Retailers: How strategic is your approach to generative AI?

By Brandon Rael and Dipesh Joshi

Retailers already use generative AI to reduce costs and unlock business value—from crafting hyper-personalized shopping experiences to reducing product returns.

As retail teams continue to navigate the fallout from the pandemic’s supply chain disruptions, the integration of generative AI across merchandising, sourcing, logistics, and product development will be essential—to both build resilience and stay ahead of fluctuating customer demand.

Yet, despite widespread prioritization of generative AI initiatives, a Kyndryl study indicates a significant implementation gap: only 10% of companies surveyed had fully documented a strategy for enterprise-wide activation, and almost half (48%) hadn’t even started the journey.

Moving forward, retailers that adopt a more strategic and prescriptive approach to their generative AI initiatives likely will come out ahead—setting new industry standards for personalization and operational adaptability.

Build resilience to future-proof your generative AI strategies

Among the respondents to the aforementioned study, 94% of companies said they are prioritizing generative AI. But before going from zero to 100 on your generative AI play, spend a moment to build resilience in order to safeguard—and future-proof—your strategy.

As a retailer, you gather data from multiple front-end and back-end sources, including supply chains, merchandising and points of sale. As such, it's essential for your team to consolidate this disparate data into a unified view—a single source of truth—for your customers and products.

To effectively process this data, consider adopting a set of Data Quality (DQ) procedures. DQ tools are an excellent resource for your team to check that your data is not only accurate but also complete and consistent.

Your team will also need to establish a governance framework to monitor that your generative AI tools are being used ethically and responsibly. This framework should outline the policies and procedures for using these tools, including how data is collected, stored and used.

A key outcome of this framework will be the widespread distribution of these tools’ benefits across your organization—otherwise known as data democratization. Data democratization will be vital, for example, in empowering your frontline workers to make informed, data-driven decisions through generative AI-powered inventories or enabling your merchandising and assortment planning teams to create dynamic and targeted content for specific products.

Unlocking value by aligning on goals

With data governance practices established, it’s time to start exploring how, exactly, generative AI can fuel your existing—and future—business strategies by asking yourselves a few basic questions.

For example: What is your team’s target return on investment (ROI) for your generative AI initiatives? How are you hoping to use these tools to boost your team’s productivity? While ROI will depend on scale and other factors, productivity boosts from a recent report found that generative AI could help boost productivity in the retail and consumer packaging goods industry by 1.2 to 2 percent of annual revenues.¹

To maximize your investment, your team might, for example, consider how you are planning to use these tools to enhance supply chain, merchandising, ecommerce, and/or your go-to-market approaches.

Maybe for you, the answer will be to direct your initial generative AI applications towards driving intelligent decision-making, route management and operational efficiencies. Or perhaps: towards conversational product assistance to equip your teams with better decision-making capabilities.

Few organizations currently personalize their content based on intent or prediction², which also may be an opportunity for organizations to differentiate themselves and their offerings. So, how will your team use your generative AI capabilities to boost personalization strategies across channels? How do you plan to help consumers seamlessly navigate physical, digital, social and live-streaming platforms to shop with your brand?

Engaging in these initial discussions, whether as a whole or simply among key decision-makers, will help clarify your priorities.

Find your starting point for use case development

These are just a few of the ways we see customers utilizing generative AI strategically:

Hyper personalization: Achieving ecommerce personalization at scale—profitably and successfully—has long been the holy grail for retailers. Generative AI can help retailers create a holistic customer view across all touchpoints, both in-store and online and including social channels like TikTok and Instagram.  

• What this looks like: Compelling promotional offers or product suggestions, not only based on past purchases but also influenced by search history and social interactions.

Agile supply chains: The economic impact of supply chain disruptions can be severe for many retailers. Employing adaptive, intelligent, just-in-time supply chain management capabilities, powered by generative AI, can enable retailers to meet consumer demands and mitigate potential disruptions.

• What this looks like: Summarizing purchase order changes to drive better decision-making, route management and operational efficiencies; optimizing fulfillment for on-time deliveries and transparency for both the retailers and customers.

Modernized storefronts: By integrating shopping and purchasing processes through generative AI, retailers can create an efficient, streamlined experience for customers and adapt their storefronts to current shopping behaviors.

• What this looks like: Dynamic pricing and electronic shelf labels, allowing retailers to not only remain competitive on price but also provide flexible pricing, according to country or region.

Redefining the IT management landscape

Retail is, fundamentally, about delivering the right product, at the right place, at the right time. Adopting a more strategic, prescriptive approach to generative AI for retail applications will not only help your team cultivate a more resilient, agile commerce operation but also set a new industry standard for what it means to be a reliable, favored brand.

Brandon Rael is a Director, Consult Partner US Consumer and Travel at Kyndryl.
Dipesh Joshi (DJ) is a Director, Consult Partner US - Consumer and Travel at Kyndryl.

¹ Economic potential of generative AI. McKinsey. June 2023.
² Adobe Digital Trends 2023. Adobe. 2023.