AI (Artificial Intelligence) has a significant impact on consumers behavior and decision-making in retail by individualizing experiences, making them convenient, and promoting interactions. And there will be two paths to be followed and implemented, one as a retailer and one as a customer.

Artificial intelligence is quietly reshaping the way we shop, influencing our buying decisions in ways we might not even notice. Imagine browsing an online store and seeing product recommendations that feel hand-picked just for you - that's AI analyzing your preferences to create a more personal shopping experience. When you chat with a customer service bot that instantly answers your questions, or when you use your voice to search for products instead of typing, you're experiencing how AI removes friction from the shopping journey. Ever noticed how some items seem to go on sale right when you're thinking about buying them? That's AI at work, optimizing prices in real-time. The ability to virtually "try on" makeup or see how furniture would look in your home before purchasing gives us more confidence in our choices. Behind the scenes, AI is also working to keep our transactions secure and ensure popular items stay in stock. These subtle yet powerful applications create a shopping experience that feels more intuitive, trustworthy, and satisfying - ultimately making us more likely to click that "buy now" button and come back for future purchases.

In retail, AI doesn’t just recommend products—it influences purchase intention by synchronizing operational readiness with consumer interest. Imagine an AI system that detects a spike in online interest for a trending sneaker, automatically adjusting regional stock levels, ad targeting, and dynamic pricing so customers see “available now” instead of “out of stock.” The perception of availability and timeliness can be as persuasive as the discount itself.

From a customer’s perspective, trust in these AI-driven experiences hinges on data ethics—clear consent, unbiased offers, and explainable logic for why certain deals or products appear. My research on Data Governance in Machine Learning demonstrated that strong governance not only improves prediction accuracy but also boosts consumer confidence—an effect equally critical in retail AI, where perceived fairness directly impacts conversion.

For analysis, measure both hard metrics (conversion rate, basket size) and trust metrics (opt-in rates, complaint frequency). The most successful AI retail deployments are those that integrate customer-centric governance with predictive agility—turning operational precision into purchase intent.

Please read more on my paper here :

Conference Paper Efficacy of Data Governance a Cutting Edge Approach to Ensur...