‘The real superpower of Gen-AI? Putting the customer at the heart of retail’

Generative AI (Gen-AI) has been one of the most talked about topics for more than a year and retailers have wasted little time in exploring how the technology could transform customer services and boost productivity.

But in the rush to unlock value, many decision makers have ignored the elephant in the room – the potentially game-changing impact generative AI could have on the retail business model.

Gen-AI algorithms, which use neural networks to generate text, images and other media, had a breakout year in 2023. Just a few months after launch, ChatGPT was drawing nearly 1.5 billion visitors a month.

Many in the retail industry have already jumped in, testing the technology’s ability to create human-like communications and deliver customer services. Walmart is among the companies to have taken a lead, launching a text-to-shop feature in which a chatbot converses back and forth with customers and recommends products based on profiling.

Driving retail efficiency through data

Our analysis suggests Gen-AI can boost business performance across the retail value chain. Probably the most mature use cases right now are in marketing and software engineering, where companies can automatically generate content from unstructured data, such as text contained in documents, emails and webpages, or accelerate code development.

“Gen-AI’s ability to supercharge internal capabilities is only part of the story. The bigger part is the power that consumers will yield with Gen-AI at their fingertips”

One of Gen-AI’s big innovations is that it can translate data into hyper-personalised outputs. The model can recommend a sequence of best actions and channels with tailored messages and appropriate tones that drive sales.

In-store, it could unlock benefits, such as chat and text customer engagement, associate support, productivity unlocks including next-best actions, synthesized KPI and performance metrics, and automated reporting.

All of that said, Gen-AI’s ability to supercharge internal capabilities is only part of the story. The bigger part is the power that consumers will yield with Gen-AI at their fingertips.

Speaking the consumer’s language

Imagine a world in which consumers employ Gen-AI-powered virtual assistants to do their shopping with the assistant scouring the market based on the customer’s budget and preferences. In this context, how does the traditional model of retail operate?

Consider a consumer that could upload a photo and either generate a custom garment that doesn’t as yet exist or put together a designer outfit from mass market products. What would that mean for fashion and department stores? These innovations are not a distant dream – the technology is already being used today.

Under a consumer-driven model, Gen-AI looks less like a driver of efficiency and more like a force of disintermediation.

Consumers will no longer be driven by learned behaviours and will use natural language to help them make and execute decisions. As a result, the relationship between retailers and their customers could be unrecognisable from anything seen previously.

Reimagining the retail business model

If Gen-AI does radically reshape retail, the bigger question for chief executives will be how to reimagine the business model. Retailers will need to consider what will be disintermediated and the implications for value propositions and cost curves.

“Leading retailers will move fast on capabilities that enable them to be service rich and cost effective”

In this paradigm, it is easy to imagine business flowing to data-driven, low-cost business models that do not have huge physical footprints or large numbers of customer-facing employees.

On the other hand, an AI-driven retail journey may present an opportunity to attract new customers and online traffic. A big unlock will be to use Gen-AI to cut the cost of delivering services safely and securely. Leading retailers will move fast on capabilities that enable them to be service rich and cost effective.

The bottom line? Gen-AI is a work in progress, but its potential means that decision makers must urgently consider the short- and longer-term implications. And rather than implementing dozens of use cases, the early priority should be to reimagine key parts of the value chain.

Anita Balchandani is a senior partner and Samantha Phillips is a partner at McKinsey & Company, Alexander Sukharevsky is a senior partner and managing partner at QuantumBlack, AI by McKinsey