The UK has one of the most vibrant and dynamic retail industries in the world, which accounts for 5 per cent of our economy, contributes £98.4bn GVA, employs three million people and has higher productivity growth than almost any other industry. But as the sector continues on its strong growth trajectory, consumers are becoming more demanding about the interactions they have with retail brands. They expect a digitally driven, personalised experience, rapid product delivery and most importantly, efficient resolution of any queries or complaints.
The rapid advancement of Generative AI has presented retailers with a myriad of opportunities to transform customer experience and unlock supply chain efficiencies. But it’s critical that any implementation of the technology is strategically sound and not impulsive. This is perhaps easier said than done when the likes of McKinsey are heralding the potential of AI to generate between $400-600bn of additional value in the retail sector alone. Implementation at pace and scale is a likely temptation for retail brands looking to stay ahead of the competition.
Yet arguably, the greatest gains are to be had from a more considered approach. Generative AI has huge potential, but it must be deployed to tackle a retailer’s biggest pain points first and foremost, whether that’s inefficiencies in back-office operations or a clunky and disjointed customer journey. Trying to transform everything, all at once will seldom deliver the promised economic gains.
But what are the key areas where Generative AI can make a real difference? And how can retailers determine their readiness to implement the technology?
Accuracy in demand forecasting and predictive analysis
AI is playing a pivotal role in revolutionizing Supply Chain. AI driven tools are being used in demand forecasting, inventory planning and procurement. Additionally, AI is adding more power and versatility to the algorithms used for logistics, real time tracking and route optimization improving KPIs and cost efficiency in the supply chain. These advancements are enabling companies to be more agile and responsive to market and customer needs. Additionally, AI driven optimization algorithms can help dynamically fine-tune production schedules, transportation routes and inventory replenishment strategies ensuring higher order fulfilment and customer satisfaction.
Better customer experience
AI is redefining retail across the whole customer experience, from enabling hyper-personalisation and tailored offers to purchase reminders. Chatbots are already an established means of triaging customer queries or helping to signpost them to relevant content or support. Gen AI is being widely acknowledged as a means of summarising product information, improving chatbot engagement and identifying supply chain issues.
For example, retailers can implement gen AI tools or combine them with existing AI tools to enhance the capabilities of chatbots. Through a conversational AI engine, and its ability to utilise next-gen natural language processing and contextual understanding, this application can offer pre-trained solutions for customers whilst mimicking the interaction style of human agents.
How ready are you to embrace AI?
AI has incredible potential to transform retail operations, but it’s not a magic bullet. There are several key considerations before embarking on a Gen AI journey.
Data quality and integrity must be considered; the efficacy of Gen AI is dependent on vast quantities of data, and the output is only as good as the data the algorithm is trained on.
Human oversight of Gen AI outputs is critical to root out bias and drive a cycle of continuous improvement. Human intervention plays a crucial role in the customer journey too, particularly when queries are escalated, require complex solutions, or empathy to manage, then human agents must lead the interaction, but with the support of generative AI to contextualise and summarise key customer info.
The forecasts and decision-making abilities of Gen AI still require human oversight too, for example, it could trigger autonomous purchases based on its predictions which trigger a cycle of shortages and perpetuate demand, among other issues.
Despite the foundational work that must be done, retail is still considered an early adopter of Generative AI technology, with some compelling use cases and applications coming to the fore. Provided implementation is done with consideration and through a strategic lens, its potential to drive further transformation in the year ahead is undeniably exciting.
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