases unfold that have a wider impact on the enterprise and the end consumer.
Unlocking new use cases for generative AI Unlocking new use cases for generative AI
To use gen AI as a lever for growth, CPG leaders should explore how the technology can transform the way data is used in these two ways:
Data insights: Combing through huge swaths of data that all CPGs are sitting on about their products, customers, and consumers and turning it into meaningful insights
Data recommendations: Turning those insights into recommendations to improve everything from promotions planning to inventory management
In practice, this might look like extracting data from the order life cycle and turning it into insights to remedy risks and issues in supply chain management. Or it could mean using gen AI to harvest better data from the point of sale and triangulating it with other data for richer insights. For example, using generative AI to decode product descriptions coming from the point of sale helps CPG and retail companies understand the exact product sold at the exact price to inform better sales-planning decisions.