GenAI brings new clarity to retail decision making

From interpreting shifting customer expectations to managing intricate supply chains, retailers face an ever-growing need for faster, more intelligent decision-making capabilities. While artificial intelligence has been supporting retail decisions for years, Generative AI (GenAI) represents a fundamental shift in how retailers can approach complex challenges and opportunities.

For instance, while traditional AI might analyse historical sales data to predict demand, GenAI can create detailed scenarios of potential market changes, generate written explanations of trends, and propose innovative solutions to complex problems. Combining analytical and creative horsepower in this way, is enabling some retailers to make more nuanced and proactive decisions in real-time and better communicate value to customers.

Below are just three examples where GenAI is bringing new clarity to retail decision-making:

Supply Chain and Inventory Management

Predictive AI has long helped retailers predict demand patterns. GenAI elevates this capability by generating comprehensive scenario analyses and providing natural language insights about supply chain dynamics. Walmart is always evolving its supply chain management. While their traditional AI systems handle demand forecasting at scale, their GenAI implementations are now:

Creating multiple scenario plans for potential disruptions before they happen and automatically drafting supplier communications based on evolving inventory needs.

Providing natural language responses to complex supply chain queries and generating detailed written reports explaining supply chain bottlenecks.

Pricing and Promotions Optimisation

Traditional AI excels at analysing historical pricing data and predicting the impact of promotional activity. GenAI brings a new dimension. Target (USA) have now begun to integrate Gen AI capabilities, augmenting their price and promotion optimisation system to include:

Creating multiple promotional and pricing scenarios with expected outcomes and the narratives in detail to explain the logic.

Producing explanations for price recommendations and then automatically drafting the related promotional copy.

Marketing and Customer Engagement

The addition of GenAI to the growing arsenal of data science and AI capabilities is perhaps most visible in marketing and customer engagement. While Amazon’s traditional recommendation engine has been a cornerstone of personalisation for years, newer GenAI applications are transforming how third party sellers engage with Amazon’s marketplace and reach customers, including:

Conversation led guidance through the process of building a presence and expanding your business, on Amazon.

The ability to generate unique product descriptions that reflect brand voice and create personalised marketing copy at scale.

Looking Ahead

The integration of GenAI into retail decision-making is a fundamental shift in how retailers understand and respond to market dynamics. It is already emerging as a transformative technology, bringing new clarity to the increasing complexity of optimising operations, meeting customer demands and staying ahead of the competition.

Next week, we will have a look at some specifics where this new technology is re-inventing the retail customer journey.