These days, Generative AI features in almost every business conversation. The common theme? That the technology will transform industries through its human-like ability to understand and interpret natural language, summarise large volumes of unstructured information, and generate text and media content.
Retail is no exception. In fact, Generative AI is uniquely suited to a wide range of use cases across the retail value chain – promising to profoundly reshape areas including marketing operations, customer experience and support, procurement, and more.
In driving this pervasive change, Generative AI is set to elevate retailers’ business agility to a new level. But how? What will this mean in practice? And in an era when every retail organisation is experimenting with Generative AI, how will companies differentiate themselves to stay ahead of the competition?
An anatomy of agility
To answer these questions, let’s first look at what agility means to a retailer. In our view, its key attributes fall into two categories.
The first is the organisation’s ability to respond more quickly and continuously to external competitive and market events. As well as being able to onboard suppliers and bring products to market faster, this also includes rapidly adapting stores, supply chain and marketing internal functions (along with external ecosystem partners) based on changing customer preferences.
The second is leadership’s ability to adapt at a higher pace to changing strategic narratives and directions through self-empowered operational decision-making and technology modernisation, while retaining the inbuilt drivers of value.
Why is agility difficult?
However, while agility in retail is easy to define, many retailers find it hard to achieve. The reason? Up to now, agility has depended crucially on the ability to act on human judgement, comprehension and intellect. And this has been a limiting factor.
AI technology is already widely used in retail enterprises to make predictions, optimize outcomes and generate insights. But the human-like capabilities to generate new content, gather perspectives from diverse sources and create a clear narrative have been uncharted territory for technology – making people the only option.
Some examples? The copy for a personalised promotion has to be written by a skilled individual; the description for a product in an ecommerce site needs to be defined manually; ‘key words’ association has to be managed by several content authors; and legal documents have to be analysed by a legal expert. Each task adds time and cost for the business. But with Generative AI, these can all be handled by machines – boosting agility while freeing up people for more value-adding activities.
Six ways that Generative AI powers agility
So, how will Generative AI actually help retailers run agile businesses? Here are six ways.
Developing product content – Today, creating product images, product descriptions and associated metadata is a time-consuming manual task. Generative AI can produce compelling product pictures with or without models, improve existing images and generate both product descriptions and the related metadata. The results include shorter time-to-market for new products and productivity gains of up to 40%. Cognizant is working closely with one of the largest CPG companies in the world to create relevant product metadata using Generative AI and, in doing so, improve the visibility of products during ecommerce searches.
Providing knowledge to employees – Retail operations have vast institutional knowledge that’s often untapped. Generative AI can harness this knowledge and work as co-pilots with employees, providing them with the expert, in-context instructions and best practices. For example, a maintenance engineer in a distribution centre can get assistance to repair equipment. Cognizant has implemented a Generative AI-based engineering advisor application for a large elevator manufacturer that helps elevator service technicians to carry out day-to-day service operations efficiently.
Streamlining and improving retail contact centres – Generative AI will enhance intelligent chatbots through its ability to understand complex complaints, interpret sentiments, converse with empathy, and summarise appropriate solutions. It can also reduce manual effort by automating data discovery and drafting email responses to customers.
Creating personalised marketing campaigns at scale – Developing tailored creative content manually is costly and time consuming. Generative AI can draw on customer data to generate bespoke campaign content at scale, industrialising the creation of real-time, personalised communications.
Modernising legacy IT – Legacy technologies remain prevalent across retail. But while these need to be modernised, it’s important not to lose the “secret sauce” within the legacy systems that brings competitive advantage and value. Generative AI can reverse-engineer the systems’ value-add while converting legacy code into modern standards, fast-tracking modernisation.
Automating procurement processes – Retail procurement demands extensive analysis of contracts with third-parties such as product, logistics and technology providers. Generative AI's ability to extract and compare information from disparate documents and summarise the findings will automate manual efforts.
The different areas of application have different levels of business value, as well as risk and implementation complexity. Cognizant has a detailed framework through which organizations can assess these factors to prioritise, shortlist and create a roadmap for their Generative AI programmes.
While Generative AI can enhance retail agility in many ways, there’s one common success factor: support and buy-in from the workforce. Unless people across the business embrace the new ways of working and collaborating with Generative AI, the potential benefits won’t be realised.
Crucially, organisations will need to align their new operating models to be business outcome-focused and develop a positive culture around Generative AI. In a follow-up blog, we’ll be taking a closer look at people and culture in the Generative AI era. So watch this space!
