Gen AI's Impact on Retail: Overcoming Data Challenges and Ethical Considerations

Microsoft and Google strategically unveiled their generative artificial intelligence capabilities for the retail industry in time for the National Retail Federation's 2024 Big Show in New York, capturing the attention of the world's leading retailers and industry leaders at this premier event. These offerings, spanning customer engagement, shopper journey experiences, and operational enhancements, align seamlessly with the relentless pursuit of differentiation, revenue growth, and improved operating margins that define the retail landscape.

A recent Fortune/Deloitte CEO Survey revealed that 79 percent of CEOs anticipate increased efficiency through gen AI, and over half foresee new growth opportunities. Evidently, generative AI is no longer confined to the realms of experimentation; it's swiftly becoming an integral part of retailers' strategic visions.

As online and e-commerce trends surge — projected to reach over $43 trillion by 2030, according to Precedence Research — the imperative for retailers to embrace personalized digital solutions becomes even more pronounced. Gen AI, with its capacity to tailor digital interactions, predict customer needs, and craft individualized shopping journeys, emerges as a strategic ally.

For instance, gen AI can offer personalized product recommendations based on order history, suggest complementary items, or even recommend seasonal products tailored to the customer's location or weather conditions. It also enables content personalization through customized email newsletters and homepage recommendations.

The Data Dilemma and Ethical Considerations

However, as the retail landscape evolves towards more personalized customer interactions, it puts additional strain on internal business operations that cover retailers’ ability to provide efficient supply chains, new product design and innovation, and resource allocation while providing excellent customer service in an evolving omnichannel environment. Gen AI steps in to address these challenges, offering autonomous customer service with human-like interactions and enabling innovative product development linked to consumer preferences.

For example, it can craft personalized responses to customer queries, resolve issues with human-like interactions, and even provide visual and text search capabilities. In product development, gen AI generates innovative ideas aligned with consumer preferences and facilitates rapid digital iteration, feedback loops and customization.

Yet, despite the undeniable potential of gen AI, scaling AI-enabled use cases encounters hurdles, primarily related to data challenges. Microsoft and Google, leveraging their cloud-native capabilities such as Microsoft Fabric, Azure Open AI service, BigQuery, and Vertex AI Search, are well-poised to navigate these challenges. However, the imperative to prioritize data maturity remains, ensuring the seamless implementation and widespread adoption of AI initiatives.

Moreover, the introduction of gen AI in retail raises ethical considerations. Transparency, bias mitigation, and overall responsibility are paramount. The recent unveiling of the United States government's Blueprint for an AI Bill of Rights underscores the evolving legal and ethical landscape surrounding AI technologies. Navigating these considerations will be critical for companies venturing into the implementation of AI-enabled solutions.

Conclusion

As the retail industry eagerly embraces generative AI, the path forward requires a delicate balance between innovation and responsibility. Retailers must navigate data-related challenges, prioritize transparency, and remain vigilant in their commitment to ethical and responsible AI implementation. The unfolding narrative of AI in retail is not just about technology; it's about shaping a future where innovation aligns seamlessly with ethical considerations, creating a retail landscape that's not only technologically advanced but also socially responsible.

Oleg Royz is the vice president of retail and distribution at DataArt, a global software engineering firm.