Retail is no longer just about scale. The next decade will belong to companies built on intelligence

For a long time, the formula in retail was relatively simple: build the right brand portfolio, secure the right locations, run operations well and scale efficiently. That model built some of the great retail companies of the last generation but the old playbook is no longer enough.

The traditional boundaries between retail, technology, media, logistics, payments and lifestyle services are disappearing. Retailers behave like technology companies, technology companies are entering commerce and customers move fluidly between physical and digital worlds.

Value is determined by the ecosystem, intelligence and experience you build around the customer, rather than from just what you sell.

Customer expectations have evolved as quickly to include personalization, convenience and immediacy as a baseline. Now, younger generations place as much regard on relevance, purpose, sustainability and experience as they do on product and price.

Add technology to the mix, AI, automation, data platforms and immersive technologies are changing what is operationally possible at scale.

For companies, the question they must ask themselves is no longer whether to adapt but how fundamentally they are willing to rethink the business itself.

AI is becoming embedded in retail’s operating model, shaping decisions, workflows, channels and customer experiences. Most visibly, it is transforming customer engagement.

Recommendation engines, conversational assistants and AI-driven journeys move retail from segment-level marketing to genuine one-to-one engagement, with personalized product discovery, offers and content.

AI is also taking on more customer service and conversion activity across digital and physical channels, driving higher conversion, retention and lifetime value.

Behind the scenes, AI is also changing how retailers forecast demand, replenish stock and design assortments. Predictive models continuously read customer signals, regional trends and operational data, then recommend or auto-execute the right product mix in the right store at the right time, reducing stockouts, excess inventory and required working capital.

Pricing, promotions and marketing are meanwhile becoming increasingly dynamic and data-driven. AI optimizes prices, offers and messaging based on demand, competition, customer behaviour and inventory levels, improving both effectiveness and efficiency.

Further down, supply chains are also becoming more intelligent. AI is improving route planning, warehouse efficiency, last-mile fulfilment and reverse logistics, predicting return behaviour, reducing return rates and matching demand and supply across the network.

Combined with traceability technologies such as blockchain, it is helping create faster, leaner and more transparent supply chains.

Stores themselves are evolving as they become supported or executed by intelligent systems. Automated scheduling, computer vision and real-time location data support operations, reduce losses and enable context-aware customer engagement and in-the-moment promotions, enriching the store into a data-rich node in the network.

When it came to applying these shifts to Apparel Group, a business with more than 85 brands, over 2,500 stores, 14 markets and 27,000 employees, we had to think beyond better apps, faster delivery or sharper loyalty programmes and focus more on the kind of company it should become as the industry changes.

Through a newly established Group Transformation Office, we went about reinventing the business model in a world dominated by AI, data and connected ecosystems.

We concluded we needed to become an AI-native lifestyle enterprise built on proprietary intelligence. This involved becoming an intellectual property-led business, re-architected around data, platforms and the intelligence we increasingly own.

Some of that work is customer-facing, some is operational and some is foundational.

We developed the SuperApp programme, a lifestyle platform beginning with the company’s traditional segments – fashion, footwear, beauty, food, drink and entertainment. However, we found that customers increasingly engage with Apparel Group as a connected lifestyle ecosystem, with higher cross-category engagement driving retention and basket size.

The aim is to expand into broader services that shape how people live, such as financial services, wellness, travel and on-demand delivery, becoming a single intelligent destination in a customer’s life.

Globally, retail is shifting toward platform-based models, while advances in AI, especially personalization and agentic capabilities, now enable a single intelligent system, which made this AI-native ecosystem the next natural evolution of our business.

The business is starting from a formidable foundation, with Club Apparel harbouring more than 16 million members. Our online shopping site, 6th Street, operates across more than 1,400 brands and hundreds of thousands of products and the physical footprint gives us proximity to around 20 and 25 million customers across the Gulf Cooperation Council (GCC) states.

This base is leveraged to provide the following intelligent customer experiences:

Behind the SuperApp or customer experience layer sits the intelligence layer, on which the enterprise runs, elevating ad hoc AI tools into a shared intelligence layer across the Group, known as the Strategic Intelligence and Modelling Stack (SIMS).

The proprietary enterprise AI platform is designed to embed intelligence into the company’s core operations, with the Apparel Brain at the centre – an intelligence layer trained on the Apparel Group’s own operating context: merchandising playbooks, customer behaviour, supplier patterns, operational rhythms and decades of institutional knowledge.

SIMS is already showing up in the business:

Autonomous AI agents will also help human employees across merchandising, finance, procurement, retail operations and market intelligence by removing friction from daily decisions, so teams can focus on higher-value work.

When customer signals, inventory movements, merchandising decisions and supply chain planning start operating closer together, the organization becomes far more agile.

Getting the right data foundation is key, as is leading the required organizational change and creating a culture that genuinely embraces new ways of working. AI built on poor data produces poor decisions at scale, which is worse than no AI at all.

People need to see real value in what is being built, trust the systems and feel empowered by AI rather than threatened by it. That has come through investment in AI fluency and internal innovation, building AI champions across functions, equipping employees to create their own AI tools and rewarding adoption.

AI has to work for the business and for the people. Becoming an AI-native enterprise is, ultimately, less about deploying software and more about changing how decisions are made.

The companies that define the next decade of retail will not necessarily be the ones with the largest store networks or the biggest marketing budgets. They will be those willing to rethink how the enterprise itself operates, moving beyond digitizing the old model and rebuilding around data, intelligence, platforms and connected ecosystems.