Viral shopping trends have made retail demand more unpredictable than ever. Products can sell out within hours, driven by TikTok, creators and social commerce rather than traditional buying cycles. David Bailey, Consumer Products Director at Arvato UK, believes this shift is forcing retailers to rethink the way they operate, with AI, automation and connected supply chains becoming essential to staying responsive, protecting customer experience and driving growth.
In the TikTok era, demand can surge almost overnight. TikTok Shop is now the UK’s fourth-largest beauty retailer, and more than 70% of Gen Z beauty purchases are influenced by the platform. That kind of discovery-led shopping is changing the way demand behaves, often turning a product into a must-have within hours rather than weeks. For retailers and brands, the challenge has moved beyond having enough stock. It is increasingly about sensing demand earlier, moving faster and keeping the customer experience intact when pressure hits.
That shift is exposing the limits of traditional commerce operations. Many businesses still run inventory, fulfilment, customer service and returns in separate systems, which makes it harder to respond when demand spikes unexpectedly. If stock sits in the wrong location, warehouse capacity is stretched or returns are too slow to process, the customer feels it quickly. In a market where social commerce can create sudden peaks, those operational gaps are no longer back-office issues. They become revenue and loyalty issues almost immediately.
That is where AI and automation are proving useful, because they help businesses handle volatility more intelligently. AI can spot emerging trends and unusual demand patterns earlier, improve forecasting and support faster decisions about where stock should sit. That matters in categories such as beauty and fashion, where trends can travel quickly across TikTok, Instagram and creator-led channels, and where the difference between selling through and overstocking can be measured in days or hours.
The practical benefit is control to avoid the sort of stock imbalance that leads to missed sales or disappointing delivery promises. That is especially important for businesses trying to balance speed with a seamless customer journey. The consumer does not care that the issue was caused by fragmented systems or poor forecasting. They care about the overall experience – whether the item is available, whether it arrives on time, and whether returns and refunds are handled quickly and efficiently.
Automation and robotics are also playing a growing role, especially in fulfilment and returns. As order volumes increase, businesses need systems that can process items quickly and accurately without introducing errors. Robotics can help speed up repetitive tasks such as sorting, scanning and moving goods through the warehouse, while automation can support more consistent processing in returns, where product condition, packaging and customer behaviour can vary widely. This creates operations that can adapt at pace without compromising service.
That is why fulfilment now sits much closer to the customer experience than it used to. Consumers do not separate the website from the warehouse or the checkout from the delivery network. They simply experience the result. If the item arrives on time and as expected, the brand feels dependable. If something goes wrong, the weaknesses in the operating model become visible very quickly. Retailers that understand this are no longer treating supply chain performance as a purely operational issue. They are treating it as a direct driver of trust and loyalty.
This also applies to personalisation as customers expect recommendations, availability and delivery options to feel tailored to them. But that only works if the operational model behind the scenes is connected enough to support it. That puts new pressure on the supply chain. Personalisation in commerce is not just a front-end marketing capability. It depends on accurate data, responsive inventory and fulfilment systems that can actually deliver on the promise. Without that, the customer journey becomes fragmented very quickly.
Returns are another good example of how operational design shape customer trust. A fast, simple return process can reinforce confidence in the brand, while a slow or confusing one can do the opposite. AI can help businesses understand why items are being returned, spot recurring issues in product fit, quality or descriptions, and route returns more efficiently. Over time, that insight can improve both the customer experience and the underlying product or operational model. In other words, returns are a cost to manage, as well as a source of information that can improve the wider commerce model.
The most effective businesses will be those that combine AI, automation and human judgement in a connected way. Technology can process data, flag exceptions and handle repetitive work. People remain essential for decision-making, customer care and managing the unexpected. In a volatile market, that balance is what creates resilience.
For commerce leaders, the lesson is straightforward. Growth increasingly depends on the ability to respond faster, connect systems more effectively and protect the customer experience even when demand changes suddenly. AI and automation are not the whole answer, but they are becoming a critical part of the operating model for businesses that want to stay relevant, reliable and responsive.
David Bailey
David Bailey is Consumer Products Director at Arvato UK and a member of the Arvato UK Executive Team. With over 30 years’ experience across logistics, operations, and supply chain leadership, David specialises in driving operational excellence, designing scalable solutions, and embedding continuous improvement across complex, multi-site operations.
