Use cases of generative AI in retail

Discover the role of generative AI in retail.

Generative AI has become an overnight global sensation, bringing sweeping changes to businesses, industries and the everyday layperson. Over the last century we have seen a significant evolution, from hand-made machinery to sophisticated technological paradigms that are reshaping economies around the world. According to a report by McKinsey, generative AI has the potential to generate $2.6 – $4.4 trillion annually across industries and the retail sector is no exception. 

Retail organisations are recognising the value of generative AI for revitalising the customer experience, improving business supply chains and increasing efficiency. But when it comes to understanding the real implications of generative AI, there is still a feeling of uncertainty. Above all, regulatory enforcement, legalities and bias are the top concerns crossing the minds of business leaders today. 

Thus, how is generative AI making its mark on the retail industry and how can we make sense of its changes?


Meeting increasing customer expectations 

McKinsey predicts that generative AI will contribute an additional $310 billion for the retail industry through enhancement of digital customer interactions.  

Just as consumers are embracing generative AI to make their lives easier, organisations are now expected to do the same. The increased competition in the market and accessibility of products means that we have entered a period of ‘flighty’ consumer behaviour. Today, consumers demand easy and customised shopping experiences or will quickly turn their attention elsewhere. Generative AI enables organisations to overcome this challenge, introducing a level of customer experience seldom achieved before. And this all comes down to personalisation 


Personalisation and curated shopping experiences 

According to Accenture, 80% of business leaders want to enhance their customer interactions by using conversational AI tools. 

What makes generative AI truly attractive is its ability to unlock a ‘curated’ shopping experience. We’ve all been there; scrolling tirelessly through tens to hundreds of retailer pages trying to find the items that we need. Intelligent chatbots remove this barrier of findability by allowing customers to source lists of items on demand, (‘find me size 4 white trainers’). Thus, removing the need for scrolling and navigational bars altogether.  

Instacart grocery delivery, for example, is trialling this ‘self-serve’ capability into their mobile application. Customers can ask food-related questions such as recipes, healthy ingredients, etc, and the application will find provide the answers to these. 


Intelligent chatbots and virtual assistants for query resolution 

Generative AI powered virtual shopping assistants and chatbots also open the door to improved customer experience. It can answer complex customer-related queries, track orders, provide instant resolution and guide users through the shopping experience, all the while maintaining natural human-like conversation and sentiment. We can think of it as a super-intelligent ‘human agent’ that can handle complaints in masse, speak multiple languages and find solutions to problems instantly.

Discover BonBon, NashTech’s intelligent and customisable chatbot solution here.

Smartifying business processes — inventory and supply chain management 

Retailers are dependent on their supply chains; one disaster or unexpected event and organisations are thrown into unimaginable chaos and unable to deliver against customer demand. Generative AI ‘smartifies’ supply chain management across the entire value chain, optimising end-to-end processes, from demand forecasting, product development, sales and operations planning, inventory management, transportation and route optimisation. Thus, enabling organisations to adapt, create contingency plans and manage unforeseen risks.  


Data led marketing, advertisement and sales 

Behind generative AI’s popularity is its ability to produce novel content such as text, videos, audio and more. It took OpenAI just sixty days after launching ChatGPT to reach 100 million users – a first in technology history – due to this ability to create content from simple prompts.  

For retailers, generative AI presents the opportunity to create targeted and personalised content that supports marketing, advertisement and sales, based on market buying behaviours or unique customer purchasing behaviours.  

For example, where customers would formerly receive discounts, suggested items and emails based on the behaviour of a related group ‘customers like you also chose x item’— generative AI takes this to the next level, offering personalised recommendations based on the unique behaviours, buying patterns and historical data of an individual themselves. What’s more, organisations can track these data points to influence future product development, assessing the success of products against others.  

Discover how we helped fashion retailer revolutionise their decision-making with advanced data and AI: 


Virtual ‘try-on’ enables sales 

Generative AI is creating opportunities for virtual ‘try-on’ in fashion retailers. Rather than relying on traditional still model imagery, customers can use themselves as a reference, ‘trying-on’ clothing pieces, jewellery and makeup to see assess if they like these products – a significant marketing and sales tool. While delivering haptic experiences is in talks, retail giant Burberry expressed during Leeds Digital Festival, that we are a ‘long-way off’ from making this happen.  

Is generative AI the sanctuary we think it is?  

The buzz surrounding generative AI use cases in retail has been immense. But is it founded in truth? Despite presenting a myriad of opportunities for the sector, there are still a number of risks that centre around generative AI, including legalities, regulations and localisation bias. 


The dangers of bias, particularly localisation bias 

Generative AI algorithms can be biased and exclude particular subsets of customers. 45% of retail organisations cite AI bias as one of their greatest risks to AI adoption. The dangers of this are skewed outputs that misrepresent particular geographical regions and diverse groups. To address these concerns, retailers must consider ethical AI approaches, introducing diverse datasets when training AI models and overseeing outputs once implemented. 


Crying out for stricter regulations 

Leaders worldwide are calling out for stricter regulations due to the threat that generative AI poses. In the Bletchley Park AI Summit, Elon musk described AI as ‘one of the biggest threats to humanity’ should it be left uncontrolled and unsupervised. During the AI Safety Summit, countries such as the US, UK and China have committed to ensuring that AI is adopted in a ‘human-centric, trustworthy and responsible way’ and this sentiment is shared worldwide by organisations. A report by Accenture found that 97% of respondents believe that AI regulation will impact their organisation in one way or another.  

In NashTech’s generative AI webinar ‘not just a chatbot’, regulation was among one of the top questions asked by the audience. Our advice? Organisations need to think carefully about how they executive generative AI programmes both responsibly and without compromising sensitive company data, while also considering that regulatory policing may come into effect in the future rendering programmes obsolete. 

“‘It’s a brave new world”

Clare Barclay, CEO of Microsoft, London Tech Week 2023

Sensitivities of legal implication 

It’s still early innings when it comes to generative AI and we are yet to see the legal ramifications surrounding its usage. Take for example IP. Generative AI off-the-shelf models such as ChatGPT rely on readily available content that is out readily in the market. Thus, when determining who ‘owns’ the content outputs, the lines are rather blurry. Moreover, inputting sensitive customer data into open-source models breaks GDPR and confidentiality legislations, again putting organisations at legal risk. Legal teams must work together with company users of generative AI models like ChatGPT to minimise these risks. 

“It’s all about embracing change and making sure that we’re working collaboratively in the right by engaging the right teams to make sure you’ve got those guardrails in place.” – Burberry, Digital Festival Leeds.”

Burberry, Digital Festival Leeds

Prepare for the generative AI shift with NashTech 

The adoption of generative AI has led to significant transformation. From changes in the nature of work to substantial productivity shifts. Yet, according to the Nash Squared Digital Leadership Report, less than 15% of organisations are prepared for the generative AI agenda. To deliver personalised customer experience and maintain competitive edge, retail organisations need to start considering generative AI in their digital strategies and fast, while also practicing caution to avoid regulatory lulls down the line. 

At NashTech we practice safe AI implementation, enabling you to deploy cost-efficient and productive programmes that boost the productivity outputs of your organisation. Together our AI experts, security expertise and technology advisory practices can ensure you are adopting the right models and taking the right steps for success. 

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